Update app.py

app.py

@@ -8,8 +8,6 @@ import tempfile
 import os
 import threading
 import traceback
-import cv2
-import numpy as np
 
 app = Flask(__name__)
 CORS(app)
@@ -35,26 +33,6 @@ def download_pipeline():
         print(f"Error downloading pipeline: {e}")
         return False
 
-def export_video(frames_list, temp_video_path):
-    # Convert PIL images to numpy arrays
-    frames_np = [np.array(frame) for frame in frames_list]
-
-    # Determine the dimensions (height, width) of the frames
-    height, width, _ = frames_np[0].shape
-
-    # Create a VideoWriter object to write the frames to a video file
-    fourcc = cv2.VideoWriter_fourcc(*'mp4v')  # Codec for MP4 format
-    out = cv2.VideoWriter(temp_video_path, fourcc, 12, (width, height))  # Adjust fps as needed
-
-    # Write each frame to the video file
-    for frame_np in frames_np:
-        # Convert RGB image (numpy array) to BGR (OpenCV format) for writing
-        frame_bgr = cv2.cvtColor(frame_np, cv2.COLOR_RGB2BGR)
-        out.write(frame_bgr)
-
-    # Release the VideoWriter object
-    out.release()
-
 def generate_and_export_animation(prompt):
     global pipe
 
@@ -79,8 +57,7 @@ def generate_and_export_animation(prompt):
         with tempfile.NamedTemporaryFile(suffix='.mp4', delete=False) as temp_file:
             temp_video_path = temp_file.name
             print('temp_video_path', temp_video_path)
-            # export_to_video(output.frames[0], temp_video_path)
-            export_video(output.frames[0], temp_video_path)
+            export_to_video(output.frames[0], temp_video_path)
 
         with open(temp_video_path, 'rb') as video_file:
             video_binary = video_file.read()