Update app.py

app.py

@@ -153,6 +153,8 @@ def make_video(video_path, outdir='./vis_video_depth', encoder='vits', blur_data
         #out = cv2.VideoWriter(output_path, fourcc, frame_rate, (output_width, frame_height))
 
         global comb_frames
+        global frames
+        global depths
         count = 0
         n = 0
         depth_frames = []
@@ -224,13 +226,13 @@ def make_video(video_path, outdir='./vis_video_depth', encoder='vits', blur_data
             blur_frame = blur_image(cv2.cvtColor(raw_frame, cv2.COLOR_BGR2BGRA), depth_color, blur_data)
             
             cv2.imwrite(f"f{count}.png", blur_frame)
-            orig_frames.append(f"f{count}.png")
+            frames.append(f"f{count}.png")
 
             cv2.imwrite(f"f{count}_.png", blur_frame)
             backup_frames.append(f"f{count}_.png")
             
             cv2.imwrite(f"f{count}_dmap.png", depth_color)
-            depth_frames.append(f"f{count}_dmap.png")
+            depths.append(f"f{count}_dmap.png")
 
             depth_gray = seg_frame(depth_gray, o, b) + 128
             #print(depth_gray[depth_gray>128]-128)
@@ -242,8 +244,8 @@ def make_video(video_path, outdir='./vis_video_depth', encoder='vits', blur_data
         color_transfer(0)
 
         j=0
-        while j<len(orig_frames):
-            comb_frame = np.concatenate((cv2.imread(orig_frames[j]), cv2.imread(depth_frames[j])), axis=0)
+        while j<len(frames):
+            comb_frame = np.concatenate((cv2.imread(frames[j]), cv2.imread(depths[j])), axis=0)
 
             cv2.imwrite(f"f{j}_comb.png", comb_frame)
             comb_frames.append(f"f{j}_comb.png")
@@ -258,12 +260,8 @@ def make_video(video_path, outdir='./vis_video_depth', encoder='vits', blur_data
 
         global gradient
         global frame_selected
-        global depths
-        global frames
-        global backups 
-        frames = orig_frames
+        global backups
         backups = backup_frames
-        depths = depth_frames
 
         if depth_color.shape[0] == 2048: #height
             gradient = cv2.imread('./gradient_large.png').astype(np.uint8)