1 | +/a/airfield 2 | ||
2 | +/a/airplane_cabin 1 | ||
3 | +/a/airport_terminal 1 | ||
4 | +/a/alcove 1 | ||
5 | +/a/alley 2 | ||
6 | +/a/amphitheater 2 | ||
7 | +/a/amusement_arcade 1 | ||
8 | +/a/amusement_park 2 | ||
9 | +/a/apartment_building/outdoor 2 | ||
10 | +/a/aquarium 1 | ||
11 | +/a/aqueduct 2 | ||
12 | +/a/arcade 1 | ||
13 | +/a/arch 2 | ||
14 | +/a/archaelogical_excavation 1 | ||
15 | +/a/archive 1 | ||
16 | +/a/arena/hockey 1 | ||
17 | +/a/arena/performance 1 | ||
18 | +/a/arena/rodeo 1 | ||
19 | +/a/army_base 2 | ||
20 | +/a/art_gallery 1 | ||
21 | +/a/art_school 1 | ||
22 | +/a/art_studio 1 | ||
23 | +/a/artists_loft 1 | ||
24 | +/a/assembly_line 1 | ||
25 | +/a/athletic_field/outdoor 2 | ||
26 | +/a/atrium/public 1 | ||
27 | +/a/attic 1 | ||
28 | +/a/auditorium 1 | ||
29 | +/a/auto_factory 1 | ||
30 | +/a/auto_showroom 1 | ||
31 | +/b/badlands 2 | ||
32 | +/b/bakery/shop 1 | ||
33 | +/b/balcony/exterior 2 | ||
34 | +/b/balcony/interior 2 | ||
35 | +/b/ball_pit 1 | ||
36 | +/b/ballroom 1 | ||
37 | +/b/bamboo_forest 2 | ||
38 | +/b/bank_vault 1 | ||
39 | +/b/banquet_hall 1 | ||
40 | +/b/bar 1 | ||
41 | +/b/barn 2 | ||
42 | +/b/barndoor 2 | ||
43 | +/b/baseball_field 2 | ||
44 | +/b/basement 1 | ||
45 | +/b/basketball_court/indoor 1 | ||
46 | +/b/bathroom 1 | ||
47 | +/b/bazaar/indoor 1 | ||
48 | +/b/bazaar/outdoor 2 | ||
49 | +/b/beach 2 | ||
50 | +/b/beach_house 2 | ||
51 | +/b/beauty_salon 1 | ||
52 | +/b/bedchamber 1 | ||
53 | +/b/bedroom 1 | ||
54 | +/b/beer_garden 2 | ||
55 | +/b/beer_hall 1 | ||
56 | +/b/berth 1 | ||
57 | +/b/biology_laboratory 1 | ||
58 | +/b/boardwalk 2 | ||
59 | +/b/boat_deck 2 | ||
60 | +/b/boathouse 2 | ||
61 | +/b/bookstore 1 | ||
62 | +/b/booth/indoor 1 | ||
63 | +/b/botanical_garden 2 | ||
64 | +/b/bow_window/indoor 1 | ||
65 | +/b/bowling_alley 1 | ||
66 | +/b/boxing_ring 1 | ||
67 | +/b/bridge 2 | ||
68 | +/b/building_facade 2 | ||
69 | +/b/bullring 2 | ||
70 | +/b/burial_chamber 1 | ||
71 | +/b/bus_interior 1 | ||
72 | +/b/bus_station/indoor 2 | ||
73 | +/b/butchers_shop 1 | ||
74 | +/b/butte 2 | ||
75 | +/c/cabin/outdoor 2 | ||
76 | +/c/cafeteria 1 | ||
77 | +/c/campsite 2 | ||
78 | +/c/campus 2 | ||
79 | +/c/canal/natural 2 | ||
80 | +/c/canal/urban 2 | ||
81 | +/c/candy_store 1 | ||
82 | +/c/canyon 2 | ||
83 | +/c/car_interior 1 | ||
84 | +/c/carrousel 2 | ||
85 | +/c/castle 2 | ||
86 | +/c/catacomb 1 | ||
87 | +/c/cemetery 2 | ||
88 | +/c/chalet 2 | ||
89 | +/c/chemistry_lab 1 | ||
90 | +/c/childs_room 1 | ||
91 | +/c/church/indoor 1 | ||
92 | +/c/church/outdoor 2 | ||
93 | +/c/classroom 1 | ||
94 | +/c/clean_room 1 | ||
95 | +/c/cliff 2 | ||
96 | +/c/closet 1 | ||
97 | +/c/clothing_store 1 | ||
98 | +/c/coast 2 | ||
99 | +/c/cockpit 1 | ||
100 | +/c/coffee_shop 1 | ||
101 | +/c/computer_room 1 | ||
102 | +/c/conference_center 1 | ||
103 | +/c/conference_room 1 | ||
104 | +/c/construction_site 2 | ||
105 | +/c/corn_field 2 | ||
106 | +/c/corral 2 | ||
107 | +/c/corridor 1 | ||
108 | +/c/cottage 2 | ||
109 | +/c/courthouse 2 | ||
110 | +/c/courtyard 2 | ||
111 | +/c/creek 2 | ||
112 | +/c/crevasse 2 | ||
113 | +/c/crosswalk 2 | ||
114 | +/d/dam 2 | ||
115 | +/d/delicatessen 1 | ||
116 | +/d/department_store 1 | ||
117 | +/d/desert/sand 2 | ||
118 | +/d/desert/vegetation 2 | ||
119 | +/d/desert_road 2 | ||
120 | +/d/diner/outdoor 2 | ||
121 | +/d/dining_hall 1 | ||
122 | +/d/dining_room 1 | ||
123 | +/d/discotheque 1 | ||
124 | +/d/doorway/outdoor 2 | ||
125 | +/d/dorm_room 1 | ||
126 | +/d/downtown 2 | ||
127 | +/d/dressing_room 1 | ||
128 | +/d/driveway 2 | ||
129 | +/d/drugstore 1 | ||
130 | +/e/elevator/door 1 | ||
131 | +/e/elevator_lobby 1 | ||
132 | +/e/elevator_shaft 1 | ||
133 | +/e/embassy 2 | ||
134 | +/e/engine_room 1 | ||
135 | +/e/entrance_hall 1 | ||
136 | +/e/escalator/indoor 1 | ||
137 | +/e/excavation 2 | ||
138 | +/f/fabric_store 1 | ||
139 | +/f/farm 2 | ||
140 | +/f/fastfood_restaurant 1 | ||
141 | +/f/field/cultivated 2 | ||
142 | +/f/field/wild 2 | ||
143 | +/f/field_road 2 | ||
144 | +/f/fire_escape 2 | ||
145 | +/f/fire_station 2 | ||
146 | +/f/fishpond 2 | ||
147 | +/f/flea_market/indoor 1 | ||
148 | +/f/florist_shop/indoor 1 | ||
149 | +/f/food_court 1 | ||
150 | +/f/football_field 2 | ||
151 | +/f/forest/broadleaf 2 | ||
152 | +/f/forest_path 2 | ||
153 | +/f/forest_road 2 | ||
154 | +/f/formal_garden 2 | ||
155 | +/f/fountain 2 | ||
156 | +/g/galley 1 | ||
157 | +/g/garage/indoor 1 | ||
158 | +/g/garage/outdoor 2 | ||
159 | +/g/gas_station 2 | ||
160 | +/g/gazebo/exterior 2 | ||
161 | +/g/general_store/indoor 1 | ||
162 | +/g/general_store/outdoor 2 | ||
163 | +/g/gift_shop 1 | ||
164 | +/g/glacier 2 | ||
165 | +/g/golf_course 2 | ||
166 | +/g/greenhouse/indoor 1 | ||
167 | +/g/greenhouse/outdoor 2 | ||
168 | +/g/grotto 2 | ||
169 | +/g/gymnasium/indoor 1 | ||
170 | +/h/hangar/indoor 1 | ||
171 | +/h/hangar/outdoor 2 | ||
172 | +/h/harbor 2 | ||
173 | +/h/hardware_store 1 | ||
174 | +/h/hayfield 2 | ||
175 | +/h/heliport 2 | ||
176 | +/h/highway 2 | ||
177 | +/h/home_office 1 | ||
178 | +/h/home_theater 1 | ||
179 | +/h/hospital 2 | ||
180 | +/h/hospital_room 1 | ||
181 | +/h/hot_spring 2 | ||
182 | +/h/hotel/outdoor 2 | ||
183 | +/h/hotel_room 1 | ||
184 | +/h/house 2 | ||
185 | +/h/hunting_lodge/outdoor 2 | ||
186 | +/i/ice_cream_parlor 1 | ||
187 | +/i/ice_floe 2 | ||
188 | +/i/ice_shelf 2 | ||
189 | +/i/ice_skating_rink/indoor 1 | ||
190 | +/i/ice_skating_rink/outdoor 2 | ||
191 | +/i/iceberg 2 | ||
192 | +/i/igloo 2 | ||
193 | +/i/industrial_area 2 | ||
194 | +/i/inn/outdoor 2 | ||
195 | +/i/islet 2 | ||
196 | +/j/jacuzzi/indoor 1 | ||
197 | +/j/jail_cell 1 | ||
198 | +/j/japanese_garden 2 | ||
199 | +/j/jewelry_shop 1 | ||
200 | +/j/junkyard 2 | ||
201 | +/k/kasbah 2 | ||
202 | +/k/kennel/outdoor 2 | ||
203 | +/k/kindergarden_classroom 1 | ||
204 | +/k/kitchen 1 | ||
205 | +/l/lagoon 2 | ||
206 | +/l/lake/natural 2 | ||
207 | +/l/landfill 2 | ||
208 | +/l/landing_deck 2 | ||
209 | +/l/laundromat 1 | ||
210 | +/l/lawn 2 | ||
211 | +/l/lecture_room 1 | ||
212 | +/l/legislative_chamber 1 | ||
213 | +/l/library/indoor 1 | ||
214 | +/l/library/outdoor 2 | ||
215 | +/l/lighthouse 2 | ||
216 | +/l/living_room 1 | ||
217 | +/l/loading_dock 2 | ||
218 | +/l/lobby 1 | ||
219 | +/l/lock_chamber 2 | ||
220 | +/l/locker_room 1 | ||
221 | +/m/mansion 2 | ||
222 | +/m/manufactured_home 2 | ||
223 | +/m/market/indoor 1 | ||
224 | +/m/market/outdoor 2 | ||
225 | +/m/marsh 2 | ||
226 | +/m/martial_arts_gym 1 | ||
227 | +/m/mausoleum 2 | ||
228 | +/m/medina 2 | ||
229 | +/m/mezzanine 1 | ||
230 | +/m/moat/water 2 | ||
231 | +/m/mosque/outdoor 2 | ||
232 | +/m/motel 2 | ||
233 | +/m/mountain 2 | ||
234 | +/m/mountain_path 2 | ||
235 | +/m/mountain_snowy 2 | ||
236 | +/m/movie_theater/indoor 1 | ||
237 | +/m/museum/indoor 1 | ||
238 | +/m/museum/outdoor 2 | ||
239 | +/m/music_studio 1 | ||
240 | +/n/natural_history_museum 1 | ||
241 | +/n/nursery 1 | ||
242 | +/n/nursing_home 1 | ||
243 | +/o/oast_house 2 | ||
244 | +/o/ocean 2 | ||
245 | +/o/office 1 | ||
246 | +/o/office_building 2 | ||
247 | +/o/office_cubicles 1 | ||
248 | +/o/oilrig 2 | ||
249 | +/o/operating_room 1 | ||
250 | +/o/orchard 2 | ||
251 | +/o/orchestra_pit 1 | ||
252 | +/p/pagoda 2 | ||
253 | +/p/palace 2 | ||
254 | +/p/pantry 1 | ||
255 | +/p/park 2 | ||
256 | +/p/parking_garage/indoor 1 | ||
257 | +/p/parking_garage/outdoor 2 | ||
258 | +/p/parking_lot 2 | ||
259 | +/p/pasture 2 | ||
260 | +/p/patio 2 | ||
261 | +/p/pavilion 2 | ||
262 | +/p/pet_shop 1 | ||
263 | +/p/pharmacy 1 | ||
264 | +/p/phone_booth 2 | ||
265 | +/p/physics_laboratory 1 | ||
266 | +/p/picnic_area 2 | ||
267 | +/p/pier 2 | ||
268 | +/p/pizzeria 1 | ||
269 | +/p/playground 2 | ||
270 | +/p/playroom 1 | ||
271 | +/p/plaza 2 | ||
272 | +/p/pond 2 | ||
273 | +/p/porch 2 | ||
274 | +/p/promenade 2 | ||
275 | +/p/pub/indoor 1 | ||
276 | +/r/racecourse 2 | ||
277 | +/r/raceway 2 | ||
278 | +/r/raft 2 | ||
279 | +/r/railroad_track 2 | ||
280 | +/r/rainforest 2 | ||
281 | +/r/reception 1 | ||
282 | +/r/recreation_room 1 | ||
283 | +/r/repair_shop 1 | ||
284 | +/r/residential_neighborhood 2 | ||
285 | +/r/restaurant 1 | ||
286 | +/r/restaurant_kitchen 1 | ||
287 | +/r/restaurant_patio 2 | ||
288 | +/r/rice_paddy 2 | ||
289 | +/r/river 2 | ||
290 | +/r/rock_arch 2 | ||
291 | +/r/roof_garden 2 | ||
292 | +/r/rope_bridge 2 | ||
293 | +/r/ruin 2 | ||
294 | +/r/runway 2 | ||
295 | +/s/sandbox 2 | ||
296 | +/s/sauna 1 | ||
297 | +/s/schoolhouse 2 | ||
298 | +/s/science_museum 1 | ||
299 | +/s/server_room 1 | ||
300 | +/s/shed 2 | ||
301 | +/s/shoe_shop 1 | ||
302 | +/s/shopfront 2 | ||
303 | +/s/shopping_mall/indoor 1 | ||
304 | +/s/shower 1 | ||
305 | +/s/ski_resort 2 | ||
306 | +/s/ski_slope 2 | ||
307 | +/s/sky 2 | ||
308 | +/s/skyscraper 2 | ||
309 | +/s/slum 2 | ||
310 | +/s/snowfield 2 | ||
311 | +/s/soccer_field 2 | ||
312 | +/s/stable 1 | ||
313 | +/s/stadium/baseball 2 | ||
314 | +/s/stadium/football 2 | ||
315 | +/s/stadium/soccer 2 | ||
316 | +/s/stage/indoor 1 | ||
317 | +/s/stage/outdoor 2 | ||
318 | +/s/staircase 1 | ||
319 | +/s/storage_room 1 | ||
320 | +/s/street 2 | ||
321 | +/s/subway_station/platform 1 | ||
322 | +/s/supermarket 1 | ||
323 | +/s/sushi_bar 1 | ||
324 | +/s/swamp 2 | ||
325 | +/s/swimming_hole 1 | ||
326 | +/s/swimming_pool/indoor 1 | ||
327 | +/s/swimming_pool/outdoor 2 | ||
328 | +/s/synagogue/outdoor 2 | ||
329 | +/t/television_room 1 | ||
330 | +/t/television_studio 1 | ||
331 | +/t/temple/asia 2 | ||
332 | +/t/throne_room 1 | ||
333 | +/t/ticket_booth 1 | ||
334 | +/t/topiary_garden 2 | ||
335 | +/t/tower 2 | ||
336 | +/t/toyshop 1 | ||
337 | +/t/train_interior 1 | ||
338 | +/t/train_station/platform 1 | ||
339 | +/t/tree_farm 2 | ||
340 | +/t/tree_house 2 | ||
341 | +/t/trench 2 | ||
342 | +/t/tundra 2 | ||
343 | +/u/underwater/ocean_deep 2 | ||
344 | +/u/utility_room 1 | ||
345 | +/v/valley 2 | ||
346 | +/v/vegetable_garden 2 | ||
347 | +/v/veterinarians_office 1 | ||
348 | +/v/viaduct 2 | ||
349 | +/v/village 2 | ||
350 | +/v/vineyard 2 | ||
351 | +/v/volcano 2 | ||
352 | +/v/volleyball_court/outdoor 2 | ||
353 | +/w/waiting_room 1 | ||
354 | +/w/water_park 2 | ||
355 | +/w/water_tower 2 | ||
356 | +/w/waterfall 2 | ||
357 | +/w/watering_hole 2 | ||
358 | +/w/wave 2 | ||
359 | +/w/wet_bar 1 | ||
360 | +/w/wheat_field 2 | ||
361 | +/w/wind_farm 2 | ||
362 | +/w/windmill 2 | ||
363 | +/y/yard 2 | ||
364 | +/y/youth_hostel 1 | ||
365 | +/z/zen_garden 2 |
1 | +/a/airfield 0 | ||
2 | +/a/airplane_cabin 1 | ||
3 | +/a/airport_terminal 2 | ||
4 | +/a/alcove 3 | ||
5 | +/a/alley 4 | ||
6 | +/a/amphitheater 5 | ||
7 | +/a/amusement_arcade 6 | ||
8 | +/a/amusement_park 7 | ||
9 | +/a/apartment_building/outdoor 8 | ||
10 | +/a/aquarium 9 | ||
11 | +/a/aqueduct 10 | ||
12 | +/a/arcade 11 | ||
13 | +/a/arch 12 | ||
14 | +/a/archaelogical_excavation 13 | ||
15 | +/a/archive 14 | ||
16 | +/a/arena/hockey 15 | ||
17 | +/a/arena/performance 16 | ||
18 | +/a/arena/rodeo 17 | ||
19 | +/a/army_base 18 | ||
20 | +/a/art_gallery 19 | ||
21 | +/a/art_school 20 | ||
22 | +/a/art_studio 21 | ||
23 | +/a/artists_loft 22 | ||
24 | +/a/assembly_line 23 | ||
25 | +/a/athletic_field/outdoor 24 | ||
26 | +/a/atrium/public 25 | ||
27 | +/a/attic 26 | ||
28 | +/a/auditorium 27 | ||
29 | +/a/auto_factory 28 | ||
30 | +/a/auto_showroom 29 | ||
31 | +/b/badlands 30 | ||
32 | +/b/bakery/shop 31 | ||
33 | +/b/balcony/exterior 32 | ||
34 | +/b/balcony/interior 33 | ||
35 | +/b/ball_pit 34 | ||
36 | +/b/ballroom 35 | ||
37 | +/b/bamboo_forest 36 | ||
38 | +/b/bank_vault 37 | ||
39 | +/b/banquet_hall 38 | ||
40 | +/b/bar 39 | ||
41 | +/b/barn 40 | ||
42 | +/b/barndoor 41 | ||
43 | +/b/baseball_field 42 | ||
44 | +/b/basement 43 | ||
45 | +/b/basketball_court/indoor 44 | ||
46 | +/b/bathroom 45 | ||
47 | +/b/bazaar/indoor 46 | ||
48 | +/b/bazaar/outdoor 47 | ||
49 | +/b/beach 48 | ||
50 | +/b/beach_house 49 | ||
51 | +/b/beauty_salon 50 | ||
52 | +/b/bedchamber 51 | ||
53 | +/b/bedroom 52 | ||
54 | +/b/beer_garden 53 | ||
55 | +/b/beer_hall 54 | ||
56 | +/b/berth 55 | ||
57 | +/b/biology_laboratory 56 | ||
58 | +/b/boardwalk 57 | ||
59 | +/b/boat_deck 58 | ||
60 | +/b/boathouse 59 | ||
61 | +/b/bookstore 60 | ||
62 | +/b/booth/indoor 61 | ||
63 | +/b/botanical_garden 62 | ||
64 | +/b/bow_window/indoor 63 | ||
65 | +/b/bowling_alley 64 | ||
66 | +/b/boxing_ring 65 | ||
67 | +/b/bridge 66 | ||
68 | +/b/building_facade 67 | ||
69 | +/b/bullring 68 | ||
70 | +/b/burial_chamber 69 | ||
71 | +/b/bus_interior 70 | ||
72 | +/b/bus_station/indoor 71 | ||
73 | +/b/butchers_shop 72 | ||
74 | +/b/butte 73 | ||
75 | +/c/cabin/outdoor 74 | ||
76 | +/c/cafeteria 75 | ||
77 | +/c/campsite 76 | ||
78 | +/c/campus 77 | ||
79 | +/c/canal/natural 78 | ||
80 | +/c/canal/urban 79 | ||
81 | +/c/candy_store 80 | ||
82 | +/c/canyon 81 | ||
83 | +/c/car_interior 82 | ||
84 | +/c/carrousel 83 | ||
85 | +/c/castle 84 | ||
86 | +/c/catacomb 85 | ||
87 | +/c/cemetery 86 | ||
88 | +/c/chalet 87 | ||
89 | +/c/chemistry_lab 88 | ||
90 | +/c/childs_room 89 | ||
91 | +/c/church/indoor 90 | ||
92 | +/c/church/outdoor 91 | ||
93 | +/c/classroom 92 | ||
94 | +/c/clean_room 93 | ||
95 | +/c/cliff 94 | ||
96 | +/c/closet 95 | ||
97 | +/c/clothing_store 96 | ||
98 | +/c/coast 97 | ||
99 | +/c/cockpit 98 | ||
100 | +/c/coffee_shop 99 | ||
101 | +/c/computer_room 100 | ||
102 | +/c/conference_center 101 | ||
103 | +/c/conference_room 102 | ||
104 | +/c/construction_site 103 | ||
105 | +/c/corn_field 104 | ||
106 | +/c/corral 105 | ||
107 | +/c/corridor 106 | ||
108 | +/c/cottage 107 | ||
109 | +/c/courthouse 108 | ||
110 | +/c/courtyard 109 | ||
111 | +/c/creek 110 | ||
112 | +/c/crevasse 111 | ||
113 | +/c/crosswalk 112 | ||
114 | +/d/dam 113 | ||
115 | +/d/delicatessen 114 | ||
116 | +/d/department_store 115 | ||
117 | +/d/desert/sand 116 | ||
118 | +/d/desert/vegetation 117 | ||
119 | +/d/desert_road 118 | ||
120 | +/d/diner/outdoor 119 | ||
121 | +/d/dining_hall 120 | ||
122 | +/d/dining_room 121 | ||
123 | +/d/discotheque 122 | ||
124 | +/d/doorway/outdoor 123 | ||
125 | +/d/dorm_room 124 | ||
126 | +/d/downtown 125 | ||
127 | +/d/dressing_room 126 | ||
128 | +/d/driveway 127 | ||
129 | +/d/drugstore 128 | ||
130 | +/e/elevator/door 129 | ||
131 | +/e/elevator_lobby 130 | ||
