use mjpeg and convert bgr to rgb

modules/capturer.py

@@ -4,13 +4,22 @@ import cv2
 
 def get_video_frame(video_path: str, frame_number: int = 0) -> Any:
     capture = cv2.VideoCapture(video_path)
+
+    # Set MJPEG format to ensure correct color space handling
+    capture.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter_fourcc(*'MJPG'))
+    # Force OpenCV to convert to RGB
+    capture.set(cv2.CAP_PROP_CONVERT_RGB, 1)
+    
     frame_total = capture.get(cv2.CAP_PROP_FRAME_COUNT)
     capture.set(cv2.CAP_PROP_POS_FRAMES, min(frame_total, frame_number - 1))
     has_frame, frame = capture.read()
-    capture.release()
+
     if has_frame:
-        return frame
+        # Convert the frame color if necessary
-    return None
+        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+
+    capture.release()
+    return frame if has_frame else None
 
 
 def get_video_frame_total(video_path: str) -> int:

modules/predicter.py

@@ -1,6 +1,7 @@
 import numpy
 import opennsfw2
 from PIL import Image
+import cv2  # Add OpenCV import
 
 from modules.typing import Frame
 
@@ -10,6 +11,8 @@ MAX_PROBABILITY = 0.85
 model = None
 
 def predict_frame(target_frame: Frame) -> bool:
+    # Convert the frame to RGB before processing
+    target_frame = cv2.cvtColor(target_frame, cv2.COLOR_BGR2RGB)
     image = Image.fromarray(target_frame)
     image = opennsfw2.preprocess_image(image, opennsfw2.Preprocessing.YAHOO)
     global model

modules/processors/frame/face_swapper.py

@@ -49,6 +49,8 @@ def swap_face(source_face: Face, target_face: Face, temp_frame: Frame) -> Frame:
 
 
 def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
+    # Ensure the frame is in RGB format
+    temp_frame = cv2.cvtColor(temp_frame, cv2.COLOR_BGR2RGB)
     if modules.globals.many_faces:
         many_faces = get_many_faces(temp_frame)
         if many_faces: