trying to fix yolov4 issue

sparse_coding_torch/keras_model.py

@@ -258,7 +258,7 @@ class PNBClassifier(keras.layers.Layer):
 
         self.max_pool = keras.layers.MaxPooling2D(pool_size=8, strides=8)
 #         self.conv_1 = keras.layers.Conv2D(32, kernel_size=8, strides=4, activation='relu', padding='valid')
-        self.conv_2 = keras.layers.Conv2D(48, kernel_size=4, strides=2, activation='relu', padding='valid')
+        self.conv_2 = keras.layers.Conv2D(48, kernel_size=(8, 16), strides=4, activation='relu', padding='valid')
 #         self.conv_3 = keras.layers.Conv2D(24, kernel_size=4, strides=2, activation='relu', padding='valid')
 #         self.conv_4 = keras.layers.Conv2D(24, kernel_size=4, strides=2, activation='relu', padding='valid')
 
@@ -266,8 +266,8 @@ class PNBClassifier(keras.layers.Layer):
 
         self.dropout = keras.layers.Dropout(0.5)
 
-#         self.ff_1 = keras.layers.Dense(1000, activation='relu', use_bias=True)
-#         self.ff_2 = keras.layers.Dense(500, activation='relu', use_bias=True)
+        self.ff_1 = keras.layers.Dense(1000, activation='relu', use_bias=True)
+        self.ff_2 = keras.layers.Dense(500, activation='relu', use_bias=True)
         self.ff_3 = keras.layers.Dense(100, activation='relu', use_bias=True)
         self.ff_4 = keras.layers.Dense(1)
 
@@ -280,10 +280,10 @@ class PNBClassifier(keras.layers.Layer):
 #         x = self.conv_3(x)
 #         x = self.conv_4(x)
         x = self.flatten(x)
-#         x = self.ff_1(x)
-#         x = self.dropout(x)
-#         x = self.ff_2(x)
-#         x = self.dropout(x)
+        x = self.ff_1(x)
+        x = self.dropout(x)
+        x = self.ff_2(x)
+        x = self.dropout(x)
         x = self.ff_3(x)
         x = self.dropout(x)
         x = self.ff_4(x)

sparse_coding_torch/train_classifier.py

@@ -50,7 +50,7 @@ if __name__ == "__main__":
     
     if args.dataset == 'pnb':
         image_height = 285
-        image_width = 235
+        image_width = 470
     elif args.dataset == 'ptx':
         image_height = 100
         image_width = 200

sparse_coding_torch/video_loader.py

@@ -98,11 +98,11 @@ def get_yolo_regions(yolo_model, clip, is_right):
         lower_y = upper_y - 285
         
         if is_right:
-            lower_x = center_x - 235
+            lower_x = center_x - 470
             upper_x = center_x
         else:
             lower_x = center_x
-            upper_x = center_x + 235
+            upper_x = center_x + 470
 
         trimmed_clip = clip[:, :, lower_y:upper_y, lower_x:upper_x]
         
@@ -172,8 +172,8 @@ class PNBLoader(Dataset):
         self.augmentation = augmentation
         self.labels = [name for name in listdir(video_path) if isdir(join(video_path, name))]
         
-        clip_cache_file = 'clip_cache_pnb.pt'
-        clip_cache_final_file = 'clip_cache_pnb_final.pt'
+        clip_cache_file = 'clip_cache_pnb_double.pt'
+        clip_cache_final_file = 'clip_cache_pnb_final_double.pt'
         
         region_labels = load_pnb_region_labels(join(video_path, 'sme_region_labels.csv'))
 
@@ -222,15 +222,15 @@ class PNBLoader(Dataset):
 #                                 cv2.imwrite('test.png', vc_sub[0, 0, :, :].unsqueeze(2).numpy())
 
                                 for clip in get_yolo_regions(yolo_model, vc_sub, is_right):
-#                                     if self.transform:
-#                                         clip = self.transform(clip)
+                                    if self.transform:
+                                        clip = self.transform(clip)
                                         
 #                                     print(clip[0, 0, :, :].size())
 #                                     cv2.imwrite('test_yolo.png', clip[0, 0, :, :].unsqueeze(2).numpy())
 #                                     print(clip.shape)
 #                                     tv.io.write_video('test_yolo.mp4', clip.swapaxes(0,1).swapaxes(1,2).swapaxes(2,3).numpy(), fps=20)
-                                    print(path)
-                                    raise Exception
+#                                     print(path)
+#                                     raise Exception
 
                                     self.clips.append(('Negatives', clip, self.videos[vid_idx][2]))
 

yolov4 @ 9f16748a

-Subproject commit 9f16748aa3f45ff240608da4bd9b1216a29127f5