132 | +/e/elevator_shaft 131 | ||
133 | +/e/embassy 132 | ||
134 | +/e/engine_room 133 | ||
135 | +/e/entrance_hall 134 | ||
136 | +/e/escalator/indoor 135 | ||
137 | +/e/excavation 136 | ||
138 | +/f/fabric_store 137 | ||
139 | +/f/farm 138 | ||
140 | +/f/fastfood_restaurant 139 | ||
141 | +/f/field/cultivated 140 | ||
142 | +/f/field/wild 141 | ||
143 | +/f/field_road 142 | ||
144 | +/f/fire_escape 143 | ||
145 | +/f/fire_station 144 | ||
146 | +/f/fishpond 145 | ||
147 | +/f/flea_market/indoor 146 | ||
148 | +/f/florist_shop/indoor 147 | ||
149 | +/f/food_court 148 | ||
150 | +/f/football_field 149 | ||
151 | +/f/forest/broadleaf 150 | ||
152 | +/f/forest_path 151 | ||
153 | +/f/forest_road 152 | ||
154 | +/f/formal_garden 153 | ||
155 | +/f/fountain 154 | ||
156 | +/g/galley 155 | ||
157 | +/g/garage/indoor 156 | ||
158 | +/g/garage/outdoor 157 | ||
159 | +/g/gas_station 158 | ||
160 | +/g/gazebo/exterior 159 | ||
161 | +/g/general_store/indoor 160 | ||
162 | +/g/general_store/outdoor 161 | ||
163 | +/g/gift_shop 162 | ||
164 | +/g/glacier 163 | ||
165 | +/g/golf_course 164 | ||
166 | +/g/greenhouse/indoor 165 | ||
167 | +/g/greenhouse/outdoor 166 | ||
168 | +/g/grotto 167 | ||
169 | +/g/gymnasium/indoor 168 | ||
170 | +/h/hangar/indoor 169 | ||
171 | +/h/hangar/outdoor 170 | ||
172 | +/h/harbor 171 | ||
173 | +/h/hardware_store 172 | ||
174 | +/h/hayfield 173 | ||
175 | +/h/heliport 174 | ||
176 | +/h/highway 175 | ||
177 | +/h/home_office 176 | ||
178 | +/h/home_theater 177 | ||
179 | +/h/hospital 178 | ||
180 | +/h/hospital_room 179 | ||
181 | +/h/hot_spring 180 | ||
182 | +/h/hotel/outdoor 181 | ||
183 | +/h/hotel_room 182 | ||
184 | +/h/house 183 | ||
185 | +/h/hunting_lodge/outdoor 184 | ||
186 | +/i/ice_cream_parlor 185 | ||
187 | +/i/ice_floe 186 | ||
188 | +/i/ice_shelf 187 | ||
189 | +/i/ice_skating_rink/indoor 188 | ||
190 | +/i/ice_skating_rink/outdoor 189 | ||
191 | +/i/iceberg 190 | ||
192 | +/i/igloo 191 | ||
193 | +/i/industrial_area 192 | ||
194 | +/i/inn/outdoor 193 | ||
195 | +/i/islet 194 | ||
196 | +/j/jacuzzi/indoor 195 | ||
197 | +/j/jail_cell 196 | ||
198 | +/j/japanese_garden 197 | ||
199 | +/j/jewelry_shop 198 | ||
200 | +/j/junkyard 199 | ||
201 | +/k/kasbah 200 | ||
202 | +/k/kennel/outdoor 201 | ||
203 | +/k/kindergarden_classroom 202 | ||
204 | +/k/kitchen 203 | ||
205 | +/l/lagoon 204 | ||
206 | +/l/lake/natural 205 | ||
207 | +/l/landfill 206 | ||
208 | +/l/landing_deck 207 | ||
209 | +/l/laundromat 208 | ||
210 | +/l/lawn 209 | ||
211 | +/l/lecture_room 210 | ||
212 | +/l/legislative_chamber 211 | ||
213 | +/l/library/indoor 212 | ||
214 | +/l/library/outdoor 213 | ||
215 | +/l/lighthouse 214 | ||
216 | +/l/living_room 215 | ||
217 | +/l/loading_dock 216 | ||
218 | +/l/lobby 217 | ||
219 | +/l/lock_chamber 218 | ||
220 | +/l/locker_room 219 | ||
221 | +/m/mansion 220 | ||
222 | +/m/manufactured_home 221 | ||
223 | +/m/market/indoor 222 | ||
224 | +/m/market/outdoor 223 | ||
225 | +/m/marsh 224 | ||
226 | +/m/martial_arts_gym 225 | ||
227 | +/m/mausoleum 226 | ||
228 | +/m/medina 227 | ||
229 | +/m/mezzanine 228 | ||
230 | +/m/moat/water 229 | ||
231 | +/m/mosque/outdoor 230 | ||
232 | +/m/motel 231 | ||
233 | +/m/mountain 232 | ||
234 | +/m/mountain_path 233 | ||
235 | +/m/mountain_snowy 234 | ||
236 | +/m/movie_theater/indoor 235 | ||
237 | +/m/museum/indoor 236 | ||
238 | +/m/museum/outdoor 237 | ||
239 | +/m/music_studio 238 | ||
240 | +/n/natural_history_museum 239 | ||
241 | +/n/nursery 240 | ||
242 | +/n/nursing_home 241 | ||
243 | +/o/oast_house 242 | ||
244 | +/o/ocean 243 | ||
245 | +/o/office 244 | ||
246 | +/o/office_building 245 | ||
247 | +/o/office_cubicles 246 | ||
248 | +/o/oilrig 247 | ||
249 | +/o/operating_room 248 | ||
250 | +/o/orchard 249 | ||
251 | +/o/orchestra_pit 250 | ||
252 | +/p/pagoda 251 | ||
253 | +/p/palace 252 | ||
254 | +/p/pantry 253 | ||
255 | +/p/park 254 | ||
256 | +/p/parking_garage/indoor 255 | ||
257 | +/p/parking_garage/outdoor 256 | ||
258 | +/p/parking_lot 257 | ||
259 | +/p/pasture 258 | ||
260 | +/p/patio 259 | ||
261 | +/p/pavilion 260 | ||
262 | +/p/pet_shop 261 | ||
263 | +/p/pharmacy 262 | ||
264 | +/p/phone_booth 263 | ||
265 | +/p/physics_laboratory 264 | ||
266 | +/p/picnic_area 265 | ||
267 | +/p/pier 266 | ||
268 | +/p/pizzeria 267 | ||
269 | +/p/playground 268 | ||
270 | +/p/playroom 269 | ||
271 | +/p/plaza 270 | ||
272 | +/p/pond 271 | ||
273 | +/p/porch 272 | ||
274 | +/p/promenade 273 | ||
275 | +/p/pub/indoor 274 | ||
276 | +/r/racecourse 275 | ||
277 | +/r/raceway 276 | ||
278 | +/r/raft 277 | ||
279 | +/r/railroad_track 278 | ||
280 | +/r/rainforest 279 | ||
281 | +/r/reception 280 | ||
282 | +/r/recreation_room 281 | ||
283 | +/r/repair_shop 282 | ||
284 | +/r/residential_neighborhood 283 | ||
285 | +/r/restaurant 284 | ||
286 | +/r/restaurant_kitchen 285 | ||
287 | +/r/restaurant_patio 286 | ||
288 | +/r/rice_paddy 287 | ||
289 | +/r/river 288 | ||
290 | +/r/rock_arch 289 | ||
291 | +/r/roof_garden 290 | ||
292 | +/r/rope_bridge 291 | ||
293 | +/r/ruin 292 | ||
294 | +/r/runway 293 | ||
295 | +/s/sandbox 294 | ||
296 | +/s/sauna 295 | ||
297 | +/s/schoolhouse 296 | ||
298 | +/s/science_museum 297 | ||
299 | +/s/server_room 298 | ||
300 | +/s/shed 299 | ||
301 | +/s/shoe_shop 300 | ||
302 | +/s/shopfront 301 | ||
303 | +/s/shopping_mall/indoor 302 | ||
304 | +/s/shower 303 | ||
305 | +/s/ski_resort 304 | ||
306 | +/s/ski_slope 305 | ||
307 | +/s/sky 306 | ||
308 | +/s/skyscraper 307 | ||
309 | +/s/slum 308 | ||
310 | +/s/snowfield 309 | ||
311 | +/s/soccer_field 310 | ||
312 | +/s/stable 311 | ||
313 | +/s/stadium/baseball 312 | ||
314 | +/s/stadium/football 313 | ||
315 | +/s/stadium/soccer 314 | ||
316 | +/s/stage/indoor 315 | ||
317 | +/s/stage/outdoor 316 | ||
318 | +/s/staircase 317 | ||
319 | +/s/storage_room 318 | ||
320 | +/s/street 319 | ||
321 | +/s/subway_station/platform 320 | ||
322 | +/s/supermarket 321 | ||
323 | +/s/sushi_bar 322 | ||
324 | +/s/swamp 323 | ||
325 | +/s/swimming_hole 324 | ||
326 | +/s/swimming_pool/indoor 325 | ||
327 | +/s/swimming_pool/outdoor 326 | ||
328 | +/s/synagogue/outdoor 327 | ||
329 | +/t/television_room 328 | ||
330 | +/t/television_studio 329 | ||
331 | +/t/temple/asia 330 | ||
332 | +/t/throne_room 331 | ||
333 | +/t/ticket_booth 332 | ||
334 | +/t/topiary_garden 333 | ||
335 | +/t/tower 334 | ||
336 | +/t/toyshop 335 | ||
337 | +/t/train_interior 336 | ||
338 | +/t/train_station/platform 337 | ||
339 | +/t/tree_farm 338 | ||
340 | +/t/tree_house 339 | ||
341 | +/t/trench 340 | ||
342 | +/t/tundra 341 | ||
343 | +/u/underwater/ocean_deep 342 | ||
344 | +/u/utility_room 343 | ||
345 | +/v/valley 344 | ||
346 | +/v/vegetable_garden 345 | ||
347 | +/v/veterinarians_office 346 | ||
348 | +/v/viaduct 347 | ||
349 | +/v/village 348 | ||
350 | +/v/vineyard 349 | ||
351 | +/v/volcano 350 | ||
352 | +/v/volleyball_court/outdoor 351 | ||
353 | +/w/waiting_room 352 | ||
354 | +/w/water_park 353 | ||
355 | +/w/water_tower 354 | ||
356 | +/w/waterfall 355 | ||
357 | +/w/watering_hole 356 | ||
358 | +/w/wave 357 | ||
359 | +/w/wet_bar 358 | ||
360 | +/w/wheat_field 359 | ||
361 | +/w/wind_farm 360 | ||
362 | +/w/windmill 361 | ||
363 | +/y/yard 362 | ||
364 | +/y/youth_hostel 363 | ||
365 | +/z/zen_garden 364 | ||
... | \ No newline at end of file | ... | \ No newline at end of file |
1 | +[net] | ||
2 | +# Testing | ||
3 | +#batch=1 | ||
4 | +#subdivisions=1 | ||
5 | +# Training | ||
6 | +batch=64 | ||
7 | +subdivisions=16 | ||
8 | +width=512 | ||
9 | +height=512 | ||
10 | +channels=3 | ||
11 | +momentum=0.9 | ||
12 | +decay=0.0005 | ||
13 | +angle=0 | ||
14 | +saturation = 1.5 | ||
15 | +exposure = 1.5 | ||
16 | +hue=.1 | ||
17 | + | ||
18 | +learning_rate=0.0001 | ||
19 | +burn_in=1000 | ||
20 | +max_batches = 500200 | ||
21 | +policy=steps | ||
22 | +steps=400000,450000 | ||
23 | +scales=.1,.1 | ||
24 | +max_epochs = 300 | ||
25 | + | ||
26 | +[convolutional] | ||
27 | +batch_normalize=1 | ||
28 | +filters=32 | ||
29 | +size=3 | ||
30 | +stride=1 | ||
31 | +pad=1 | ||
32 | +activation=leaky | ||
33 | + | ||
34 | +# Downsample | ||
35 | + | ||
36 | +[convolutional] | ||
37 | +batch_normalize=1 | ||
38 | +filters=64 | ||
39 | +size=3 | ||
40 | +stride=2 | ||
41 | +pad=1 | ||
42 | +activation=leaky | ||
43 | + | ||
44 | +[convolutional] | ||
45 | +batch_normalize=1 | ||
46 | +filters=32 | ||
47 | +size=1 | ||
48 | +stride=1 | ||
49 | +pad=1 | ||
50 | +activation=leaky | ||
51 | + | ||
52 | +[convolutional] | ||
53 | +batch_normalize=1 | ||
54 | +filters=64 | ||
55 | +size=3 | ||
56 | +stride=1 | ||
57 | +pad=1 | ||
58 | +activation=leaky | ||
59 | + | ||
60 | +[shortcut] | ||
61 | +from=-3 | ||
62 | +activation=linear | ||
63 | + | ||
64 | +# Downsample | ||
65 | + | ||
66 | +[convolutional] | ||
67 | +batch_normalize=1 | ||
68 | +filters=128 | ||
69 | +size=3 | ||
70 | +stride=2 | ||
71 | +pad=1 | ||
72 | +activation=leaky | ||
73 | + | ||
74 | +[convolutional] | ||
75 | +batch_normalize=1 | ||
76 | +filters=64 | ||
77 | +size=1 | ||
78 | +stride=1 | ||
79 | +pad=1 | ||
80 | +activation=leaky | ||
81 | + | ||
82 | +[convolutional] | ||
83 | +batch_normalize=1 | ||
84 | +filters=128 | ||
85 | +size=3 | ||
86 | +stride=1 | ||
87 | +pad=1 | ||
88 | +activation=leaky | ||
89 | + | ||
90 | +[shortcut] | ||
91 | +from=-3 | ||
92 | +activation=linear | ||
93 | + | ||
94 | +[convolutional] | ||
95 | +batch_normalize=1 | ||
96 | +filters=64 | ||
97 | +size=1 | ||
98 | +stride=1 | ||
99 | +pad=1 | ||
100 | +activation=leaky | ||
101 | + | ||
102 | +[convolutional] | ||
103 | +batch_normalize=1 | ||
104 | +filters=128 | ||
105 | +size=3 | ||
106 | +stride=1 | ||
107 | +pad=1 | ||
108 | +activation=leaky | ||
109 | + | ||
110 | +[shortcut] | ||
111 | +from=-3 | ||
112 | +activation=linear | ||
113 | + | ||
114 | +# Downsample | ||
115 | + | ||
116 | +[convolutional] | ||
117 | +batch_normalize=1 | ||
118 | +filters=256 | ||
119 | +size=3 | ||
120 | +stride=2 | ||
121 | +pad=1 | ||
122 | +activation=leaky | ||
123 | + | ||
124 | +[convolutional] | ||
125 | +batch_normalize=1 | ||
126 | +filters=128 | ||
127 | +size=1 | ||
128 | +stride=1 | ||
129 | +pad=1 | ||
130 | +activation=leaky | ||
131 | + | ||
132 | +[convolutional] | ||
133 | +batch_normalize=1 | ||
134 | +filters=256 | ||
135 | +size=3 | ||
136 | +stride=1 | ||
137 | +pad=1 | ||
138 | +activation=leaky | ||
139 | + | ||
140 | +[shortcut] | ||
141 | +from=-3 | ||
142 | +activation=linear | ||
143 | + | ||
144 | +[convolutional] | ||
145 | +batch_normalize=1 | ||
146 | +filters=128 | ||
147 | +size=1 | ||
148 | +stride=1 | ||
149 | +pad=1 | ||
150 | +activation=leaky | ||
151 | + | ||
152 | +[convolutional] | ||
153 | +batch_normalize=1 | ||
154 | +filters=256 | ||
155 | +size=3 | ||
156 | +stride=1 | ||
157 | +pad=1 | ||
158 | +activation=leaky | ||
159 | + | ||
160 | +[shortcut] | ||
161 | +from=-3 | ||
162 | +activation=linear | ||
163 | + | ||
164 | +[convolutional] | ||
165 | +batch_normalize=1 | ||
166 | +filters=128 | ||
167 | +size=1 | ||
168 | +stride=1 | ||
169 | +pad=1 | ||
170 | +activation=leaky | ||
171 | + | ||
172 | +[convolutional] | ||
173 | +batch_normalize=1 | ||
174 | +filters=256 | ||
175 | +size=3 | ||
176 | +stride=1 | ||
177 | +pad=1 | ||
178 | +activation=leaky | ||
179 | + | ||
180 | +[shortcut] | ||
181 | +from=-3 | ||
182 | +activation=linear | ||
183 | + | ||
184 | +[convolutional] | ||
185 | +batch_normalize=1 | ||
186 | +filters=128 | ||
187 | +size=1 | ||
188 | +stride=1 | ||
189 | +pad=1 | ||
190 | +activation=leaky | ||
191 | + | ||
192 | +[convolutional] | ||
193 | +batch_normalize=1 | ||
194 | +filters=256 | ||
195 | +size=3 | ||
196 | +stride=1 | ||
197 | +pad=1 | ||
198 | +activation=leaky | ||
199 | + | ||
200 | +[shortcut] | ||
201 | +from=-3 | ||
202 | +activation=linear | ||
203 | + | ||
204 | + | ||
205 | +[convolutional] | ||
206 | +batch_normalize=1 | ||
207 | +filters=128 | ||
208 | +size=1 | ||
209 | +stride=1 | ||
210 | +pad=1 | ||
211 | +activation=leaky | ||
212 | + | ||
213 | +[convolutional] | ||
214 | +batch_normalize=1 | ||
215 | +filters=256 | ||
216 | +size=3 | ||
217 | +stride=1 | ||
218 | +pad=1 | ||
219 | +activation=leaky | ||
220 | + | ||
221 | +[shortcut] | ||
222 | +from=-3 | ||
223 | +activation=linear | ||
224 | + | ||
225 | +[convolutional] | ||
226 | +batch_normalize=1 | ||
227 | +filters=128 | ||
228 | +size=1 | ||
229 | +stride=1 | ||
230 | +pad=1 | ||
231 | +activation=leaky | ||
232 | + | ||
233 | +[convolutional] | ||
234 | +batch_normalize=1 | ||
235 | +filters=256 | ||
236 | +size=3 | ||
237 | +stride=1 | ||
238 | +pad=1 | ||
239 | +activation=leaky | ||
240 | + | ||
241 | +[shortcut] | ||
242 | +from=-3 | ||
243 | +activation=linear | ||
244 | + | ||
245 | +[convolutional] | ||
246 | +batch_normalize=1 | ||
247 | +filters=128 | ||
248 | +size=1 | ||
249 | +stride=1 | ||
250 | +pad=1 | ||
251 | +activation=leaky | ||
252 | + | ||
253 | +[convolutional] | ||
254 | +batch_normalize=1 | ||
255 | +filters=256 | ||
256 | +size=3 | ||
257 | +stride=1 | ||
258 | +pad=1 | ||
259 | +activation=leaky | ||
260 | + | ||
261 | +[shortcut] | ||
262 | +from=-3 | ||
263 | +activation=linear | ||
264 | + | ||
265 | +[convolutional] | ||
266 | +batch_normalize=1 | ||
267 | +filters=128 | ||
268 | +size=1 | ||
269 | +stride=1 | ||
270 | +pad=1 | ||
271 | +activation=leaky | ||
272 | + | ||
273 | +[convolutional] | ||
274 | +batch_normalize=1 | ||
275 | +filters=256 | ||
276 | +size=3 | ||
277 | +stride=1 | ||
278 | +pad=1 | ||
279 | +activation=leaky | ||
280 | + | ||
281 | +[shortcut] | ||
282 | +from=-3 | ||
283 | +activation=linear | ||
284 | + | ||
285 | +# Downsample | ||
286 | + | ||
287 | +[convolutional] | ||
288 | +batch_normalize=1 | ||
289 | +filters=512 | ||
290 | +size=3 | ||
291 | +stride=2 | ||
292 | +pad=1 | ||
293 | +activation=leaky | ||
294 | + | ||
295 | +[convolutional] | ||
296 | +batch_normalize=1 | ||
297 | +filters=256 | ||
298 | +size=1 | ||
299 | +stride=1 | ||
300 | +pad=1 | ||
301 | +activation=leaky | ||
302 | + | ||
303 | +[convolutional] | ||
304 | +batch_normalize=1 | ||
305 | +filters=512 | ||
306 | +size=3 | ||
307 | +stride=1 | ||
308 | +pad=1 | ||
309 | +activation=leaky | ||
310 | + | ||
311 | +[shortcut] | ||
312 | +from=-3 | ||
313 | +activation=linear | ||
314 | + | ||
