seungmin lee

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Showing 891 changed files with 4995 additions and 0 deletions
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
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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 +
This diff is collapsed. Click to expand it.
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 +classes= 80
2 +train = E:/MSCOCO/trainvalno5k.txt
3 +#train = E:/MSCOCO/5k.txt
4 +valid = E:/MSCOCO/5k.txt
5 +names = data/coco.names
6 +backup = backup
7 +eval=coco
8 +
1 +classes= 9418
2 +#train = /home/pjreddie/data/coco/trainvalno5k.txt
3 +train = data/combine9k.train.list
4 +valid = /home/pjreddie/data/imagenet/det.val.files
5 +labels = data/9k.labels
6 +names = data/9k.names
7 +backup = backup/
8 +map = data/inet9k.map
9 +eval = imagenet
10 +results = results
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
This diff is collapsed. Click to expand it.
This diff is collapsed. Click to expand it.
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 +
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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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