fixed video test code

@@ -16,7 +16,7 @@ def readImage(path):
 
 def main():
     ANNOTATION_PATH = '../data/train.txt' #annotation set (train/val/test) text file
-    IMAGE_DIRECTORY = 'image_data/' #image directory
+    IMAGE_DIRECTORY = 'image_data' #image directory
     SAVE_PATH = 'train.tfrecord' #save path for tfrecord
 
     print('Tensorflow version:', tf.__version__) #tensorflow version should be 1.x

@@ -12,8 +12,9 @@ img_size = 416
 weight_path = '../../data/darknet_weights/yolov3.weights'
 save_path = '../../data/darknet_weights/yolov3.ckpt'
 anchors = parse_anchors('../../data/yolo_anchors.txt')
+class_num = 1
 
-model = yolov3(80, anchors)
+model = yolov3(class_num, anchors)
 with tf.Session() as sess:
     inputs = tf.placeholder(tf.float32, [1, img_size, img_size, 3])
 

@@ -14,19 +14,19 @@ from data_utils import letterbox_resize
 from model import yolov3
 
 parser = argparse.ArgumentParser(description="YOLO-V3 video test procedure.")
-parser.add_argument("input_video", type=str,
+parser.add_argument("--input_video", type=str, default="../../data/video.mp4",
                     help="The path of the input video.")
-parser.add_argument("--anchor_path", type=str, default="./data/yolo_anchors.txt",
+parser.add_argument("--anchor_path", type=str, default="../../data/yolo_anchors.txt",
                     help="The path of the anchor txt file.")
 parser.add_argument("--new_size", nargs='*', type=int, default=[416, 416],
                     help="Resize the input image with `new_size`, size format: [width, height]")
 parser.add_argument("--letterbox_resize", type=lambda x: (str(x).lower() == 'true'), default=True,
                     help="Whether to use the letterbox resize.")
-parser.add_argument("--class_name_path", type=str, default="./data/classes.txt",
+parser.add_argument("--class_name_path", type=str, default="../../data/classes.txt",
                     help="The path of the class names.")
-parser.add_argument("--restore_path", type=str, default="./data/darknet_weights/yolov3.ckpt",
+parser.add_argument("--restore_path", type=str, default="../data/trained/model.ckpt",
                     help="The path of the weights to restore.")
-parser.add_argument("--save_video", type=lambda x: (str(x).lower() == 'true'), default=False,
+parser.add_argument("--save_video", type=lambda x: (str(x).lower() == 'true'), default=True,
                     help="Whether to save the video detection results.")
 args = parser.parse_args()
 

@@ -1672,7 +1672,8 @@
         "  save_path = '/content/gdrive/My Drive/yolo/weights/yolov3.ckpt'\n",
         "  anchors = parse_anchors('/content/gdrive/My Drive/yolo/data/yolo_anchors.txt')\n",
         "\n",
-        "  model = yolov3(80, anchors)\n",
+		"  class_num = 1\n"
+        "  model = yolov3(class_num, anchors)\n",
         "  with tf.Session() as sess:\n",
         "      inputs = tf.placeholder(tf.float32, [1, img_size, img_size, 3])\n",
         "\n",