315 | + | ||
316 | +[convolutional] | ||
317 | +batch_normalize=1 | ||
318 | +filters=256 | ||
319 | +size=1 | ||
320 | +stride=1 | ||
321 | +pad=1 | ||
322 | +activation=leaky | ||
323 | + | ||
324 | +[convolutional] | ||
325 | +batch_normalize=1 | ||
326 | +filters=512 | ||
327 | +size=3 | ||
328 | +stride=1 | ||
329 | +pad=1 | ||
330 | +activation=leaky | ||
331 | + | ||
332 | +[shortcut] | ||
333 | +from=-3 | ||
334 | +activation=linear | ||
335 | + | ||
336 | + | ||
337 | +[convolutional] | ||
338 | +batch_normalize=1 | ||
339 | +filters=256 | ||
340 | +size=1 | ||
341 | +stride=1 | ||
342 | +pad=1 | ||
343 | +activation=leaky | ||
344 | + | ||
345 | +[convolutional] | ||
346 | +batch_normalize=1 | ||
347 | +filters=512 | ||
348 | +size=3 | ||
349 | +stride=1 | ||
350 | +pad=1 | ||
351 | +activation=leaky | ||
352 | + | ||
353 | +[shortcut] | ||
354 | +from=-3 | ||
355 | +activation=linear | ||
356 | + | ||
357 | + | ||
358 | +[convolutional] | ||
359 | +batch_normalize=1 | ||
360 | +filters=256 | ||
361 | +size=1 | ||
362 | +stride=1 | ||
363 | +pad=1 | ||
364 | +activation=leaky | ||
365 | + | ||
366 | +[convolutional] | ||
367 | +batch_normalize=1 | ||
368 | +filters=512 | ||
369 | +size=3 | ||
370 | +stride=1 | ||
371 | +pad=1 | ||
372 | +activation=leaky | ||
373 | + | ||
374 | +[shortcut] | ||
375 | +from=-3 | ||
376 | +activation=linear | ||
377 | + | ||
378 | +[convolutional] | ||
379 | +batch_normalize=1 | ||
380 | +filters=256 | ||
381 | +size=1 | ||
382 | +stride=1 | ||
383 | +pad=1 | ||
384 | +activation=leaky | ||
385 | + | ||
386 | +[convolutional] | ||
387 | +batch_normalize=1 | ||
388 | +filters=512 | ||
389 | +size=3 | ||
390 | +stride=1 | ||
391 | +pad=1 | ||
392 | +activation=leaky | ||
393 | + | ||
394 | +[shortcut] | ||
395 | +from=-3 | ||
396 | +activation=linear | ||
397 | + | ||
398 | + | ||
399 | +[convolutional] | ||
400 | +batch_normalize=1 | ||
401 | +filters=256 | ||
402 | +size=1 | ||
403 | +stride=1 | ||
404 | +pad=1 | ||
405 | +activation=leaky | ||
406 | + | ||
407 | +[convolutional] | ||
408 | +batch_normalize=1 | ||
409 | +filters=512 | ||
410 | +size=3 | ||
411 | +stride=1 | ||
412 | +pad=1 | ||
413 | +activation=leaky | ||
414 | + | ||
415 | +[shortcut] | ||
416 | +from=-3 | ||
417 | +activation=linear | ||
418 | + | ||
419 | + | ||
420 | +[convolutional] | ||
421 | +batch_normalize=1 | ||
422 | +filters=256 | ||
423 | +size=1 | ||
424 | +stride=1 | ||
425 | +pad=1 | ||
426 | +activation=leaky | ||
427 | + | ||
428 | +[convolutional] | ||
429 | +batch_normalize=1 | ||
430 | +filters=512 | ||
431 | +size=3 | ||
432 | +stride=1 | ||
433 | +pad=1 | ||
434 | +activation=leaky | ||
435 | + | ||
436 | +[shortcut] | ||
437 | +from=-3 | ||
438 | +activation=linear | ||
439 | + | ||
440 | +[convolutional] | ||
441 | +batch_normalize=1 | ||
442 | +filters=256 | ||
443 | +size=1 | ||
444 | +stride=1 | ||
445 | +pad=1 | ||
446 | +activation=leaky | ||
447 | + | ||
448 | +[convolutional] | ||
449 | +batch_normalize=1 | ||
450 | +filters=512 | ||
451 | +size=3 | ||
452 | +stride=1 | ||
453 | +pad=1 | ||
454 | +activation=leaky | ||
455 | + | ||
456 | +[shortcut] | ||
457 | +from=-3 | ||
458 | +activation=linear | ||
459 | + | ||
460 | +# Downsample | ||
461 | + | ||
462 | +[convolutional] | ||
463 | +batch_normalize=1 | ||
464 | +filters=1024 | ||
465 | +size=3 | ||
466 | +stride=2 | ||
467 | +pad=1 | ||
468 | +activation=leaky | ||
469 | + | ||
470 | +[convolutional] | ||
471 | +batch_normalize=1 | ||
472 | +filters=512 | ||
473 | +size=1 | ||
474 | +stride=1 | ||
475 | +pad=1 | ||
476 | +activation=leaky | ||
477 | + | ||
478 | +[convolutional] | ||
479 | +batch_normalize=1 | ||
480 | +filters=1024 | ||
481 | +size=3 | ||
482 | +stride=1 | ||
483 | +pad=1 | ||
484 | +activation=leaky | ||
485 | + | ||
486 | +[shortcut] | ||
487 | +from=-3 | ||
488 | +activation=linear | ||
489 | + | ||
490 | +[convolutional] | ||
491 | +batch_normalize=1 | ||
492 | +filters=512 | ||
493 | +size=1 | ||
494 | +stride=1 | ||
495 | +pad=1 | ||
496 | +activation=leaky | ||
497 | + | ||
498 | +[convolutional] | ||
499 | +batch_normalize=1 | ||
500 | +filters=1024 | ||
501 | +size=3 | ||
502 | +stride=1 | ||
503 | +pad=1 | ||
504 | +activation=leaky | ||
505 | + | ||
506 | +[shortcut] | ||
507 | +from=-3 | ||
508 | +activation=linear | ||
509 | + | ||
510 | +[convolutional] | ||
511 | +batch_normalize=1 | ||
512 | +filters=512 | ||
513 | +size=1 | ||
514 | +stride=1 | ||
515 | +pad=1 | ||
516 | +activation=leaky | ||
517 | + | ||
518 | +[convolutional] | ||
519 | +batch_normalize=1 | ||
520 | +filters=1024 | ||
521 | +size=3 | ||
522 | +stride=1 | ||
523 | +pad=1 | ||
524 | +activation=leaky | ||
525 | + | ||
526 | +[shortcut] | ||
527 | +from=-3 | ||
528 | +activation=linear | ||
529 | + | ||
530 | +[convolutional] | ||
531 | +batch_normalize=1 | ||
532 | +filters=512 | ||
533 | +size=1 | ||
534 | +stride=1 | ||
535 | +pad=1 | ||
536 | +activation=leaky | ||
537 | + | ||
538 | +[convolutional] | ||
539 | +batch_normalize=1 | ||
540 | +filters=1024 | ||
541 | +size=3 | ||
542 | +stride=1 | ||
543 | +pad=1 | ||
544 | +activation=leaky | ||
545 | + | ||
546 | +[shortcut] | ||
547 | +from=-3 | ||
548 | +activation=linear | ||
549 | + | ||
550 | +###################### | ||
551 | + | ||
552 | +[convolutional] | ||
553 | +batch_normalize=1 | ||
554 | +filters=512 | ||
555 | +size=1 | ||
556 | +stride=1 | ||
557 | +pad=1 | ||
558 | +activation=leaky | ||
559 | + | ||
560 | +[convolutional] | ||
561 | +batch_normalize=1 | ||
562 | +size=3 | ||
563 | +stride=1 | ||
564 | +pad=1 | ||
565 | +filters=1024 | ||
566 | +activation=leaky | ||
567 | + | ||
568 | +[convolutional] | ||
569 | +batch_normalize=1 | ||
570 | +filters=512 | ||
571 | +size=1 | ||
572 | +stride=1 | ||
573 | +pad=1 | ||
574 | +activation=leaky | ||
575 | + | ||
576 | +[convolutional] | ||
577 | +batch_normalize=1 | ||
578 | +size=3 | ||
579 | +stride=1 | ||
580 | +pad=1 | ||
581 | +filters=1024 | ||
582 | +activation=leaky | ||
583 | + | ||
584 | +[convolutional] | ||
585 | +batch_normalize=1 | ||
586 | +filters=512 | ||
587 | +size=1 | ||
588 | +stride=1 | ||
589 | +pad=1 | ||
590 | +activation=leaky | ||
591 | + | ||
592 | +[convolutional] | ||
593 | +batch_normalize=1 | ||
594 | +size=3 | ||
595 | +stride=1 | ||
596 | +pad=1 | ||
597 | +filters=1024 | ||
598 | +activation=leaky | ||
599 | + | ||
600 | +[convolutional] | ||
601 | +size=1 | ||
602 | +stride=1 | ||
603 | +pad=1 | ||
604 | +filters=57 | ||
605 | +activation=linear | ||
606 | + | ||
607 | + | ||
608 | +[Gaussian_yolo] | ||
609 | +mask = 6,7,8 | ||
610 | +anchors = 7,10, 14,24, 27,43, 32,97, 57,64, 92,109, 73,175, 141,178, 144,291 | ||
611 | +classes=10 | ||
612 | +num=9 | ||
613 | +jitter=.3 | ||
614 | +ignore_thresh = .5 | ||
615 | +truth_thresh = 1 | ||
616 | +iou_thresh=0.213 | ||
617 | +uc_normalizer=1.0 | ||
618 | +cls_normalizer=1.0 | ||
619 | +iou_normalizer=0.5 | ||
620 | +iou_loss=giou | ||
621 | +scale_x_y=1.0 | ||
622 | +random=1 | ||
623 | + | ||
624 | + | ||
625 | +[route] | ||
626 | +layers = -4 | ||
627 | + | ||
628 | +[convolutional] | ||
629 | +batch_normalize=1 | ||
630 | +filters=256 | ||
631 | +size=1 | ||
632 | +stride=1 | ||
633 | +pad=1 | ||
634 | +activation=leaky | ||
635 | + | ||
636 | +[upsample] | ||
637 | +stride=2 | ||
638 | + | ||
639 | +[route] | ||
640 | +layers = -1, 61 | ||
641 | + | ||
642 | + | ||
643 | + | ||
644 | +[convolutional] | ||
645 | +batch_normalize=1 | ||
646 | +filters=256 | ||
647 | +size=1 | ||
648 | +stride=1 | ||
649 | +pad=1 | ||
650 | +activation=leaky | ||
651 | + | ||
652 | +[convolutional] | ||
653 | +batch_normalize=1 | ||
654 | +size=3 | ||
655 | +stride=1 | ||
656 | +pad=1 | ||
657 | +filters=512 | ||
658 | +activation=leaky | ||
659 | + | ||
660 | +[convolutional] | ||
661 | +batch_normalize=1 | ||
662 | +filters=256 | ||
663 | +size=1 | ||
664 | +stride=1 | ||
665 | +pad=1 | ||
666 | +activation=leaky | ||
667 | + | ||
668 | +[convolutional] | ||
669 | +batch_normalize=1 | ||
670 | +size=3 | ||
671 | +stride=1 | ||
672 | +pad=1 | ||
673 | +filters=512 | ||
674 | +activation=leaky | ||
675 | + | ||
676 | +[convolutional] | ||
677 | +batch_normalize=1 | ||
678 | +filters=256 | ||
679 | +size=1 | ||
680 | +stride=1 | ||
681 | +pad=1 | ||
682 | +activation=leaky | ||
683 | + | ||
684 | +[convolutional] | ||
685 | +batch_normalize=1 | ||
686 | +size=3 | ||
687 | +stride=1 | ||
688 | +pad=1 | ||
689 | +filters=512 | ||
690 | +activation=leaky | ||
691 | + | ||
692 | +[convolutional] | ||
693 | +size=1 | ||
694 | +stride=1 | ||
695 | +pad=1 | ||
696 | +filters=57 | ||
697 | +activation=linear | ||
698 | + | ||
699 | + | ||
700 | +[Gaussian_yolo] | ||
701 | +mask = 3,4,5 | ||
702 | +anchors = 7,10, 14,24, 27,43, 32,97, 57,64, 92,109, 73,175, 141,178, 144,291 | ||
703 | +classes=10 | ||
704 | +num=9 | ||
705 | +jitter=.3 | ||
706 | +ignore_thresh = .5 | ||
707 | +truth_thresh = 1 | ||
708 | +iou_thresh=0.213 | ||
709 | +uc_normalizer=1.0 | ||
710 | +cls_normalizer=1.0 | ||
711 | +iou_normalizer=0.5 | ||
712 | +iou_loss=giou | ||
713 | +scale_x_y=1.0 | ||
714 | +random=1 | ||
715 | + | ||
716 | + | ||
717 | + | ||
718 | +[route] | ||
719 | +layers = -4 | ||
720 | + | ||
721 | +[convolutional] | ||
722 | +batch_normalize=1 | ||
723 | +filters=128 | ||
724 | +size=1 | ||
725 | +stride=1 | ||
726 | +pad=1 | ||
727 | +activation=leaky | ||
728 | + | ||
729 | +[upsample] | ||
730 | +stride=2 | ||
731 | + | ||
732 | +[route] | ||
733 | +layers = -1, 36 | ||
734 | + | ||
735 | + | ||
736 | + | ||
737 | +[convolutional] | ||
738 | +batch_normalize=1 | ||
739 | +filters=128 | ||
740 | +size=1 | ||
741 | +stride=1 | ||
742 | +pad=1 | ||
743 | +activation=leaky | ||
744 | + | ||
745 | +[convolutional] | ||
746 | +batch_normalize=1 | ||
747 | +size=3 | ||
748 | +stride=1 | ||
749 | +pad=1 | ||
750 | +filters=256 | ||
751 | +activation=leaky | ||
752 | + | ||
753 | +[convolutional] | ||
754 | +batch_normalize=1 | ||
755 | +filters=128 | ||
756 | +size=1 | ||
757 | +stride=1 | ||
758 | +pad=1 | ||
759 | +activation=leaky | ||
760 | + | ||
761 | +[convolutional] | ||
762 | +batch_normalize=1 | ||
763 | +size=3 | ||
764 | +stride=1 | ||
765 | +pad=1 | ||
766 | +filters=256 | ||
767 | +activation=leaky | ||
768 | + | ||
769 | +[convolutional] | ||
770 | +batch_normalize=1 | ||
771 | +filters=128 | ||
772 | +size=1 | ||
773 | +stride=1 | ||
774 | +pad=1 | ||
775 | +activation=leaky | ||
776 | + | ||
777 | +[convolutional] | ||
778 | +batch_normalize=1 | ||
779 | +size=3 | ||
780 | +stride=1 | ||
781 | +pad=1 | ||
782 | +filters=256 | ||
783 | +activation=leaky | ||
784 | + | ||
785 | +[convolutional] | ||
786 | +size=1 | ||
787 | +stride=1 | ||
788 | +pad=1 | ||
789 | +filters=57 | ||
790 | +activation=linear | ||
791 | + | ||
792 | + | ||
793 | +[Gaussian_yolo] | ||
794 | +mask = 0,1,2 | ||
795 | +anchors = 7,10, 14,24, 27,43, 32,97, 57,64, 92,109, 73,175, 141,178, 144,291 | ||
796 | +classes=10 | ||
797 | +num=9 | ||
798 | +jitter=.3 | ||
799 | +ignore_thresh = .5 | ||
800 | +truth_thresh = 1 | ||
801 | +iou_thresh=0.213 | ||
802 | +uc_normalizer=1.0 | ||
803 | +cls_normalizer=1.0 | ||
804 | +iou_normalizer=0.5 | ||
805 | +iou_loss=giou | ||
806 | +scale_x_y=1.0 | ||
807 | +random=1 |
1 | +[net] | ||
2 | +batch=128 | ||
3 | +subdivisions=1 | ||
4 | +height=227 | ||
5 | +width=227 | ||
6 | +channels=3 | ||
7 | +momentum=0.9 | ||
8 | +decay=0.0005 | ||
9 | +max_crop=256 | ||
10 | + | ||
11 | +learning_rate=0.01 | ||
12 | +policy=poly | ||
13 | +power=4 | ||
14 | +max_batches=800000 | ||
15 | + | ||
16 | +angle=7 | ||
17 | +hue = .1 | ||
18 | +saturation=.75 | ||
19 | +exposure=.75 | ||
20 | +aspect=.75 | ||
21 | + | ||
22 | +[convolutional] | ||
23 | +filters=96 | ||
24 | +size=11 | ||
25 | +stride=4 | ||
26 | +pad=0 | ||
27 | +activation=relu | ||
28 | + | ||
29 | +[maxpool] | ||
30 | +size=3 | ||
31 | +stride=2 | ||
32 | +padding=0 | ||
33 | + | ||
34 | +[convolutional] | ||
35 | +filters=256 | ||
36 | +size=5 | ||
37 | +stride=1 | ||
38 | +pad=1 | ||
39 | +activation=relu | ||
40 | + | ||
41 | +[maxpool] | ||
42 | +size=3 | ||
43 | +stride=2 | ||
44 | +padding=0 | ||
45 | + | ||
46 | +[convolutional] | ||
47 | +filters=384 | ||
48 | +size=3 | ||
49 | +stride=1 | ||
50 | +pad=1 | ||
51 | +activation=relu | ||
52 | + | ||
53 | +[convolutional] | ||
54 | +filters=384 | ||
55 | +size=3 | ||
56 | +stride=1 | ||
57 | +pad=1 | ||
58 | +activation=relu | ||
59 | + | ||
60 | +[convolutional] | ||
61 | +filters=256 | ||
62 | +size=3 | ||
63 | +stride=1 | ||
64 | +pad=1 | ||
65 | +activation=relu | ||
66 | + | ||
67 | +[maxpool] | ||
68 | +size=3 | ||
69 | +stride=2 | ||
70 | +padding=0 | ||
71 | + | ||
72 | +[connected] | ||
73 | +output=4096 | ||
74 | +activation=relu | ||
75 | + | ||
76 | +[dropout] | ||
77 | +probability=.5 | ||
78 | + | ||
79 | +[connected] | ||
80 | +output=4096 | ||
81 | +activation=relu | ||
82 | + | ||
83 | +[dropout] | ||
84 | +probability=.5 | ||
85 | + | ||
86 | +[connected] | ||
87 | +output=1000 | ||
88 | +activation=linear | ||
89 | + | ||
90 | +[softmax] | ||
91 | +groups=1 | ||
92 | + | ||
93 | +[cost] | ||
94 | +type=sse | ||
95 | + |
1 | +[net] | ||
2 | +batch=128 | ||
3 | +subdivisions=1 | ||
4 | +height=32 | ||
5 | +width=32 | ||
6 | +channels=3 | ||
7 | +momentum=0.9 | ||
8 | +decay=0.0005 | ||
9 | + | ||
10 | +learning_rate=0.4 | ||
11 | +policy=poly | ||
12 | +power=4 | ||
13 | +max_batches = 50000 | ||
14 | + | ||
15 | +[crop] | ||
16 | +crop_width=28 | ||
17 | +crop_height=28 | ||
18 | +flip=1 | ||
19 | +angle=0 | ||
20 | +saturation = 1 | ||
21 | +exposure = 1 | ||
22 | +noadjust=1 | ||
23 | + | ||
24 | +[convolutional] | ||
25 | +batch_normalize=1 | ||
26 | +filters=128 | ||
27 | +size=3 | ||
28 | +stride=1 | ||
29 | +pad=1 | ||
30 | +activation=leaky | ||
31 | + | ||
32 | +[convolutional] | ||
33 | +batch_normalize=1 | ||
34 | +filters=128 | ||
35 | +size=3 | ||
36 | +stride=1 | ||
37 | +pad=1 | ||
38 | +activation=leaky | ||
39 | + | ||
40 | +[convolutional] | ||
41 | +batch_normalize=1 | ||
42 | +filters=128 | ||
43 | +size=3 | ||
44 | +stride=1 | ||
45 | +pad=1 | ||
46 | +activation=leaky | ||
47 | + | ||
48 | +[maxpool] | ||
49 | +size=2 | ||
50 | +stride=2 | ||
51 | + | ||
52 | +[dropout] | ||
53 | +probability=.5 | ||
54 | + | ||
55 | +[convolutional] | ||
56 | +batch_normalize=1 | ||
57 | +filters=256 | ||
58 | +size=3 | ||
59 | +stride=1 | ||
60 | +pad=1 | ||
61 | +activation=leaky | ||
62 | + | ||
63 | +[convolutional] | ||
64 | +batch_normalize=1 | ||
65 | +filters=256 | ||
66 | +size=3 | ||
67 | +stride=1 | ||
68 | +pad=1 | ||
69 | +activation=leaky | ||
70 | + | ||
71 | +[convolutional] | ||
72 | +batch_normalize=1 | ||
73 | +filters=256 | ||
74 | +size=3 | ||
75 | +stride=1 | ||
76 | +pad=1 | ||
77 | +activation=leaky | ||
78 | + | ||
79 | +[maxpool] | ||
80 | +size=2 | ||
81 | +stride=2 | ||
82 | + | ||
83 | +[dropout] | ||
84 | +probability=.5 | ||
85 | + | ||
86 | +[convolutional] | ||
87 | +batch_normalize=1 | ||
88 | +filters=512 | ||
89 | +size=3 | ||
90 | +stride=1 | ||
91 | +pad=1 | ||
92 | +activation=leaky | ||
93 | + | ||
94 | +[convolutional] | ||
95 | +batch_normalize=1 | ||
96 | +filters=512 | ||
97 | +size=3 | ||
98 | +stride=1 | ||
99 | +pad=1 | ||
100 | +activation=leaky | ||
101 | + | ||
102 | +[convolutional] | ||
103 | +batch_normalize=1 | ||
104 | +filters=512 | ||
105 | +size=3 | ||
106 | +stride=1 | ||
107 | +pad=1 | ||
108 | +activation=leaky | ||
109 | + | ||
110 | +[dropout] | ||
111 | +probability=.5 | ||
112 | + | ||
113 | +[convolutional] | ||
114 | +filters=10 | ||
115 | +size=1 | ||
116 | +stride=1 | ||
117 | +pad=1 | ||
118 | +activation=leaky | ||
119 | + | ||
120 | +[avgpool] | ||
121 | + | ||
122 | +[softmax] | ||
123 | +groups=1 | ||
124 | + | ||
125 | +[cost] | ||
126 | + |
1 | +[net] | ||
2 | +batch=128 | ||
3 | +subdivisions=1 | ||
4 | +height=32 | ||
5 | +width=32 | ||
6 | +channels=3 | ||
7 | +momentum=0.9 | ||
8 | +decay=0.0005 | ||
9 | + | ||
10 | +learning_rate=0.4 | ||
11 | +policy=poly | ||
12 | +power=4 | ||
13 | +max_batches = 50000 | ||
14 | + | ||
15 | + | ||
16 | +[convolutional] | ||
17 | +batch_normalize=1 | ||
18 | +filters=128 | ||
19 | +size=3 | ||
20 | +stride=1 | ||
21 | +pad=1 | ||
22 | +activation=leaky | ||
23 | + | ||
24 | +[convolutional] | ||
25 | +batch_normalize=1 | ||
26 | +filters=128 | ||
27 | +size=3 | ||
28 | +stride=1 | ||
29 | +pad=1 | ||
30 | +activation=leaky | ||
31 | + | ||
32 | +[convolutional] | ||
33 | +batch_normalize=1 | ||
34 | +filters=128 | ||
35 | +size=3 | ||
36 | +stride=1 | ||
37 | +pad=1 | ||
38 | +activation=leaky | ||
39 | + | ||
40 | +[maxpool] | ||
41 | +size=2 | ||
42 | +stride=2 | ||
43 | + | ||
44 | +[dropout] | ||
45 | +probability=.5 | ||
46 | + | ||
47 | +[convolutional] | ||
48 | +batch_normalize=1 | ||
49 | +filters=256 | ||
50 | +size=3 | ||
51 | +stride=1 | ||
52 | +pad=1 | ||
53 | +activation=leaky | ||
54 | + | ||
55 | +[convolutional] | ||
56 | +batch_normalize=1 | ||
57 | +filters=256 | ||
58 | +size=3 | ||
59 | +stride=1 | ||
60 | +pad=1 | ||
61 | +activation=leaky | ||
62 | + | ||
63 | +[convolutional] | ||
64 | +batch_normalize=1 | ||
65 | +filters=256 | ||
66 | +size=3 | ||
67 | +stride=1 | ||
68 | +pad=1 | ||
69 | +activation=leaky | ||
70 | + | ||
71 | +[maxpool] | ||
72 | +size=2 | ||
73 | +stride=2 | ||
74 | + | ||
75 | +[dropout] | ||
76 | +probability=.5 | ||
77 | + | ||
78 | +[convolutional] | ||
79 | +batch_normalize=1 | ||
80 | +filters=512 | ||
81 | +size=3 | ||
82 | +stride=1 | ||
83 | +pad=1 | ||
84 | +activation=leaky | ||
85 | + | ||
86 | +[convolutional] | ||
87 | +batch_normalize=1 | ||
88 | +filters=512 | ||
89 | +size=3 | ||
90 | +stride=1 | ||
91 | +pad=1 | ||
92 | +activation=leaky | ||
93 | + | ||
94 | +[convolutional] | ||
95 | +batch_normalize=1 | ||
96 | +filters=512 | ||
97 | +size=3 | ||
98 | +stride=1 | ||
99 | +pad=1 | ||
100 | +activation=leaky | ||
101 | + | ||
102 | +[dropout] | ||
103 | +probability=.5 | ||
104 | + | ||
105 | +[convolutional] | ||
106 | +filters=10 | ||
107 | +size=1 | ||
108 | +stride=1 | ||
109 | +pad=1 | ||
110 | +activation=leaky | ||
111 | + | ||
112 | +[avgpool] | ||
113 | + | ||
114 | +[softmax] | ||
115 | +groups=1 | ||
116 | +temperature=3 | ||
117 | + | ||
118 | +[cost] | ||
119 | + |
1 | +[net] | ||
2 | +subdivisions=8 | ||
3 | +inputs=256 | ||
4 | +batch = 128 | ||
5 | +momentum=0.9 | ||
6 | +decay=0.001 | ||
7 | +max_batches = 2000 | ||
8 | +time_steps=576 | ||
9 | +learning_rate=0.1 | ||
10 | +policy=steps | ||
11 | +steps=1000,1500 | ||
12 | +scales=.1,.1 | ||
13 | + | ||
14 | +try_fix_nan=1 | ||
15 | + | ||
16 | +[connected] | ||
17 | +output=256 | ||
18 | +activation=leaky | ||
19 | + | ||
20 | +[crnn] | ||
21 | +batch_normalize=1 | ||
22 | +size=1 | ||
23 | +pad=0 | ||
24 | +output = 1024 | ||
25 | +hidden=1024 | ||
26 | +activation=leaky | ||
27 | + | ||
28 | +[crnn] | ||
29 | +batch_normalize=1 | ||
30 | +size=1 | ||
31 | +pad=0 | ||
32 | +output = 1024 | ||
33 | +hidden=1024 | ||
34 | +activation=leaky | ||
35 | + | ||
36 | +[crnn] | ||
37 | +batch_normalize=1 | ||
38 | +size=1 | ||
39 | +pad=0 | ||
40 | +output = 1024 | ||
41 | +hidden=1024 | ||
42 | +activation=leaky | ||
43 | + | ||
44 | +[connected] | ||
45 | +output=256 | ||
46 | +activation=leaky | ||
47 | + | ||
48 | +[softmax] | ||
49 | + | ||
50 | +[cost] | ||
51 | +type=sse | ||
52 | + |
1 | +[net] | ||
2 | +# Training | ||
3 | +batch=128 | ||
4 | +subdivisions=4 | ||
5 | + | ||
6 | +label_smooth_eps=0.1 | ||
7 | + | ||
8 | +# Testing | ||
9 | +# batch=1 | ||
10 | +# subdivisions=1 | ||
11 | + | ||
12 | +height=256 | ||
13 | +width=256 | ||
14 | +channels=3 | ||
15 | +min_crop=128 | ||
16 | +max_crop=448 | ||
17 | + | ||
18 | +mosaic=1 | ||
19 | +cutmix=1 | ||
20 | + | ||
21 | +burn_in=1000 | ||
22 | +learning_rate=0.1 | ||
23 | +policy=poly | ||
24 | +power=4 | ||
25 | +max_batches=1200000 | ||
26 | +momentum=0.9 | ||
27 | +decay=0.0005 | ||
28 | + | ||
29 | +angle=7 | ||
30 | +hue=.1 | ||
31 | +saturation=.75 | ||
32 | +exposure=.75 | ||
33 | +aspect=.75 | ||
34 | + | ||
35 | + | ||
36 | + | ||
37 | +[convolutional] | ||
38 | +batch_normalize=1 | ||
39 | +filters=32 | ||
40 | +size=3 | ||
41 | +stride=1 | ||
42 | +pad=1 | ||
43 | +activation=mish | ||
44 | + | ||
45 | +# Downsample | ||
46 | + | ||
47 | +[convolutional] | ||
48 | +batch_normalize=1 | ||
49 | +filters=64 | ||
50 | +size=3 | ||
51 | +stride=2 | ||
52 | +pad=1 | ||
53 | +activation=mish | ||
54 | + | ||
55 | +[convolutional] | ||
56 | +batch_normalize=1 | ||
57 | +filters=64 | ||
58 | +size=1 | ||
59 | +stride=1 | ||
60 | +pad=1 | ||
61 | +activation=mish | ||
62 | + | ||
63 | +[route] | ||
64 | +layers = -2 | ||
65 | + | ||
66 | +[convolutional] | ||
67 | +batch_normalize=1 | ||
68 | +filters=64 | ||
69 | +size=1 | ||
70 | +stride=1 | ||
71 | +pad=1 | ||
72 | +activation=mish | ||
73 | + | ||
74 | +[convolutional] | ||
75 | +batch_normalize=1 | ||
76 | +filters=32 | ||
77 | +size=1 | ||
78 | +stride=1 | ||
79 | +pad=1 | ||
80 | +activation=mish | ||
81 | + | ||
82 | +[convolutional] | ||
83 | +batch_normalize=1 | ||
84 | +filters=64 | ||
85 | +size=3 | ||
86 | +stride=1 | ||
87 | +pad=1 | ||
88 | +activation=mish | ||
89 | + | ||
90 | +[shortcut] | ||
91 | +from=-3 | ||
92 | +activation=linear | ||
93 | + | ||
94 | +[convolutional] | ||
95 | +batch_normalize=1 | ||
96 | +filters=64 | ||
97 | +size=1 | ||
98 | +stride=1 | ||
99 | +pad=1 | ||
100 | +activation=mish | ||
101 | + | ||
102 | +[route] | ||
103 | +layers = -1,-7 | ||
104 | + | ||
105 | +[convolutional] | ||
106 | +batch_normalize=1 | ||
107 | +filters=64 | ||
108 | +size=1 | ||
109 | +stride=1 | ||
110 | +pad=1 | ||
111 | +activation=mish | ||
112 | + | ||
113 | +# Downsample | ||
114 | + | ||
115 | +[convolutional] | ||
116 | +batch_normalize=1 | ||
117 | +filters=128 | ||
118 | +size=3 | ||
119 | +stride=2 | ||
120 | +pad=1 | ||
121 | +activation=mish | ||
122 | + | ||
123 | +[convolutional] | ||
124 | +batch_normalize=1 | ||
125 | +filters=64 | ||
126 | +size=1 | ||
127 | +stride=1 | ||
128 | +pad=1 | ||
129 | +activation=mish | ||
130 | + | ||
131 | +[route] | ||
132 | +layers = -2 | ||
133 | + | ||
134 | +[convolutional] | ||
135 | +batch_normalize=1 | ||
136 | +filters=64 | ||
137 | +size=1 | ||
138 | +stride=1 | ||
139 | +pad=1 | ||
140 | +activation=mish | ||
141 | + | ||
142 | +[convolutional] | ||
143 | +batch_normalize=1 | ||
144 | +filters=64 | ||
145 | +size=1 | ||
146 | +stride=1 | ||
147 | +pad=1 | ||
148 | +activation=mish | ||
149 | + | ||
150 | +[convolutional] | ||
151 | +batch_normalize=1 | ||
152 | +filters=64 | ||
153 | +size=3 | ||
154 | +stride=1 | ||
155 | +pad=1 | ||
156 | +activation=mish | ||
157 | + | ||
158 | +[shortcut] | ||
159 | +from=-3 | ||
160 | +activation=linear | ||
161 | + | ||
162 | +[convolutional] | ||
163 | +batch_normalize=1 | ||
164 | +filters=64 | ||
165 | +size=1 | ||
166 | +stride=1 | ||
167 | +pad=1 | ||
168 | +activation=mish | ||
169 | + | ||
170 | +[convolutional] | ||
171 | +batch_normalize=1 | ||
172 | +filters=64 | ||
173 | +size=3 | ||
174 | +stride=1 | ||
175 | +pad=1 | ||
176 | +activation=mish | ||
177 | + | ||
178 | +[shortcut] | ||
179 | +from=-3 | ||
180 | +activation=linear | ||
181 | + | ||
182 | +[convolutional] | ||
183 | +batch_normalize=1 | ||
184 | +filters=64 | ||
185 | +size=1 | ||
186 | +stride=1 | ||
187 | +pad=1 | ||
188 | +activation=mish | ||
189 | + | ||
190 | +[route] | ||
191 | +layers = -1,-10 | ||
192 | + | ||
193 | +[convolutional] | ||
194 | +batch_normalize=1 | ||
195 | +filters=128 | ||
196 | +size=1 | ||
197 | +stride=1 | ||
198 | +pad=1 | ||
199 | +activation=mish | ||
200 | + | ||
201 | +# Downsample | ||
202 | + | ||
203 | +[convolutional] | ||
204 | +batch_normalize=1 | ||
205 | +filters=256 | ||
206 | +size=3 | ||
207 | +stride=2 | ||
208 | +pad=1 | ||
209 | +activation=mish | ||
210 | + | ||
211 | +[convolutional] | ||
212 | +batch_normalize=1 | ||
213 | +filters=128 | ||
214 | +size=1 | ||
215 | +stride=1 | ||
216 | +pad=1 | ||
217 | +activation=mish | ||
218 | + | ||
219 | +[route] | ||
220 | +layers = -2 | ||
221 | + | ||
222 | +[convolutional] | ||
223 | +batch_normalize=1 | ||
224 | +filters=128 | ||
225 | +size=1 | ||
226 | +stride=1 | ||
227 | +pad=1 | ||
228 | +activation=mish | ||
229 | + | ||
230 | +[convolutional] | ||
231 | +batch_normalize=1 | ||
232 | +filters=128 | ||
233 | +size=1 | ||
234 | +stride=1 | ||
235 | +pad=1 | ||
236 | +activation=mish | ||
237 | + | ||
238 | +[convolutional] | ||
239 | +batch_normalize=1 | ||
240 | +filters=128 | ||
241 | +size=3 | ||
242 | +stride=1 | ||
243 | +pad=1 | ||
244 | +activation=mish | ||
245 | + | ||
246 | +[shortcut] | ||
247 | +from=-3 | ||
248 | +activation=linear | ||
249 | + | ||
250 | +[convolutional] | ||
251 | +batch_normalize=1 | ||
252 | +filters=128 | ||
253 | +size=1 | ||
254 | +stride=1 | ||
255 | +pad=1 | ||
256 | +activation=mish | ||
257 | + | ||
258 | +[convolutional] | ||
259 | +batch_normalize=1 | ||
260 | +filters=128 | ||
261 | +size=3 | ||
262 | +stride=1 | ||
263 | +pad=1 | ||
264 | +activation=mish | ||
265 | + | ||
266 | +[shortcut] | ||
267 | +from=-3 | ||
268 | +activation=linear | ||
269 | + | ||
270 | +[convolutional] | ||
271 | +batch_normalize=1 | ||
272 | +filters=128 | ||
273 | +size=1 | ||
274 | +stride=1 | ||
275 | +pad=1 | ||
276 | +activation=mish | ||
277 | + | ||
278 | +[convolutional] | ||
279 | +batch_normalize=1 | ||
280 | +filters=128 | ||
281 | +size=3 | ||
282 | +stride=1 | ||
283 | +pad=1 | ||
284 | +activation=mish | ||
285 | + | ||
286 | +[shortcut] | ||
287 | +from=-3 | ||
288 | +activation=linear | ||
289 | + | ||
290 | +[convolutional] | ||
291 | +batch_normalize=1 | ||
292 | +filters=128 | ||
293 | +size=1 | ||
294 | +stride=1 | ||
295 | +pad=1 | ||
296 | +activation=mish | ||
297 | + | ||
298 | +[convolutional] | ||
299 | +batch_normalize=1 | ||
300 | +filters=128 | ||
301 | +size=3 | ||
302 | +stride=1 | ||
303 | +pad=1 | ||
304 | +activation=mish | ||
305 | + | ||
306 | +[shortcut] | ||
307 | +from=-3 | ||
308 | +activation=linear | ||
309 | + | ||
310 | + | ||
311 | +[convolutional] | ||
312 | +batch_normalize=1 | ||
313 | +filters=128 | ||
314 | +size=1 | ||
315 | +stride=1 | ||
316 | +pad=1 | ||
317 | +activation=mish | ||
318 | + | ||
319 | +[convolutional] | ||
320 | +batch_normalize=1 | ||
321 | +filters=128 | ||
322 | +size=3 | ||
323 | +stride=1 | ||
324 | +pad=1 | ||
325 | +activation=mish | ||
326 | + | ||
327 | +[shortcut] | ||
328 | +from=-3 | ||
329 | +activation=linear | ||
330 | + | ||
331 | +[convolutional] | ||
332 | +batch_normalize=1 | ||
333 | +filters=128 | ||
334 | +size=1 | ||
335 | +stride=1 | ||
336 | +pad=1 | ||
337 | +activation=mish | ||
338 | + | ||
339 | +[convolutional] | ||
340 | +batch_normalize=1 | ||
341 | +filters=128 | ||
342 | +size=3 | ||
343 | +stride=1 | ||
344 | +pad=1 | ||
345 | +activation=mish | ||
346 | + | ||
347 | +[shortcut] | ||
348 | +from=-3 | ||
349 | +activation=linear | ||
350 | + | ||
351 | +[convolutional] | ||
352 | +batch_normalize=1 | ||
353 | +filters=128 | ||
354 | +size=1 | ||
355 | +stride=1 | ||
356 | +pad=1 | ||
357 | +activation=mish | ||
358 | + | ||
359 | +[convolutional] | ||
360 | +batch_normalize=1 | ||
361 | +filters=128 | ||
362 | +size=3 | ||
363 | +stride=1 | ||
364 | +pad=1 | ||
365 | +activation=mish | ||
366 | + | ||
367 | +[shortcut] | ||
368 | +from=-3 | ||
369 | +activation=linear | ||
370 | + | ||
371 | +[convolutional] | ||
372 | +batch_normalize=1 | ||
373 | +filters=128 | ||
374 | +size=1 | ||
375 | +stride=1 | ||
376 | +pad=1 | ||
377 | +activation=mish | ||
378 | + | ||
379 | +[convolutional] | ||
380 | +batch_normalize=1 | ||
381 | +filters=128 | ||
382 | +size=3 | ||
383 | +stride=1 | ||
384 | +pad=1 | ||
385 | +activation=mish | ||
386 | + | ||
387 | +[shortcut] | ||
388 | +from=-3 | ||
389 | +activation=linear | ||
390 | + | ||
391 | +[convolutional] | ||
392 | +batch_normalize=1 | ||
393 | +filters=128 | ||
394 | +size=1 | ||
395 | +stride=1 | ||
396 | +pad=1 | ||
397 | +activation=mish | ||
398 | + | ||
399 | +[route] | ||
400 | +layers = -1,-28 | ||
401 | + | ||
402 | +[convolutional] | ||
403 | +batch_normalize=1 | ||
404 | +filters=256 | ||
405 | +size=1 | ||
406 | +stride=1 | ||
407 | +pad=1 | ||
408 | +activation=mish | ||
409 | + | ||
410 | +# Downsample | ||
411 | + | ||
412 | +[convolutional] | ||
413 | +batch_normalize=1 | ||
414 | +filters=512 | ||
415 | +size=3 | ||
416 | +stride=2 | ||
417 | +pad=1 | ||
418 | +activation=mish | ||
419 | + | ||
420 | +[convolutional] | ||
