Update app.py

app.py

@@ -9,6 +9,7 @@ import gradio as gr
 import subprocess
 from PIL import Image
 
+progress = 0
 
 def video_to_frames(video_path, output_folder):
     vidcap = cv2.VideoCapture(video_path)
@@ -30,6 +31,7 @@ def video_to_frames(video_path, output_folder):
 
 def frames_to_video(frame_folder, video_path, image_path, frame_count,fps):
     print("ImagePath",image_path)
+    global progress
     frames = [f for f in os.listdir(frame_folder) if f.endswith('.jpg')]
     frames.sort(key=lambda x: int(x.split('_')[1].split('.')[0]))  # Sort frames in ascending order
 
@@ -47,6 +49,7 @@ def frames_to_video(frame_folder, video_path, image_path, frame_count,fps):
     face_enhancer = gfpgan.GFPGANer(model_path="GFPGANv1.4.pth", upscale=1, device='cuda')
     
     for i in tqdm(range(frame_count), desc="Converting frames to video"):
+        print("Progress:",progress)
         img1 = cv2.imread(os.path.join(frame_folder, frames[i]))
         #img2_pil = Image.open(image_path)
         #img2_cv2 = cv2.cvtColor(np.array(img2_pil), cv2.COLOR_RGB2BGR)
@@ -68,7 +71,6 @@ def frames_to_video(frame_folder, video_path, image_path, frame_count,fps):
         else:
             out.write(img1)
         progress = int((i + 1) / frame_count * 100)
-        print(progress,end="")
     out.release()
     
     print(f"Video saved at {video_path}.")
@@ -76,8 +78,8 @@ def frames_to_video(frame_folder, video_path, image_path, frame_count,fps):
 def face_swap(video_path, image_path):
     output_folder = "Out_Frames"
     frame_count = video_to_frames(video_path, output_folder)
-    if frame_count[0] > 500:
-        frame_count[0] = 500
+    if frame_count[0] > 400:
+        frame_count[0] = 400
     output_video_path = "output_video.mp4" 
     frames_to_video(output_folder, output_video_path, image_path, frame_count[0],frame_count[1])
     return output_video_path