421 | +batch_normalize=1 | ||
422 | +filters=256 | ||
423 | +size=1 | ||
424 | +stride=1 | ||
425 | +pad=1 | ||
426 | +activation=mish | ||
427 | + | ||
428 | +[route] | ||
429 | +layers = -2 | ||
430 | + | ||
431 | +[convolutional] | ||
432 | +batch_normalize=1 | ||
433 | +filters=256 | ||
434 | +size=1 | ||
435 | +stride=1 | ||
436 | +pad=1 | ||
437 | +activation=mish | ||
438 | + | ||
439 | +[convolutional] | ||
440 | +batch_normalize=1 | ||
441 | +filters=256 | ||
442 | +size=1 | ||
443 | +stride=1 | ||
444 | +pad=1 | ||
445 | +activation=mish | ||
446 | + | ||
447 | +[convolutional] | ||
448 | +batch_normalize=1 | ||
449 | +filters=256 | ||
450 | +size=3 | ||
451 | +stride=1 | ||
452 | +pad=1 | ||
453 | +activation=mish | ||
454 | + | ||
455 | +[shortcut] | ||
456 | +from=-3 | ||
457 | +activation=linear | ||
458 | + | ||
459 | + | ||
460 | +[convolutional] | ||
461 | +batch_normalize=1 | ||
462 | +filters=256 | ||
463 | +size=1 | ||
464 | +stride=1 | ||
465 | +pad=1 | ||
466 | +activation=mish | ||
467 | + | ||
468 | +[convolutional] | ||
469 | +batch_normalize=1 | ||
470 | +filters=256 | ||
471 | +size=3 | ||
472 | +stride=1 | ||
473 | +pad=1 | ||
474 | +activation=mish | ||
475 | + | ||
476 | +[shortcut] | ||
477 | +from=-3 | ||
478 | +activation=linear | ||
479 | + | ||
480 | + | ||
481 | +[convolutional] | ||
482 | +batch_normalize=1 | ||
483 | +filters=256 | ||
484 | +size=1 | ||
485 | +stride=1 | ||
486 | +pad=1 | ||
487 | +activation=mish | ||
488 | + | ||
489 | +[convolutional] | ||
490 | +batch_normalize=1 | ||
491 | +filters=256 | ||
492 | +size=3 | ||
493 | +stride=1 | ||
494 | +pad=1 | ||
495 | +activation=mish | ||
496 | + | ||
497 | +[shortcut] | ||
498 | +from=-3 | ||
499 | +activation=linear | ||
500 | + | ||
501 | + | ||
502 | +[convolutional] | ||
503 | +batch_normalize=1 | ||
504 | +filters=256 | ||
505 | +size=1 | ||
506 | +stride=1 | ||
507 | +pad=1 | ||
508 | +activation=mish | ||
509 | + | ||
510 | +[convolutional] | ||
511 | +batch_normalize=1 | ||
512 | +filters=256 | ||
513 | +size=3 | ||
514 | +stride=1 | ||
515 | +pad=1 | ||
516 | +activation=mish | ||
517 | + | ||
518 | +[shortcut] | ||
519 | +from=-3 | ||
520 | +activation=linear | ||
521 | + | ||
522 | + | ||
523 | +[convolutional] | ||
524 | +batch_normalize=1 | ||
525 | +filters=256 | ||
526 | +size=1 | ||
527 | +stride=1 | ||
528 | +pad=1 | ||
529 | +activation=mish | ||
530 | + | ||
531 | +[convolutional] | ||
532 | +batch_normalize=1 | ||
533 | +filters=256 | ||
534 | +size=3 | ||
535 | +stride=1 | ||
536 | +pad=1 | ||
537 | +activation=mish | ||
538 | + | ||
539 | +[shortcut] | ||
540 | +from=-3 | ||
541 | +activation=linear | ||
542 | + | ||
543 | + | ||
544 | +[convolutional] | ||
545 | +batch_normalize=1 | ||
546 | +filters=256 | ||
547 | +size=1 | ||
548 | +stride=1 | ||
549 | +pad=1 | ||
550 | +activation=mish | ||
551 | + | ||
552 | +[convolutional] | ||
553 | +batch_normalize=1 | ||
554 | +filters=256 | ||
555 | +size=3 | ||
556 | +stride=1 | ||
557 | +pad=1 | ||
558 | +activation=mish | ||
559 | + | ||
560 | +[shortcut] | ||
561 | +from=-3 | ||
562 | +activation=linear | ||
563 | + | ||
564 | + | ||
565 | +[convolutional] | ||
566 | +batch_normalize=1 | ||
567 | +filters=256 | ||
568 | +size=1 | ||
569 | +stride=1 | ||
570 | +pad=1 | ||
571 | +activation=mish | ||
572 | + | ||
573 | +[convolutional] | ||
574 | +batch_normalize=1 | ||
575 | +filters=256 | ||
576 | +size=3 | ||
577 | +stride=1 | ||
578 | +pad=1 | ||
579 | +activation=mish | ||
580 | + | ||
581 | +[shortcut] | ||
582 | +from=-3 | ||
583 | +activation=linear | ||
584 | + | ||
585 | +[convolutional] | ||
586 | +batch_normalize=1 | ||
587 | +filters=256 | ||
588 | +size=1 | ||
589 | +stride=1 | ||
590 | +pad=1 | ||
591 | +activation=mish | ||
592 | + | ||
593 | +[convolutional] | ||
594 | +batch_normalize=1 | ||
595 | +filters=256 | ||
596 | +size=3 | ||
597 | +stride=1 | ||
598 | +pad=1 | ||
599 | +activation=mish | ||
600 | + | ||
601 | +[shortcut] | ||
602 | +from=-3 | ||
603 | +activation=linear | ||
604 | + | ||
605 | +[convolutional] | ||
606 | +batch_normalize=1 | ||
607 | +filters=256 | ||
608 | +size=1 | ||
609 | +stride=1 | ||
610 | +pad=1 | ||
611 | +activation=mish | ||
612 | + | ||
613 | +[route] | ||
614 | +layers = -1,-28 | ||
615 | + | ||
616 | +[convolutional] | ||
617 | +batch_normalize=1 | ||
618 | +filters=512 | ||
619 | +size=1 | ||
620 | +stride=1 | ||
621 | +pad=1 | ||
622 | +activation=mish | ||
623 | + | ||
624 | +# Downsample | ||
625 | + | ||
626 | +[convolutional] | ||
627 | +batch_normalize=1 | ||
628 | +filters=1024 | ||
629 | +size=3 | ||
630 | +stride=2 | ||
631 | +pad=1 | ||
632 | +activation=mish | ||
633 | + | ||
634 | +[convolutional] | ||
635 | +batch_normalize=1 | ||
636 | +filters=512 | ||
637 | +size=1 | ||
638 | +stride=1 | ||
639 | +pad=1 | ||
640 | +activation=mish | ||
641 | + | ||
642 | +[route] | ||
643 | +layers = -2 | ||
644 | + | ||
645 | +[convolutional] | ||
646 | +batch_normalize=1 | ||
647 | +filters=512 | ||
648 | +size=1 | ||
649 | +stride=1 | ||
650 | +pad=1 | ||
651 | +activation=mish | ||
652 | + | ||
653 | +[convolutional] | ||
654 | +batch_normalize=1 | ||
655 | +filters=512 | ||
656 | +size=1 | ||
657 | +stride=1 | ||
658 | +pad=1 | ||
659 | +activation=mish | ||
660 | + | ||
661 | +[convolutional] | ||
662 | +batch_normalize=1 | ||
663 | +filters=512 | ||
664 | +size=3 | ||
665 | +stride=1 | ||
666 | +pad=1 | ||
667 | +activation=mish | ||
668 | + | ||
669 | +[shortcut] | ||
670 | +from=-3 | ||
671 | +activation=linear | ||
672 | + | ||
673 | +[convolutional] | ||
674 | +batch_normalize=1 | ||
675 | +filters=512 | ||
676 | +size=1 | ||
677 | +stride=1 | ||
678 | +pad=1 | ||
679 | +activation=mish | ||
680 | + | ||
681 | +[convolutional] | ||
682 | +batch_normalize=1 | ||
683 | +filters=512 | ||
684 | +size=3 | ||
685 | +stride=1 | ||
686 | +pad=1 | ||
687 | +activation=mish | ||
688 | + | ||
689 | +[shortcut] | ||
690 | +from=-3 | ||
691 | +activation=linear | ||
692 | + | ||
693 | +[convolutional] | ||
694 | +batch_normalize=1 | ||
695 | +filters=512 | ||
696 | +size=1 | ||
697 | +stride=1 | ||
698 | +pad=1 | ||
699 | +activation=mish | ||
700 | + | ||
701 | +[convolutional] | ||
702 | +batch_normalize=1 | ||
703 | +filters=512 | ||
704 | +size=3 | ||
705 | +stride=1 | ||
706 | +pad=1 | ||
707 | +activation=mish | ||
708 | + | ||
709 | +[shortcut] | ||
710 | +from=-3 | ||
711 | +activation=linear | ||
712 | + | ||
713 | +[convolutional] | ||
714 | +batch_normalize=1 | ||
715 | +filters=512 | ||
716 | +size=1 | ||
717 | +stride=1 | ||
718 | +pad=1 | ||
719 | +activation=mish | ||
720 | + | ||
721 | +[convolutional] | ||
722 | +batch_normalize=1 | ||
723 | +filters=512 | ||
724 | +size=3 | ||
725 | +stride=1 | ||
726 | +pad=1 | ||
727 | +activation=mish | ||
728 | + | ||
729 | +[shortcut] | ||
730 | +from=-3 | ||
731 | +activation=linear | ||
732 | + | ||
733 | +[convolutional] | ||
734 | +batch_normalize=1 | ||
735 | +filters=512 | ||
736 | +size=1 | ||
737 | +stride=1 | ||
738 | +pad=1 | ||
739 | +activation=mish | ||
740 | + | ||
741 | +[route] | ||
742 | +layers = -1,-16 | ||
743 | + | ||
744 | +[convolutional] | ||
745 | +batch_normalize=1 | ||
746 | +filters=1024 | ||
747 | +size=1 | ||
748 | +stride=1 | ||
749 | +pad=1 | ||
750 | +activation=mish | ||
751 | + | ||
752 | +[avgpool] | ||
753 | + | ||
754 | +[convolutional] | ||
755 | +filters=1000 | ||
756 | +size=1 | ||
757 | +stride=1 | ||
758 | +pad=1 | ||
759 | +activation=linear | ||
760 | + | ||
761 | +[softmax] | ||
762 | +groups=1 |
1 | +[net] | ||
2 | +batch=128 | ||
3 | +subdivisions=1 | ||
4 | +height=224 | ||
5 | +width=224 | ||
6 | +channels=3 | ||
7 | +momentum=0.9 | ||
8 | +decay=0.0005 | ||
9 | +max_crop=320 | ||
10 | + | ||
11 | +learning_rate=0.1 | ||
12 | +policy=poly | ||
13 | +power=4 | ||
14 | +max_batches=1600000 | ||
15 | + | ||
16 | +[convolutional] | ||
17 | +batch_normalize=1 | ||
18 | +filters=16 | ||
19 | +size=3 | ||
20 | +stride=1 | ||
21 | +pad=1 | ||
22 | +activation=leaky | ||
23 | + | ||
24 | +[maxpool] | ||
25 | +size=2 | ||
26 | +stride=2 | ||
27 | + | ||
28 | +[convolutional] | ||
29 | +batch_normalize=1 | ||
30 | +filters=32 | ||
31 | +size=3 | ||
32 | +stride=1 | ||
33 | +pad=1 | ||
34 | +activation=leaky | ||
35 | + | ||
36 | +[maxpool] | ||
37 | +size=2 | ||
38 | +stride=2 | ||
39 | + | ||
40 | +[convolutional] | ||
41 | +batch_normalize=1 | ||
42 | +filters=64 | ||
43 | +size=3 | ||
44 | +stride=1 | ||
45 | +pad=1 | ||
46 | +activation=leaky | ||
47 | + | ||
48 | +[maxpool] | ||
49 | +size=2 | ||
50 | +stride=2 | ||
51 | + | ||
52 | +[convolutional] | ||
53 | +batch_normalize=1 | ||
54 | +filters=128 | ||
55 | +size=3 | ||
56 | +stride=1 | ||
57 | +pad=1 | ||
58 | +activation=leaky | ||
59 | + | ||
60 | +[maxpool] | ||
61 | +size=2 | ||
62 | +stride=2 | ||
63 | + | ||
64 | +[convolutional] | ||
65 | +batch_normalize=1 | ||
66 | +filters=256 | ||
67 | +size=3 | ||
68 | +stride=1 | ||
69 | +pad=1 | ||
70 | +activation=leaky | ||
71 | + | ||
72 | +[maxpool] | ||
73 | +size=2 | ||
74 | +stride=2 | ||
75 | + | ||
76 | +[convolutional] | ||
77 | +batch_normalize=1 | ||
78 | +filters=512 | ||
79 | +size=3 | ||
80 | +stride=1 | ||
81 | +pad=1 | ||
82 | +activation=leaky | ||
83 | + | ||
84 | +[maxpool] | ||
85 | +size=2 | ||
86 | +stride=2 | ||
87 | +padding=1 | ||
88 | + | ||
89 | +[convolutional] | ||
90 | +batch_normalize=1 | ||
91 | +filters=1024 | ||
92 | +size=3 | ||
93 | +stride=1 | ||
94 | +pad=1 | ||
95 | +activation=leaky | ||
96 | + | ||
97 | +[convolutional] | ||
98 | +filters=1000 | ||
99 | +size=1 | ||
100 | +stride=1 | ||
101 | +pad=1 | ||
102 | +activation=leaky | ||
103 | + | ||
104 | +[avgpool] | ||
105 | + | ||
106 | +[softmax] | ||
107 | +groups=1 | ||
108 | + | ||
109 | +[cost] | ||
110 | +type=sse | ||
111 | + |
1 | +[net] | ||
2 | +batch=128 | ||
3 | +subdivisions=1 | ||
4 | +height=224 | ||
5 | +width=224 | ||
6 | +channels=3 | ||
7 | +momentum=0.9 | ||
8 | +decay=0.0005 | ||
9 | +max_crop=448 | ||
10 | + | ||
11 | +learning_rate=0.1 | ||
12 | +policy=poly | ||
13 | +power=4 | ||
14 | +max_batches=1600000 | ||
15 | + | ||
16 | +[convolutional] | ||
17 | +batch_normalize=1 | ||
18 | +filters=32 | ||
19 | +size=3 | ||
20 | +stride=1 | ||
21 | +pad=1 | ||
22 | +activation=leaky | ||
23 | + | ||
24 | +[maxpool] | ||
25 | +size=2 | ||
26 | +stride=2 | ||
27 | + | ||
28 | +[convolutional] | ||
29 | +batch_normalize=1 | ||
30 | +filters=64 | ||
31 | +size=3 | ||
32 | +stride=1 | ||
33 | +pad=1 | ||
34 | +activation=leaky | ||
35 | + | ||
36 | +[maxpool] | ||
37 | +size=2 | ||
38 | +stride=2 | ||
39 | + | ||
40 | +[convolutional] | ||
41 | +batch_normalize=1 | ||
42 | +filters=128 | ||
43 | +size=3 | ||
44 | +stride=1 | ||
45 | +pad=1 | ||
46 | +activation=leaky | ||
47 | + | ||
48 | +[convolutional] | ||
49 | +batch_normalize=1 | ||
50 | +filters=64 | ||
51 | +size=1 | ||
52 | +stride=1 | ||
53 | +pad=1 | ||
54 | +activation=leaky | ||
55 | + | ||
56 | +[convolutional] | ||
57 | +batch_normalize=1 | ||
58 | +filters=128 | ||
59 | +size=3 | ||
60 | +stride=1 | ||
61 | +pad=1 | ||
62 | +activation=leaky | ||
63 | + | ||
64 | +[maxpool] | ||
65 | +size=2 | ||
66 | +stride=2 | ||
67 | + | ||
68 | +[convolutional] | ||
69 | +batch_normalize=1 | ||
70 | +filters=256 | ||
71 | +size=3 | ||
72 | +stride=1 | ||
73 | +pad=1 | ||
74 | +activation=leaky | ||
75 | + | ||
76 | +[convolutional] | ||
77 | +batch_normalize=1 | ||
78 | +filters=128 | ||
79 | +size=1 | ||
80 | +stride=1 | ||
81 | +pad=1 | ||
82 | +activation=leaky | ||
83 | + | ||
84 | +[convolutional] | ||
85 | +batch_normalize=1 | ||
86 | +filters=256 | ||
87 | +size=3 | ||
88 | +stride=1 | ||
89 | +pad=1 | ||
90 | +activation=leaky | ||
91 | + | ||
92 | +[maxpool] | ||
93 | +size=2 | ||
94 | +stride=2 | ||
95 | + | ||
96 | +[convolutional] | ||
97 | +batch_normalize=1 | ||
98 | +filters=512 | ||
99 | +size=3 | ||
100 | +stride=1 | ||
101 | +pad=1 | ||
102 | +activation=leaky | ||
103 | + | ||
104 | +[convolutional] | ||
105 | +batch_normalize=1 | ||
106 | +filters=256 | ||
107 | +size=1 | ||
108 | +stride=1 | ||
109 | +pad=1 | ||
110 | +activation=leaky | ||
111 | + | ||
112 | +[convolutional] | ||
113 | +batch_normalize=1 | ||
114 | +filters=512 | ||
115 | +size=3 | ||
116 | +stride=1 | ||
117 | +pad=1 | ||
118 | +activation=leaky | ||
119 | + | ||
120 | +[convolutional] | ||
121 | +batch_normalize=1 | ||
122 | +filters=256 | ||
123 | +size=1 | ||
124 | +stride=1 | ||
125 | +pad=1 | ||
126 | +activation=leaky | ||
127 | + | ||
128 | +[convolutional] | ||
129 | +batch_normalize=1 | ||
130 | +filters=512 | ||
131 | +size=3 | ||
132 | +stride=1 | ||
133 | +pad=1 | ||
134 | +activation=leaky | ||
135 | + | ||
136 | +[maxpool] | ||
137 | +size=2 | ||
138 | +stride=2 | ||
139 | + | ||
140 | +[convolutional] | ||
141 | +batch_normalize=1 | ||
142 | +filters=1024 | ||
143 | +size=3 | ||
144 | +stride=1 | ||
145 | +pad=1 | ||
146 | +activation=leaky | ||
147 | + | ||
148 | +[convolutional] | ||
149 | +batch_normalize=1 | ||
150 | +filters=512 | ||
151 | +size=1 | ||
152 | +stride=1 | ||
153 | +pad=1 | ||
154 | +activation=leaky | ||
155 | + | ||
156 | +[convolutional] | ||
157 | +batch_normalize=1 | ||
158 | +filters=1024 | ||
159 | +size=3 | ||
160 | +stride=1 | ||
161 | +pad=1 | ||
162 | +activation=leaky | ||
163 | + | ||
164 | +[convolutional] | ||
165 | +batch_normalize=1 | ||
166 | +filters=512 | ||
167 | +size=1 | ||
168 | +stride=1 | ||
169 | +pad=1 | ||
170 | +activation=leaky | ||
171 | + | ||
172 | +[convolutional] | ||
173 | +batch_normalize=1 | ||
174 | +filters=1024 | ||
175 | +size=3 | ||
176 | +stride=1 | ||
177 | +pad=1 | ||
178 | +activation=leaky | ||
179 | + | ||
180 | +[convolutional] | ||
181 | +filters=1000 | ||
182 | +size=1 | ||
183 | +stride=1 | ||
184 | +pad=1 | ||
185 | +activation=linear | ||
186 | + | ||
187 | +[avgpool] | ||
188 | + | ||
189 | +[softmax] | ||
190 | +groups=1 | ||
191 | + | ||
192 | +[cost] | ||
193 | +type=sse | ||
194 | + |
1 | +[net] | ||
2 | +#batch=128 | ||
3 | +#subdivisions=4 | ||
4 | +batch=1 | ||
5 | +subdivisions=1 | ||
6 | +height=448 | ||
7 | +width=448 | ||
8 | +max_crop=512 | ||
9 | +channels=3 | ||
10 | +momentum=0.9 | ||
11 | +decay=0.0005 | ||
12 | + | ||
13 | +learning_rate=0.001 | ||
14 | +policy=poly | ||
15 | +power=4 | ||
16 | +max_batches=100000 | ||
17 | + | ||
18 | +angle=7 | ||
19 | +hue = .1 | ||
20 | +saturation=.75 | ||
21 | +exposure=.75 | ||
22 | +aspect=.75 | ||
23 | + | ||
24 | +[convolutional] | ||
25 | +batch_normalize=1 | ||
26 | +filters=32 | ||
27 | +size=3 | ||
28 | +stride=1 | ||
29 | +pad=1 | ||
30 | +activation=leaky | ||
31 | + | ||
32 | +[maxpool] | ||
33 | +size=2 | ||
34 | +stride=2 | ||
35 | + | ||
36 | +[convolutional] | ||
37 | +batch_normalize=1 | ||
38 | +filters=64 | ||
39 | +size=3 | ||
40 | +stride=1 | ||
41 | +pad=1 | ||
42 | +activation=leaky | ||
43 | + | ||
44 | +[maxpool] | ||
45 | +size=2 | ||
46 | +stride=2 | ||
47 | + | ||
48 | +[convolutional] | ||
49 | +batch_normalize=1 | ||
50 | +filters=128 | ||
51 | +size=3 | ||
52 | +stride=1 | ||
53 | +pad=1 | ||
54 | +activation=leaky | ||
55 | + | ||
56 | +[convolutional] | ||
57 | +batch_normalize=1 | ||
58 | +filters=64 | ||
59 | +size=1 | ||
60 | +stride=1 | ||
61 | +pad=1 | ||
62 | +activation=leaky | ||
63 | + | ||
64 | +[convolutional] | ||
65 | +batch_normalize=1 | ||
66 | +filters=128 | ||
67 | +size=3 | ||
68 | +stride=1 | ||
69 | +pad=1 | ||
70 | +activation=leaky | ||
71 | + | ||
72 | +[maxpool] | ||
73 | +size=2 | ||
74 | +stride=2 | ||
75 | + | ||
76 | +[convolutional] | ||
77 | +batch_normalize=1 | ||
78 | +filters=256 | ||
79 | +size=3 | ||
80 | +stride=1 | ||
81 | +pad=1 | ||
82 | +activation=leaky | ||
83 | + | ||
84 | +[convolutional] | ||
85 | +batch_normalize=1 | ||
86 | +filters=128 | ||
87 | +size=1 | ||
88 | +stride=1 | ||
89 | +pad=1 | ||
90 | +activation=leaky | ||
91 | + | ||
92 | +[convolutional] | ||
93 | +batch_normalize=1 | ||
94 | +filters=256 | ||
95 | +size=3 | ||
96 | +stride=1 | ||
97 | +pad=1 | ||
98 | +activation=leaky | ||
99 | + | ||
100 | +[maxpool] | ||
101 | +size=2 | ||
102 | +stride=2 | ||
103 | + | ||
104 | +[convolutional] | ||
105 | +batch_normalize=1 | ||
106 | +filters=512 | ||
107 | +size=3 | ||
108 | +stride=1 | ||
109 | +pad=1 | ||
110 | +activation=leaky | ||
111 | + | ||
112 | +[convolutional] | ||
113 | +batch_normalize=1 | ||
114 | +filters=256 | ||
115 | +size=1 | ||
116 | +stride=1 | ||
117 | +pad=1 | ||
118 | +activation=leaky | ||
119 | + | ||
120 | +[convolutional] | ||
121 | +batch_normalize=1 | ||
122 | +filters=512 | ||
123 | +size=3 | ||
124 | +stride=1 | ||
125 | +pad=1 | ||
126 | +activation=leaky | ||
127 | + | ||
128 | +[convolutional] | ||
129 | +batch_normalize=1 | ||
130 | +filters=256 | ||
131 | +size=1 | ||
132 | +stride=1 | ||
133 | +pad=1 | ||
134 | +activation=leaky | ||
135 | + | ||
136 | +[convolutional] | ||
137 | +batch_normalize=1 | ||
138 | +filters=512 | ||
139 | +size=3 | ||
140 | +stride=1 | ||
141 | +pad=1 | ||
142 | +activation=leaky | ||
143 | + | ||
144 | +[maxpool] | ||
145 | +size=2 | ||
146 | +stride=2 | ||
147 | + | ||
148 | +[convolutional] | ||
149 | +batch_normalize=1 | ||
150 | +filters=1024 | ||
151 | +size=3 | ||
152 | +stride=1 | ||
153 | +pad=1 | ||
154 | +activation=leaky | ||
155 | + | ||
156 | +[convolutional] | ||
157 | +batch_normalize=1 | ||
158 | +filters=512 | ||
159 | +size=1 | ||
160 | +stride=1 | ||
161 | +pad=1 | ||
162 | +activation=leaky | ||
163 | + | ||
164 | +[convolutional] | ||
165 | +batch_normalize=1 | ||
166 | +filters=1024 | ||
167 | +size=3 | ||
168 | +stride=1 | ||
169 | +pad=1 | ||
170 | +activation=leaky | ||
171 | + | ||
172 | +[convolutional] | ||
173 | +batch_normalize=1 | ||
174 | +filters=512 | ||
175 | +size=1 | ||
176 | +stride=1 | ||
177 | +pad=1 | ||
178 | +activation=leaky | ||
179 | + | ||
180 | +[convolutional] | ||
181 | +batch_normalize=1 | ||
182 | +filters=1024 | ||
183 | +size=3 | ||
184 | +stride=1 | ||
185 | +pad=1 | ||
186 | +activation=leaky | ||
187 | + | ||
188 | +[convolutional] | ||
189 | +filters=1000 | ||
190 | +size=1 | ||
191 | +stride=1 | ||
192 | +pad=1 | ||
193 | +activation=linear | ||
194 | + | ||
195 | +[avgpool] | ||
196 | + | ||
197 | +[softmax] | ||
198 | +groups=1 | ||
199 | + | ||
200 | +[cost] | ||
201 | +type=sse | ||
202 | + |
1 | +[net] | ||
2 | +# Training | ||
3 | +batch=128 | ||
4 | +subdivisions=8 | ||
5 | + | ||
6 | +# Testing | ||
7 | +#batch=1 | ||
8 | +#subdivisions=1 | ||
9 | + | ||
10 | +height=256 | ||
11 | +width=256 | ||
12 | +channels=3 | ||
13 | +min_crop=128 | ||
14 | +max_crop=448 | ||
15 | + | ||
16 | +burn_in=1000 | ||
17 | +learning_rate=0.1 | ||
18 | +policy=poly | ||
19 | +power=4 | ||
20 | +max_batches=800000 | ||
21 | +momentum=0.9 | ||
22 | +decay=0.0005 | ||
23 | + | ||
24 | +angle=7 | ||
25 | +hue=.1 | ||
26 | +saturation=.75 | ||
27 | +exposure=.75 | ||
28 | +aspect=.75 | ||
29 | + | ||
30 | + | ||
31 | +[convolutional] | ||
32 | +batch_normalize=1 | ||
33 | +filters=32 | ||
34 | +size=3 | ||
35 | +stride=1 | ||
36 | +pad=1 | ||
37 | +activation=leaky | ||
38 | + | ||
39 | +# Downsample | ||
40 | + | ||
41 | +[convolutional] | ||
42 | +batch_normalize=1 | ||
43 | +filters=64 | ||
44 | +size=3 | ||
45 | +stride=2 | ||
46 | +pad=1 | ||
47 | +activation=leaky | ||
48 | + | ||
49 | +[convolutional] | ||
50 | +batch_normalize=1 | ||
51 | +filters=32 | ||
52 | +size=1 | ||
53 | +stride=1 | ||
54 | +pad=1 | ||
55 | +activation=leaky | ||
56 | + | ||
57 | +[convolutional] | ||
58 | +batch_normalize=1 | ||
59 | +filters=64 | ||
60 | +size=3 | ||
61 | +stride=1 | ||
62 | +pad=1 | ||
63 | +activation=leaky | ||
64 | + | ||
65 | +[shortcut] | ||
66 | +from=-3 | ||
67 | +activation=linear | ||
68 | + | ||
69 | +# Downsample | ||
70 | + | ||
71 | +[convolutional] | ||
72 | +batch_normalize=1 | ||
73 | +filters=128 | ||
74 | +size=3 | ||
75 | +stride=2 | ||
76 | +pad=1 | ||
77 | +activation=leaky | ||
78 | + | ||
79 | +[convolutional] | ||
80 | +batch_normalize=1 | ||
81 | +filters=64 | ||
82 | +size=1 | ||
83 | +stride=1 | ||
84 | +pad=1 | ||
85 | +activation=leaky | ||
86 | + | ||
87 | +[convolutional] | ||
88 | +batch_normalize=1 | ||
89 | +filters=128 | ||
90 | +size=3 | ||
91 | +stride=1 | ||
92 | +pad=1 | ||
93 | +activation=leaky | ||
94 | + | ||
95 | +[shortcut] | ||
96 | +from=-3 | ||
97 | +activation=linear | ||
98 | + | ||
99 | +[convolutional] | ||
100 | +batch_normalize=1 | ||
101 | +filters=64 | ||
102 | +size=1 | ||
103 | +stride=1 | ||
104 | +pad=1 | ||
105 | +activation=leaky | ||
106 | + | ||
107 | +[convolutional] | ||
108 | +batch_normalize=1 | ||
109 | +filters=128 | ||
110 | +size=3 | ||
111 | +stride=1 | ||
112 | +pad=1 | ||
113 | +activation=leaky | ||
114 | + | ||
115 | +[shortcut] | ||
116 | +from=-3 | ||
117 | +activation=linear | ||
118 | + | ||
119 | +# Downsample | ||
120 | + | ||
121 | +[convolutional] | ||
122 | +batch_normalize=1 | ||
123 | +filters=256 | ||
124 | +size=3 | ||
125 | +stride=2 | ||
126 | +pad=1 | ||
127 | +activation=leaky | ||
128 | + | ||
129 | +[convolutional] | ||
130 | +batch_normalize=1 | ||
131 | +filters=128 | ||
132 | +size=1 | ||
133 | +stride=1 | ||
134 | +pad=1 | ||
135 | +activation=leaky | ||
136 | + | ||
137 | +[convolutional] | ||
138 | +batch_normalize=1 | ||
139 | +filters=256 | ||
140 | +size=3 | ||
141 | +stride=1 | ||
142 | +pad=1 | ||
143 | +activation=leaky | ||
144 | + | ||
145 | +[shortcut] | ||
146 | +from=-3 | ||
147 | +activation=linear | ||
148 | + | ||
149 | +[convolutional] | ||
150 | +batch_normalize=1 | ||
151 | +filters=128 | ||
152 | +size=1 | ||
153 | +stride=1 | ||
154 | +pad=1 | ||
155 | +activation=leaky | ||
156 | + | ||
157 | +[convolutional] | ||
158 | +batch_normalize=1 | ||
159 | +filters=256 | ||
160 | +size=3 | ||
161 | +stride=1 | ||
162 | +pad=1 | ||
163 | +activation=leaky | ||
164 | + | ||
165 | +[shortcut] | ||
166 | +from=-3 | ||
167 | +activation=linear | ||
168 | + | ||
169 | +[convolutional] | ||
170 | +batch_normalize=1 | ||
171 | +filters=128 | ||
172 | +size=1 | ||
173 | +stride=1 | ||
174 | +pad=1 | ||
175 | +activation=leaky | ||
176 | + | ||
177 | +[convolutional] | ||
178 | +batch_normalize=1 | ||
179 | +filters=256 | ||
180 | +size=3 | ||
181 | +stride=1 | ||
182 | +pad=1 | ||
183 | +activation=leaky | ||
184 | + | ||
185 | +[shortcut] | ||
186 | +from=-3 | ||
187 | +activation=linear | ||
188 | + | ||
189 | +[convolutional] | ||
190 | +batch_normalize=1 | ||
191 | +filters=128 | ||
192 | +size=1 | ||
193 | +stride=1 | ||
194 | +pad=1 | ||
195 | +activation=leaky | ||
196 | + | ||
197 | +[convolutional] | ||
198 | +batch_normalize=1 | ||
199 | +filters=256 | ||
200 | +size=3 | ||
201 | +stride=1 | ||
202 | +pad=1 | ||
203 | +activation=leaky | ||
204 | + | ||
205 | +[shortcut] | ||
206 | +from=-3 | ||
207 | +activation=linear | ||
208 | + | ||
209 | + | ||
210 | +[convolutional] | ||
211 | +batch_normalize=1 | ||
212 | +filters=128 | ||
213 | +size=1 | ||
214 | +stride=1 | ||
215 | +pad=1 | ||
216 | +activation=leaky | ||
217 | + | ||
218 | +[convolutional] | ||
219 | +batch_normalize=1 | ||
220 | +filters=256 | ||
221 | +size=3 | ||
222 | +stride=1 | ||
223 | +pad=1 | ||
224 | +activation=leaky | ||
225 | + | ||
226 | +[shortcut] | ||
227 | +from=-3 | ||
228 | +activation=linear | ||
229 | + | ||
230 | +[convolutional] | ||
231 | +batch_normalize=1 | ||
232 | +filters=128 | ||
233 | +size=1 | ||
234 | +stride=1 | ||
235 | +pad=1 | ||
236 | +activation=leaky | ||
237 | + | ||
238 | +[convolutional] | ||
239 | +batch_normalize=1 | ||
240 | +filters=256 | ||
241 | +size=3 | ||
242 | +stride=1 | ||
243 | +pad=1 | ||
244 | +activation=leaky | ||
245 | + | ||
246 | +[shortcut] | ||
247 | +from=-3 | ||
248 | +activation=linear | ||
249 | + | ||
250 | +[convolutional] | ||
251 | +batch_normalize=1 | ||
252 | +filters=128 | ||
253 | +size=1 | ||
254 | +stride=1 | ||
255 | +pad=1 | ||
256 | +activation=leaky | ||
257 | + | ||
258 | +[convolutional] | ||
259 | +batch_normalize=1 | ||
260 | +filters=256 | ||
261 | +size=3 | ||
262 | +stride=1 | ||
263 | +pad=1 | ||
264 | +activation=leaky | ||
265 | + | ||
266 | +[shortcut] | ||
267 | +from=-3 | ||
268 | +activation=linear | ||
269 | + | ||
270 | +[convolutional] | ||
271 | +batch_normalize=1 | ||
272 | +filters=128 | ||
273 | +size=1 | ||
274 | +stride=1 | ||
275 | +pad=1 | ||
276 | +activation=leaky | ||
277 | + | ||
278 | +[convolutional] | ||
279 | +batch_normalize=1 | ||
280 | +filters=256 | ||
281 | +size=3 | ||
282 | +stride=1 | ||
283 | +pad=1 | ||
284 | +activation=leaky | ||
285 | + | ||
286 | +[shortcut] | ||
287 | +from=-3 | ||
288 | +activation=linear | ||
289 | + | ||
290 | +# Downsample | ||
291 | + | ||
292 | +[convolutional] | ||
293 | +batch_normalize=1 | ||
294 | +filters=512 | ||
295 | +size=3 | ||
296 | +stride=2 | ||
297 | +pad=1 | ||
298 | +activation=leaky | ||
299 | + | ||
300 | +[convolutional] | ||
301 | +batch_normalize=1 | ||
302 | +filters=256 | ||
303 | +size=1 | ||
304 | +stride=1 | ||
305 | +pad=1 | ||
306 | +activation=leaky | ||
307 | + | ||
308 | +[convolutional] | ||
309 | +batch_normalize=1 | ||
310 | +filters=512 | ||
311 | +size=3 | ||
312 | +stride=1 | ||
313 | +pad=1 | ||
314 | +activation=leaky | ||
315 | + | ||
316 | +[shortcut] | ||
317 | +from=-3 | ||
318 | +activation=linear | ||
319 | + | ||
320 | + | ||
321 | +[convolutional] | ||
322 | +batch_normalize=1 | ||
323 | +filters=256 | ||
324 | +size=1 | ||
325 | +stride=1 | ||
326 | +pad=1 | ||
327 | +activation=leaky | ||
328 | + | ||
329 | +[convolutional] | ||
330 | +batch_normalize=1 | ||
331 | +filters=512 | ||
332 | +size=3 | ||
333 | +stride=1 | ||
334 | +pad=1 | ||
335 | +activation=leaky | ||
336 | + | ||
337 | +[shortcut] | ||
338 | +from=-3 | ||
339 | +activation=linear | ||
340 | + | ||
341 | + | ||
342 | +[convolutional] | ||
343 | +batch_normalize=1 | ||
344 | +filters=256 | ||
345 | +size=1 | ||
346 | +stride=1 | ||
347 | +pad=1 | ||
348 | +activation=leaky | ||
349 | + | ||
350 | +[convolutional] | ||
351 | +batch_normalize=1 | ||
352 | +filters=512 | ||
353 | +size=3 | ||
354 | +stride=1 | ||
355 | +pad=1 | ||
356 | +activation=leaky | ||
357 | + | ||
358 | +[shortcut] | ||
359 | +from=-3 | ||
360 | +activation=linear | ||
361 | + | ||
362 | + | ||
363 | +[convolutional] | ||
364 | +batch_normalize=1 | ||
365 | +filters=256 | ||
366 | +size=1 | ||
367 | +stride=1 | ||
368 | +pad=1 | ||
369 | +activation=leaky | ||
370 | + | ||
371 | +[convolutional] | ||
372 | +batch_normalize=1 | ||
373 | +filters=512 | ||
374 | +size=3 | ||
375 | +stride=1 | ||
376 | +pad=1 | ||
377 | +activation=leaky | ||
378 | + | ||
379 | +[shortcut] | ||
380 | +from=-3 | ||
381 | +activation=linear | ||
382 | + | ||
383 | +[convolutional] | ||
384 | +batch_normalize=1 | ||
385 | +filters=256 | ||
386 | +size=1 | ||
387 | +stride=1 | ||
388 | +pad=1 | ||
389 | +activation=leaky | ||
390 | + | ||
391 | +[convolutional] | ||
392 | +batch_normalize=1 | ||
393 | +filters=512 | ||
394 | +size=3 | ||
395 | +stride=1 | ||
396 | +pad=1 | ||
397 | +activation=leaky | ||
398 | + | ||
399 | +[shortcut] | ||
400 | +from=-3 | ||
401 | +activation=linear | ||
402 | + | ||
403 | + | ||
404 | +[convolutional] | ||
405 | +batch_normalize=1 | ||
406 | +filters=256 | ||
407 | +size=1 | ||
408 | +stride=1 | ||
409 | +pad=1 | ||
410 | +activation=leaky | ||
411 | + | ||
412 | +[convolutional] | ||
413 | +batch_normalize=1 | ||
414 | +filters=512 | ||
415 | +size=3 | ||
416 | +stride=1 | ||
417 | +pad=1 | ||
418 | +activation=leaky | ||
419 | + | ||
420 | +[shortcut] | ||
421 | +from=-3 | ||
422 | +activation=linear | ||
423 | + | ||
424 | + | ||
425 | +[convolutional] | ||
426 | +batch_normalize=1 | ||
427 | +filters=256 | ||
428 | +size=1 | ||
429 | +stride=1 | ||
430 | +pad=1 | ||
431 | +activation=leaky | ||
432 | + | ||
433 | +[convolutional] | ||
434 | +batch_normalize=1 | ||
435 | +filters=512 | ||
436 | +size=3 | ||
437 | +stride=1 | ||
438 | +pad=1 | ||
439 | +activation=leaky | ||
440 | + | ||
441 | +[shortcut] | ||
442 | +from=-3 | ||
443 | +activation=linear | ||
444 | + | ||
445 | +[convolutional] | ||
446 | +batch_normalize=1 | ||
447 | +filters=256 | ||
448 | +size=1 | ||
449 | +stride=1 | ||
450 | +pad=1 | ||
451 | +activation=leaky | ||
452 | + | ||
453 | +[convolutional] | ||
454 | +batch_normalize=1 | ||
455 | +filters=512 | ||
456 | +size=3 | ||
457 | +stride=1 | ||
458 | +pad=1 | ||
459 | +activation=leaky | ||
460 | + | ||
461 | +[shortcut] | ||
462 | +from=-3 | ||
463 | +activation=linear | ||
464 | + | ||
465 | +# Downsample | ||
466 | + | ||
467 | +[convolutional] | ||
468 | +batch_normalize=1 | ||
469 | +filters=1024 | ||
470 | +size=3 | ||
471 | +stride=2 | ||
472 | +pad=1 | ||
473 | +activation=leaky | ||
474 | + | ||
475 | +[convolutional] | ||
476 | +batch_normalize=1 | ||
477 | +filters=512 | ||
478 | +size=1 | ||
479 | +stride=1 | ||
480 | +pad=1 | ||
481 | +activation=leaky | ||
482 | + | ||
483 | +[convolutional] | ||
484 | +batch_normalize=1 | ||
485 | +filters=1024 | ||
486 | +size=3 | ||
487 | +stride=1 | ||
488 | +pad=1 | ||
489 | +activation=leaky | ||
490 | + | ||
491 | +[shortcut] | ||
492 | +from=-3 | ||
493 | +activation=linear | ||
494 | + | ||
495 | +[convolutional] | ||
496 | +batch_normalize=1 | ||
497 | +filters=512 | ||
498 | +size=1 | ||
499 | +stride=1 | ||
500 | +pad=1 | ||
501 | +activation=leaky | ||
502 | + | ||
503 | +[convolutional] | ||
504 | +batch_normalize=1 | ||
505 | +filters=1024 | ||
506 | +size=3 | ||
507 | +stride=1 | ||
508 | +pad=1 | ||
509 | +activation=leaky | ||
510 | + | ||
511 | +[shortcut] | ||
512 | +from=-3 | ||
513 | +activation=linear | ||
514 | + | ||
515 | +[convolutional] | ||
516 | +batch_normalize=1 | ||
517 | +filters=512 | ||
518 | +size=1 | ||
519 | +stride=1 | ||
520 | +pad=1 | ||
521 | +activation=leaky | ||
522 | + | ||
523 | +[convolutional] | ||
524 | +batch_normalize=1 | ||
525 | +filters=1024 | ||
526 | +size=3 | ||
527 | +stride=1 | ||
528 | +pad=1 | ||
529 | +activation=leaky | ||
530 | + | ||
531 | +[shortcut] | ||
532 | +from=-3 | ||
533 | +activation=linear | ||
534 | + | ||
535 | +[convolutional] | ||
536 | +batch_normalize=1 | ||
537 | +filters=512 | ||
538 | +size=1 | ||
539 | +stride=1 | ||
540 | +pad=1 | ||
541 | +activation=leaky | ||
542 | + | ||
543 | +[convolutional] | ||
544 | +batch_normalize=1 | ||
545 | +filters=1024 | ||
546 | +size=3 | ||
547 | +stride=1 | ||
548 | +pad=1 | ||
549 | +activation=leaky | ||
550 | + | ||
551 | +[shortcut] | ||
552 | +from=-3 | ||
553 | +activation=linear | ||
554 | + | ||
555 | +[avgpool] | ||
556 | + | ||
557 | +[convolutional] | ||
558 | +filters=1000 | ||
559 | +size=1 | ||
560 | +stride=1 | ||
561 | +pad=1 | ||
562 | +activation=linear | ||
563 | + | ||
564 | +[softmax] | ||
565 | +groups=1 | ||
566 | + |
1 | +[net] | ||
2 | +# Training - start training with darknet53.weights | ||
3 | +batch=120 | ||
4 | +subdivisions=20 | ||
5 | + | ||
6 | +# Testing | ||
7 | +#batch=1 | ||
8 | +#subdivisions=1 | ||
9 | + | ||
10 | +height=448 | ||
11 | +width=448 | ||
12 | +channels=3 | ||
13 | +min_crop=448 | ||
14 | +max_crop=512 | ||
15 | + | ||
16 | +burn_in=1000 | ||
17 | +learning_rate=0.1 | ||
18 | +policy=poly | ||
19 | +power=4 | ||
20 | +max_batches=100000 | ||
21 | +momentum=0.9 | ||
22 | +decay=0.0005 | ||
23 | + | ||
24 | + | ||
25 | +[convolutional] | ||
26 | +batch_normalize=1 | ||
27 | +filters=32 | ||
28 | +size=3 | ||
29 | +stride=1 | ||
30 | +pad=1 | ||
31 | +activation=leaky | ||
32 | + | ||
33 | +# Downsample | ||
34 | + | ||
35 | +[convolutional] | ||
36 | +xnor=1 | ||
37 | +batch_normalize=1 | ||
38 | +filters=64 | ||
39 | +size=3 | ||
40 | +stride=2 | ||
41 | +pad=1 | ||
42 | +activation=leaky | ||
43 | + | ||
44 | +[convolutional] | ||
45 | +xnor=1 | ||
46 | +batch_normalize=1 | ||
47 | +filters=32 | ||
48 | +size=1 | ||
49 | +stride=1 | ||
50 | +pad=1 | ||
51 | +activation=leaky | ||
52 | + | ||
53 | +[convolutional] | ||
54 | +xnor=1 | ||
55 | +batch_normalize=1 | ||
56 | +filters=64 | ||
57 | +size=3 | ||
58 | +stride=1 | ||
59 | +pad=1 | ||
60 | +activation=leaky | ||
61 | + | ||
62 | +[shortcut] | ||
63 | +from=-3 | ||
64 | +activation=linear | ||
65 | + | ||
66 | +# Downsample | ||
67 | + | ||
68 | +[convolutional] | ||
69 | +xnor=1 | ||
70 | +batch_normalize=1 | ||
71 | +filters=128 | ||
72 | +size=3 | ||
73 | +stride=2 | ||
74 | +pad=1 | ||
75 | +activation=leaky | ||
76 | + | ||
77 | +[convolutional] | ||
78 | +xnor=1 | ||
79 | +batch_normalize=1 | ||
80 | +filters=64 | ||
81 | +size=1 | ||
82 | +stride=1 | ||
83 | +pad=1 | ||
84 | +activation=leaky | ||
85 | + | ||
86 | +[convolutional] | ||
87 | +xnor=1 | ||
88 | +batch_normalize=1 | ||
89 | +filters=128 | ||
90 | +size=3 | ||
91 | +stride=1 | ||
92 | +pad=1 | ||
93 | +activation=leaky | ||
94 | + | ||
95 | +[shortcut] | ||
96 | +from=-3 | ||
97 | +activation=linear | ||
98 | + | ||
99 | +[convolutional] | ||
100 | +xnor=1 | ||
101 | +batch_normalize=1 | ||
102 | +filters=64 | ||
103 | +size=1 | ||
104 | +stride=1 | ||
105 | +pad=1 | ||
106 | +activation=leaky | ||
107 | + | ||
108 | +[convolutional] | ||
109 | +xnor=1 | ||
110 | +batch_normalize=1 | ||
111 | +filters=128 | ||
112 | +size=3 | ||
113 | +stride=1 | ||
114 | +pad=1 | ||
115 | +activation=leaky | ||
116 | + | ||
117 | +[shortcut] | ||
118 | +from=-3 | ||
119 | +activation=linear | ||
120 | + | ||
121 | +# Downsample | ||
122 | + | ||
123 | +[convolutional] | ||
124 | +xnor=1 | ||
125 | +batch_normalize=1 | ||
126 | +filters=256 | ||
127 | +size=3 | ||
128 | +stride=2 | ||
129 | +pad=1 | ||
130 | +activation=leaky | ||
131 | + | ||
132 | +[convolutional] | ||
133 | +xnor=1 | ||
134 | +batch_normalize=1 | ||
135 | +filters=128 | ||
136 | +size=1 | ||
137 | +stride=1 | ||
138 | +pad=1 | ||
139 | +activation=leaky | ||
140 | + | ||
141 | +[convolutional] | ||
142 | +xnor=1 | ||
143 | +batch_normalize=1 | ||
144 | +filters=256 | ||
145 | +size=3 | ||
146 | +stride=1 | ||
147 | +pad=1 | ||
148 | +activation=leaky | ||
149 | + | ||
150 | +[shortcut] | ||
151 | +from=-3 | ||
152 | +activation=linear | ||
153 | + | ||
154 | +[convolutional] | ||
155 | +xnor=1 | ||
156 | +batch_normalize=1 | ||
157 | +filters=128 | ||
158 | +size=1 | ||
159 | +stride=1 | ||
160 | +pad=1 | ||
161 | +activation=leaky | ||
162 | + | ||
163 | +[convolutional] | ||
164 | +xnor=1 | ||
165 | +batch_normalize=1 | ||
166 | +filters=256 | ||
167 | +size=3 | ||
168 | +stride=1 | ||
169 | +pad=1 | ||
170 | +activation=leaky | ||
171 | + | ||
172 | +[shortcut] | ||
173 | +from=-3 | ||
174 | +activation=linear | ||
175 | + | ||
176 | +[convolutional] | ||
177 | +xnor=1 | ||
178 | +batch_normalize=1 | ||
179 | +filters=128 | ||
180 | +size=1 | ||
181 | +stride=1 | ||
182 | +pad=1 | ||
183 | +activation=leaky | ||
184 | + | ||
185 | +[convolutional] | ||
186 | +xnor=1 | ||
187 | +batch_normalize=1 | ||
188 | +filters=256 | ||
189 | +size=3 | ||
190 | +stride=1 | ||
191 | +pad=1 | ||
192 | +activation=leaky | ||
193 | + | ||
194 | +[shortcut] | ||
195 | +from=-3 | ||
196 | +activation=linear | ||
197 | + | ||
198 | +[convolutional] | ||
199 | +xnor=1 | ||
200 | +batch_normalize=1 | ||
201 | +filters=128 | ||
202 | +size=1 | ||
203 | +stride=1 | ||
204 | +pad=1 | ||
205 | +activation=leaky | ||
206 | + | ||
207 | +[convolutional] | ||
208 | +xnor=1 | ||
209 | +batch_normalize=1 | ||
210 | +filters=256 | ||
211 | +size=3 | ||
212 | +stride=1 | ||
213 | +pad=1 | ||
214 | +activation=leaky | ||
215 | + | ||
216 | +[shortcut] | ||
217 | +from=-3 | ||
218 | +activation=linear | ||
219 | + | ||
220 | + | ||
221 | +[convolutional] | ||
222 | +xnor=1 | ||
223 | +batch_normalize=1 | ||
224 | +filters=128 | ||
225 | +size=1 | ||
226 | +stride=1 | ||
227 | +pad=1 | ||
228 | +activation=leaky | ||
229 | + | ||
230 | +[convolutional] | ||
231 | +xnor=1 | ||
232 | +batch_normalize=1 | ||
233 | +filters=256 | ||
234 | +size=3 | ||
235 | +stride=1 | ||
236 | +pad=1 | ||
237 | +activation=leaky | ||
238 | + | ||
239 | +[shortcut] | ||
240 | +from=-3 | ||
241 | +activation=linear | ||
242 | + | ||
243 | +[convolutional] | ||
244 | +xnor=1 | ||
245 | +batch_normalize=1 | ||
246 | +filters=128 | ||
247 | +size=1 | ||
248 | +stride=1 | ||
249 | +pad=1 | ||
250 | +activation=leaky | ||
251 | + | ||
252 | +[convolutional] | ||
253 | +xnor=1 | ||
254 | +batch_normalize=1 | ||
255 | +filters=256 | ||
256 | +size=3 | ||
257 | +stride=1 | ||
258 | +pad=1 | ||
259 | +activation=leaky | ||
260 | + | ||
261 | +[shortcut] | ||
262 | +from=-3 | ||
263 | +activation=linear | ||
264 | + | ||
265 | +[convolutional] | ||
266 | +xnor=1 | ||
267 | +batch_normalize=1 | ||
268 | +filters=128 | ||
269 | +size=1 | ||
270 | +stride=1 | ||
271 | +pad=1 | ||
272 | +activation=leaky | ||
273 | + | ||
274 | +[convolutional] | ||
275 | +xnor=1 | ||
276 | +batch_normalize=1 | ||
277 | +filters=256 | ||
278 | +size=3 | ||
279 | +stride=1 | ||
280 | +pad=1 | ||
281 | +activation=leaky | ||
282 | + | ||
283 | +[shortcut] | ||
284 | +from=-3 | ||
285 | +activation=linear | ||
286 | + | ||
287 | +[convolutional] | ||
288 | +xnor=1 | ||
289 | +batch_normalize=1 | ||
290 | +filters=128 | ||
291 | +size=1 | ||
292 | +stride=1 | ||
293 | +pad=1 | ||
294 | +activation=leaky | ||
295 | + | ||
296 | +[convolutional] | ||
297 | +xnor=1 | ||
298 | +batch_normalize=1 | ||
299 | +filters=256 | ||
300 | +size=3 | ||
301 | +stride=1 | ||
302 | +pad=1 | ||
303 | +activation=leaky | ||
304 | + | ||
305 | +[shortcut] | ||
306 | +from=-3 | ||
307 | +activation=linear | ||
308 | + | ||
309 | +# Downsample | ||
310 | + | ||
311 | +[convolutional] | ||
312 | +xnor=1 | ||
313 | +batch_normalize=1 | ||
314 | +filters=512 | ||
315 | +size=3 | ||
316 | +stride=2 | ||
317 | +pad=1 | ||
318 | +activation=leaky | ||
319 | + | ||
320 | +[convolutional] | ||
321 | +xnor=1 | ||
322 | +batch_normalize=1 | ||
323 | +filters=256 | ||
324 | +size=1 | ||
325 | +stride=1 | ||
326 | +pad=1 | ||
327 | +activation=leaky | ||
328 | + | ||
329 | +[convolutional] | ||
330 | +xnor=1 | ||
331 | +batch_normalize=1 | ||
332 | +filters=512 | ||
333 | +size=3 | ||
334 | +stride=1 | ||
335 | +pad=1 | ||
336 | +activation=leaky | ||
337 | + | ||
338 | +[shortcut] | ||
339 | +from=-3 | ||
340 | +activation=linear | ||
341 | + | ||
342 | + | ||
343 | +[convolutional] | ||
344 | +xnor=1 | ||
345 | +batch_normalize=1 | ||
346 | +filters=256 | ||
347 | +size=1 | ||
348 | +stride=1 | ||
349 | +pad=1 | ||
350 | +activation=leaky | ||
351 | + | ||
352 | +[convolutional] | ||
353 | +xnor=1 | ||
354 | +batch_normalize=1 | ||
355 | +filters=512 | ||
356 | +size=3 | ||
357 | +stride=1 | ||
358 | +pad=1 | ||
359 | +activation=leaky | ||
360 | + | ||
361 | +[shortcut] | ||
362 | +from=-3 | ||
363 | +activation=linear | ||
364 | + | ||
365 | + | ||
366 | +[convolutional] | ||
367 | +xnor=1 | ||
368 | +batch_normalize=1 | ||
369 | +filters=256 | ||
370 | +size=1 | ||
371 | +stride=1 | ||
372 | +pad=1 | ||
373 | +activation=leaky | ||
374 | + | ||
375 | +[convolutional] | ||
376 | +xnor=1 | ||
377 | +batch_normalize=1 | ||
378 | +filters=512 | ||
379 | +size=3 | ||
380 | +stride=1 | ||
381 | +pad=1 | ||
382 | +activation=leaky | ||
383 | + | ||
384 | +[shortcut] | ||
385 | +from=-3 | ||
386 | +activation=linear | ||
387 | + | ||
388 | + | ||
389 | +[convolutional] | ||
390 | +xnor=1 | ||
391 | +batch_normalize=1 | ||
392 | +filters=256 | ||
393 | +size=1 | ||
394 | +stride=1 | ||
395 | +pad=1 | ||
396 | +activation=leaky | ||
397 | + | ||
398 | +[convolutional] | ||
399 | +xnor=1 | ||
400 | +batch_normalize=1 | ||
401 | +filters=512 | ||
402 | +size=3 | ||
403 | +stride=1 | ||
404 | +pad=1 | ||
405 | +activation=leaky | ||
406 | + | ||
407 | +[shortcut] | ||
408 | +from=-3 | ||
409 | +activation=linear | ||
410 | + | ||
411 | +[convolutional] | ||
412 | +xnor=1 | ||
413 | +batch_normalize=1 | ||
414 | +filters=256 | ||
415 | +size=1 | ||
416 | +stride=1 | ||
417 | +pad=1 | ||
418 | +activation=leaky | ||
419 | + | ||
420 | +[convolutional] | ||
421 | +xnor=1 | ||
422 | +batch_normalize=1 | ||
423 | +filters=512 | ||
424 | +size=3 | ||
425 | +stride=1 | ||
426 | +pad=1 | ||
427 | +activation=leaky | ||
428 | + | ||
429 | +[shortcut] | ||
430 | +from=-3 | ||
431 | +activation=linear | ||
432 | + | ||
433 | + | ||
434 | +[convolutional] | ||
435 | +xnor=1 | ||
436 | +batch_normalize=1 | ||
437 | +filters=256 | ||
438 | +size=1 | ||
439 | +stride=1 | ||
440 | +pad=1 | ||
441 | +activation=leaky | ||
442 | + | ||
443 | +[convolutional] | ||
444 | +xnor=1 | ||
445 | +batch_normalize=1 | ||
446 | +filters=512 | ||
447 | +size=3 | ||
448 | +stride=1 | ||
449 | +pad=1 | ||
450 | +activation=leaky | ||
451 | + | ||
452 | +[shortcut] | ||
453 | +from=-3 | ||
454 | +activation=linear | ||
455 | + | ||
456 | + | ||
457 | +[convolutional] | ||
458 | +xnor=1 | ||
459 | +batch_normalize=1 | ||
460 | +filters=256 | ||
461 | +size=1 | ||
462 | +stride=1 | ||
463 | +pad=1 | ||
464 | +activation=leaky | ||
465 | + | ||
466 | +[convolutional] | ||
467 | +xnor=1 | ||
468 | +batch_normalize=1 | ||
469 | +filters=512 | ||
470 | +size=3 | ||
471 | +stride=1 | ||
472 | +pad=1 | ||
473 | +activation=leaky | ||
474 | + | ||
475 | +[shortcut] | ||
476 | +from=-3 | ||
477 | +activation=linear | ||
478 | + | ||
479 | +[convolutional] | ||
480 | +xnor=1 | ||
481 | +batch_normalize=1 | ||
482 | +filters=256 | ||
483 | +size=1 | ||
484 | +stride=1 | ||
485 | +pad=1 | ||
486 | +activation=leaky | ||
487 | + | ||
488 | +[convolutional] | ||
489 | +xnor=1 | ||
490 | +batch_normalize=1 | ||
491 | +filters=512 | ||
492 | +size=3 | ||
493 | +stride=1 | ||
494 | +pad=1 | ||
495 | +activation=leaky | ||
496 | + | ||
497 | +[shortcut] | ||
498 | +from=-3 | ||
499 | +activation=linear | ||
500 | + | ||
501 | +# Downsample | ||
502 | + | ||
503 | +[convolutional] | ||
504 | +xnor=1 | ||
505 | +batch_normalize=1 | ||
506 | +filters=1024 | ||
507 | +size=3 | ||
508 | +stride=2 | ||
509 | +pad=1 | ||
510 | +activation=leaky | ||
511 | + | ||
512 | +[convolutional] | ||
513 | +xnor=1 | ||
514 | +batch_normalize=1 | ||
515 | +filters=512 | ||
516 | +size=1 | ||
517 | +stride=1 | ||
518 | +pad=1 | ||
519 | +activation=leaky | ||
520 | + | ||
521 | +[convolutional] | ||
522 | +xnor=1 | ||
523 | +batch_normalize=1 | ||
524 | +filters=1024 | ||
525 | +size=3 | ||
526 | +stride=1 | ||
527 | +pad=1 | ||
528 | +activation=leaky | ||
529 | + | ||
530 | +[shortcut] | ||
531 | +from=-3 | ||
532 | +activation=linear | ||
533 | + | ||
534 | +[convolutional] | ||
535 | +xnor=1 | ||
536 | +batch_normalize=1 | ||
537 | +filters=512 | ||
538 | +size=1 | ||
539 | +stride=1 | ||
540 | +pad=1 | ||
541 | +activation=leaky | ||
542 | + | ||
543 | +[convolutional] | ||
544 | +xnor=1 | ||
545 | +batch_normalize=1 | ||
546 | +filters=1024 | ||
547 | +size=3 | ||
548 | +stride=1 | ||
549 | +pad=1 | ||
550 | +activation=leaky | ||
551 | + | ||
552 | +[shortcut] | ||
553 | +from=-3 | ||
554 | +activation=linear | ||
555 | + | ||
556 | +[convolutional] | ||
557 | +xnor=1 | ||
558 | +batch_normalize=1 | ||
559 | +filters=512 | ||
560 | +size=1 | ||
561 | +stride=1 | ||
562 | +pad=1 | ||
563 | +activation=leaky | ||
564 | + | ||
565 | +[convolutional] | ||
566 | +xnor=1 | ||
567 | +batch_normalize=1 | ||
568 | +filters=1024 | ||
569 | +size=3 | ||
570 | +stride=1 | ||
571 | +pad=1 | ||
572 | +activation=leaky | ||
573 | + | ||
574 | +[shortcut] | ||
575 | +from=-3 | ||
576 | +activation=linear | ||
577 | + | ||
578 | +[convolutional] | ||
579 | +xnor=1 | ||
580 | +batch_normalize=1 | ||
581 | +filters=512 | ||
582 | +size=1 | ||
583 | +stride=1 | ||
584 | +pad=1 | ||
585 | +activation=leaky | ||
586 | + | ||
587 | +[convolutional] | ||
588 | +xnor=1 | ||
589 | +batch_normalize=1 | ||
590 | +filters=1024 | ||
591 | +size=3 | ||
592 | +stride=1 | ||
593 | +pad=1 | ||
594 | +activation=leaky | ||
595 | + | ||
596 | +[shortcut] | ||
597 | +from=-3 | ||
598 | +activation=linear | ||
599 | + | ||
600 | +[convolutional] | ||
601 | +batch_normalize=1 | ||
602 | +filters=512 | ||
603 | +size=1 | ||
604 | +stride=1 | ||
605 | +pad=1 | ||
606 | +activation=leaky | ||
607 | + | ||
608 | +[avgpool] | ||
609 | + | ||
610 | +[convolutional] | ||
611 | +filters=1000 | ||
612 | +size=1 | ||
613 | +stride=1 | ||
614 | +pad=1 | ||
615 | +activation=linear | ||
616 | + | ||
617 | +[softmax] | ||
618 | +groups=1 | ||
619 | + |
1 | +[net] | ||
2 | +batch=128 | ||
3 | +subdivisions=1 | ||
4 | +height=224 | ||
5 | +width=224 | ||
6 | +max_crop=320 | ||
7 | +channels=3 | ||
8 | +momentum=0.9 | ||
9 | +decay=0.0005 | ||
10 | + | ||
11 | +learning_rate=0.1 | ||
12 | +policy=poly | ||
13 | +power=4 | ||
14 | +max_batches=1600000 | ||
15 | + | ||
16 | +[convolutional] | ||
17 | +batch_normalize=1 | ||
18 | +filters=64 | ||
19 | +size=7 | ||
20 | +stride=2 | ||
21 | +pad=1 | ||
22 | +activation=leaky | ||
23 | + | ||
24 | +[maxpool] | ||
25 | +size=2 | ||
26 | +stride=2 | ||
27 | + | ||
28 | +[convolutional] | ||
29 | +batch_normalize=1 | ||
30 | +filters=192 | ||
31 | +size=3 | ||
32 | +stride=1 | ||
33 | +pad=1 | ||
34 | +activation=leaky | ||
35 | + | ||
36 | +[maxpool] | ||
37 | +size=2 | ||
38 | +stride=2 | ||
39 | + | ||
40 | +[convolutional] | ||
41 | +batch_normalize=1 | ||
42 | +filters=128 | ||
43 | +size=1 | ||
44 | +stride=1 | ||
45 | +pad=1 | ||
46 | +activation=leaky | ||
47 | + | ||
48 | +[convolutional] | ||
49 | +batch_normalize=1 | ||
50 | +filters=256 | ||
51 | +size=3 | ||
52 | +stride=1 | ||
53 | +pad=1 | ||
54 | +activation=leaky | ||
55 | + | ||
56 | +[convolutional] | ||
57 | +batch_normalize=1 | ||
58 | +filters=256 | ||
59 | +size=1 | ||
60 | +stride=1 | ||
61 | +pad=1 | ||
62 | +activation=leaky | ||
63 | + | ||
64 | +[convolutional] | ||
65 | +batch_normalize=1 | ||
66 | +filters=512 | ||
67 | +size=3 | ||
68 | +stride=1 | ||
69 | +pad=1 | ||
70 | +activation=leaky | ||
71 | + | ||
72 | +[maxpool] | ||
73 | +size=2 | ||
74 | +stride=2 | ||
75 | + | ||
76 | +[convolutional] | ||
77 | +batch_normalize=1 | ||
78 | +filters=256 | ||
79 | +size=1 | ||
80 | +stride=1 | ||
81 | +pad=1 | ||
82 | +activation=leaky | ||
83 | + | ||
84 | +[convolutional] | ||
85 | +batch_normalize=1 | ||
86 | +filters=512 | ||
87 | +size=3 | ||
88 | +stride=1 | ||
89 | +pad=1 | ||
90 | +activation=leaky | ||
91 | + | ||
92 | +[convolutional] | ||
93 | +batch_normalize=1 | ||
94 | +filters=256 | ||
95 | +size=1 | ||
96 | +stride=1 | ||
97 | +pad=1 | ||
98 | +activation=leaky | ||
99 | + | ||
100 | +[convolutional] | ||
101 | +batch_normalize=1 | ||
102 | +filters=512 | ||
103 | +size=3 | ||
104 | +stride=1 | ||
105 | +pad=1 | ||
106 | +activation=leaky | ||
107 | + | ||
108 | +[convolutional] | ||
109 | +batch_normalize=1 | ||
110 | +filters=256 | ||
111 | +size=1 | ||
112 | +stride=1 | ||
113 | +pad=1 | ||
114 | +activation=leaky | ||
115 | + | ||
116 | +[convolutional] | ||
117 | +batch_normalize=1 | ||
118 | +filters=512 | ||
119 | +size=3 | ||
120 | +stride=1 | ||
121 | +pad=1 | ||
122 | +activation=leaky | ||
123 | + | ||
124 | +[convolutional] | ||
125 | +batch_normalize=1 | ||
126 | +filters=256 | ||
127 | +size=1 | ||
128 | +stride=1 | ||
129 | +pad=1 | ||
130 | +activation=leaky | ||
131 | + | ||
132 | +[convolutional] | ||
133 | +batch_normalize=1 | ||
134 | +filters=512 | ||
135 | +size=3 | ||
136 | +stride=1 | ||
137 | +pad=1 | ||
138 | +activation=leaky | ||
139 | + | ||
140 | +[convolutional] | ||
141 | +batch_normalize=1 | ||
142 | +filters=512 | ||
143 | +size=1 | ||
144 | +stride=1 | ||
145 | +pad=1 | ||
146 | +activation=leaky | ||
147 | + | ||
148 | +[convolutional] | ||
149 | +batch_normalize=1 | ||
150 | +filters=1024 | ||
151 | +size=3 | ||
152 | +stride=1 | ||
153 | +pad=1 | ||
154 | +activation=leaky | ||
155 | + | ||
156 | +[maxpool] | ||
157 | +size=2 | ||
158 | +stride=2 | ||
159 | + | ||
160 | +[convolutional] | ||
161 | +batch_normalize=1 | ||
162 | +filters=512 | ||
163 | +size=1 | ||
164 | +stride=1 | ||
165 | +pad=1 | ||
166 | +activation=leaky | ||
167 | + | ||
168 | +[convolutional] | ||
169 | +batch_normalize=1 | ||
170 | +filters=1024 | ||
171 | +size=3 | ||
172 | +stride=1 | ||
173 | +pad=1 | ||
174 | +activation=leaky | ||
175 | + | ||
176 | +[convolutional] | ||
177 | +batch_normalize=1 | ||
178 | +filters=512 | ||
179 | +size=1 | ||
180 | +stride=1 | ||
181 | +pad=1 | ||
182 | +activation=leaky | ||
183 | + | ||
184 | +[convolutional] | ||
185 | +batch_normalize=1 | ||
186 | +filters=1024 | ||
187 | +size=3 | ||
188 | +stride=1 | ||
189 | +pad=1 | ||
190 | +activation=leaky | ||
191 | + | ||
192 | +[convolutional] | ||
193 | +filters=1000 | ||
194 | +size=1 | ||
195 | +stride=1 | ||
196 | +pad=1 | ||
197 | +activation=leaky | ||
198 | + | ||
199 | +[avgpool] | ||
200 | + | ||
201 | +[softmax] | ||
202 | +groups=1 | ||
203 | + | ||
204 | +[cost] | ||
205 | +type=sse | ||
206 | + |
1 | +[net] | ||
2 | +batch=1 | ||
3 | +subdivisions=1 | ||
4 | +height=256 | ||
5 | +width=256 | ||
6 | +channels=3 | ||
7 | +momentum=0.9 | ||
8 | +decay=0.0005 | ||
9 | + | ||
10 | +learning_rate=0.5 | ||
11 | +policy=poly | ||
12 | +power=6 | ||
13 | +max_batches=500000 | ||
14 | + | ||
15 | +[convolutional] | ||
16 | +filters=64 | ||
17 | +size=7 | ||
18 | +stride=2 | ||
19 | +pad=1 | ||
20 | +activation=leaky | ||
21 | + | ||
22 | +[maxpool] | ||
23 | +size=2 | ||
24 | +stride=2 | ||
25 | + | ||
26 | +[convolutional] | ||
27 | +filters=192 | ||
28 | +size=3 | ||
29 | +stride=1 | ||
30 | +pad=1 | ||
31 | +activation=leaky | ||
32 | + | ||
33 | +[maxpool] | ||
34 | +size=2 | ||
35 | +stride=2 | ||
36 | + | ||
37 | +[convolutional] | ||
38 | +filters=128 | ||
39 | +size=1 | ||
40 | +stride=1 | ||
41 | +pad=1 | ||
42 | +activation=leaky | ||
43 | + | ||
44 | +[convolutional] | ||
45 | +filters=256 | ||
46 | +size=3 | ||
47 | +stride=1 | ||
48 | +pad=1 | ||
49 | +activation=leaky | ||
50 | + | ||
51 | +[convolutional] | ||
52 | +filters=256 | ||
53 | +size=1 | ||
54 | +stride=1 | ||
55 | +pad=1 | ||
56 | +activation=leaky | ||
57 | + | ||
58 | +[convolutional] | ||
59 | +filters=512 | ||
60 | +size=3 | ||
61 | +stride=1 | ||
62 | +pad=1 | ||
63 | +activation=leaky | ||
64 | + | ||
65 | +[maxpool] | ||
66 | +size=2 | ||
67 | +stride=2 | ||
68 | + | ||
69 | +[convolutional] | ||
70 | +filters=256 | ||
71 | +size=1 | ||
72 | +stride=1 | ||
73 | +pad=1 | ||
74 | +activation=leaky | ||
75 | + | ||
76 | +[convolutional] | ||
77 | +filters=512 | ||
78 | +size=3 | ||
79 | +stride=1 | ||
80 | +pad=1 | ||
81 | +activation=leaky | ||
82 | + | ||
83 | +[convolutional] | ||
84 | +filters=256 | ||
85 | +size=1 | ||
86 | +stride=1 | ||
87 | +pad=1 | ||
88 | +activation=leaky | ||
89 | + | ||
90 | +[convolutional] | ||
91 | +filters=512 | ||
92 | +size=3 | ||
93 | +stride=1 | ||
94 | +pad=1 | ||
95 | +activation=leaky | ||
96 | + | ||
97 | +[convolutional] | ||
98 | +filters=256 | ||
99 | +size=1 | ||
100 | +stride=1 | ||
101 | +pad=1 | ||
102 | +activation=leaky | ||
103 | + | ||
104 | +[convolutional] | ||
105 | +filters=512 | ||
106 | +size=3 | ||
107 | +stride=1 | ||
108 | +pad=1 | ||
109 | +activation=leaky | ||
110 | + | ||
111 | +[convolutional] | ||
112 | +filters=256 | ||
113 | +size=1 | ||
114 | +stride=1 | ||
115 | +pad=1 | ||
116 | +activation=leaky | ||
117 | + | ||
118 | +[convolutional] | ||
119 | +filters=512 | ||
120 | +size=3 | ||
121 | +stride=1 | ||
122 | +pad=1 | ||
123 | +activation=leaky | ||
124 | + | ||
125 | +[convolutional] | ||
126 | +filters=512 | ||
127 | +size=1 | ||
128 | +stride=1 | ||
129 | +pad=1 | ||
130 | +activation=leaky | ||
131 | + | ||
132 | +[convolutional] | ||
133 | +filters=1024 | ||
134 | +size=3 | ||
135 | +stride=1 | ||
136 | +pad=1 | ||
137 | +activation=leaky | ||
138 | + | ||
139 | +[maxpool] | ||
140 | +size=2 | ||
141 | +stride=2 | ||
142 | + | ||
143 | +[convolutional] | ||
144 | +filters=512 | ||
145 | +size=1 | ||
146 | +stride=1 | ||
147 | +pad=1 | ||
148 | +activation=leaky | ||
149 | + | ||
150 | +[convolutional] | ||
151 | +filters=1024 | ||
152 | +size=3 | ||
153 | +stride=1 | ||
154 | +pad=1 | ||
155 | +activation=leaky | ||
156 | + | ||
157 | +[convolutional] | ||
158 | +filters=512 | ||
159 | +size=1 | ||
160 | +stride=1 | ||
161 | +pad=1 | ||
162 | +activation=leaky | ||
163 | + | ||
164 | +[convolutional] | ||
165 | +filters=1024 | ||
166 | +size=3 | ||
167 | +stride=1 | ||
168 | +pad=1 | ||
169 | +activation=leaky | ||
170 | + | ||
171 | +[avgpool] | ||
172 | + | ||
173 | +[connected] | ||
174 | +output=1000 | ||
175 | +activation=leaky | ||
176 | + | ||
177 | +[softmax] | ||
178 | +groups=1 | ||
179 | + |
1 | +[net] | ||
2 | +batch=128 | ||
3 | +subdivisions=1 | ||
4 | +height=224 | ||
5 | +width=224 | ||
6 | +max_crop=320 | ||
7 | +channels=3 | ||
8 | +momentum=0.9 | ||
9 | +decay=0.0005 | ||
10 | + | ||
11 | +learning_rate=0.01 | ||
12 | +max_batches = 0 | ||
13 | +policy=steps | ||
14 | +steps=444000,590000,970000 | ||
15 | +scales=.5,.2,.1 | ||
16 | + | ||
17 | +#policy=sigmoid | ||
18 | +#gamma=.00008 | ||
19 | +#step=100000 | ||
20 | +#max_batches=200000 | ||
21 | + | ||
22 | +[convolutional] | ||
23 | +batch_normalize=1 | ||
24 | +filters=64 | ||
25 | +size=7 | ||
26 | +stride=2 | ||
27 | +pad=1 | ||
28 | +activation=leaky | ||
29 | + | ||
30 | +[maxpool] | ||
31 | +size=2 | ||
32 | +stride=2 | ||
33 | + | ||
34 | +[convolutional] | ||
35 | +batch_normalize=1 | ||
36 | +filters=192 | ||
37 | +size=3 | ||
38 | +stride=1 | ||
39 | +pad=1 | ||
40 | +activation=leaky | ||
41 | + | ||
42 | +[maxpool] | ||
43 | +size=2 | ||
44 | +stride=2 | ||
45 | + | ||
46 | +[convolutional] | ||
47 | +batch_normalize=1 | ||
48 | +filters=128 | ||
49 | +size=1 | ||
50 | +stride=1 | ||
51 | +pad=1 | ||
52 | +activation=leaky | ||
53 | + | ||
54 | +[convolutional] | ||
55 | +batch_normalize=1 | ||
56 | +filters=256 | ||
57 | +size=3 | ||
58 | +stride=1 | ||
59 | +pad=1 | ||
60 | +activation=leaky | ||
61 | + | ||
62 | +[convolutional] | ||
63 | +batch_normalize=1 | ||
64 | +filters=256 | ||
65 | +size=1 | ||
66 | +stride=1 | ||
67 | +pad=1 | ||
68 | +activation=leaky | ||
69 | + | ||
70 | +[convolutional] | ||
71 | +batch_normalize=1 | ||
72 | +filters=512 | ||
73 | +size=3 | ||
74 | +stride=1 | ||
75 | +pad=1 | ||
76 | +activation=leaky | ||
77 | + | ||
78 | +[maxpool] | ||
79 | +size=2 | ||
80 | +stride=2 | ||
81 | + | ||
82 | +[convolutional] | ||
83 | +batch_normalize=1 | ||
84 | +filters=256 | ||
85 | +size=1 | ||
86 | +stride=1 | ||
87 | +pad=1 | ||
88 | +activation=leaky | ||
89 | + | ||
90 | +[convolutional] | ||
91 | +batch_normalize=1 | ||
92 | +filters=512 | ||
93 | +size=3 | ||
94 | +stride=1 | ||
95 | +pad=1 | ||
96 | +activation=leaky | ||
97 | + | ||
98 | +[convolutional] | ||
99 | +batch_normalize=1 | ||
100 | +filters=256 | ||
101 | +size=1 | ||
102 | +stride=1 | ||
103 | +pad=1 | ||
104 | +activation=leaky | ||
105 | + | ||
106 | +[convolutional] | ||
107 | +batch_normalize=1 | ||
108 | +filters=512 | ||
109 | +size=3 | ||
110 | +stride=1 | ||
111 | +pad=1 | ||
112 | +activation=leaky | ||
113 | + | ||
114 | +[convolutional] | ||
115 | +batch_normalize=1 | ||
116 | +filters=256 | ||
117 | +size=1 | ||
118 | +stride=1 | ||
119 | +pad=1 | ||
120 | +activation=leaky | ||
121 | + | ||
122 | +[convolutional] | ||
123 | +batch_normalize=1 | ||
124 | +filters=512 | ||
125 | +size=3 | ||
126 | +stride=1 | ||
127 | +pad=1 | ||
128 | +activation=leaky | ||
129 | + | ||
130 | +[convolutional] | ||
131 | +batch_normalize=1 | ||
132 | +filters=256 | ||
133 | +size=1 | ||
134 | +stride=1 | ||
135 | +pad=1 | ||
136 | +activation=leaky | ||
137 | + | ||
138 | +[convolutional] | ||
139 | +batch_normalize=1 | ||
140 | +filters=512 | ||
141 | +size=3 | ||
142 | +stride=1 | ||
143 | +pad=1 | ||
144 | +activation=leaky | ||
145 | + | ||
146 | +[convolutional] | ||
147 | +batch_normalize=1 | ||
148 | +filters=512 | ||
149 | +size=1 | ||
150 | +stride=1 | ||
151 | +pad=1 | ||
152 | +activation=leaky | ||
153 | + | ||
154 | +[convolutional] | ||
155 | +batch_normalize=1 | ||
156 | +filters=1024 | ||
157 | +size=3 | ||
158 | +stride=1 | ||
159 | +pad=1 | ||
160 | +activation=leaky | ||
161 | + | ||
162 | +[maxpool] | ||
163 | +size=2 | ||
164 | +stride=2 | ||
165 | + | ||
166 | +[convolutional] | ||
167 | +batch_normalize=1 | ||
168 | +filters=1024 | ||
169 | +size=1 | ||
170 | +stride=1 | ||
171 | +pad=1 | ||
172 | +activation=leaky | ||
173 | + | ||
174 | +[convolutional] | ||
175 | +batch_normalize=1 | ||
176 | +filters=2048 | ||
177 | +size=3 | ||
178 | +stride=1 | ||
179 | +pad=1 | ||
180 | +activation=leaky | ||
181 | + | ||
182 | +[convolutional] | ||
183 | +batch_normalize=1 | ||
184 | +filters=1024 | ||
185 | +size=1 | ||
186 | +stride=1 | ||
187 | +pad=1 | ||
188 | +activation=leaky | ||
189 | + | ||
190 | +[convolutional] | ||
191 | +batch_normalize=1 | ||
192 | +filters=2048 | ||
193 | +size=3 | ||
194 | +stride=1 | ||
195 | +pad=1 | ||
196 | +activation=leaky | ||
197 | + | ||
198 | +[avgpool] | ||
199 | + | ||
200 | +[connected] | ||
201 | +output=21842 | ||
202 | +activation=leaky | ||
203 | + | ||
204 | +[softmax] | ||
205 | +groups=1 | ||
206 | + | ||
207 | +[cost] | ||
208 | +type=sse | ||
209 | + |
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