Update app.py

app.py

@@ -1,5 +1,7 @@
 import cv2
 import numpy as np
+import torch
+from transformers import pipeline
 
 class VideoPlayer:
     def __init__(self, video_path):
@@ -8,6 +10,25 @@ class VideoPlayer:
         self.is_stopped = False
         self.frame = None
         self.playback_speed = 1.0
+        self.detector = pipeline("object-detection")  # Hugging Face Object Detection Pipeline
+
+    def process_frame(self, frame):
+        # Convert the frame to RGB (Hugging Face models expect RGB input)
+        rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+        
+        # Perform object detection (can be changed to any other Hugging Face task)
+        results = self.detector(rgb_frame)
+        
+        # Annotate the frame with detection results
+        for result in results:
+            box = result['box']
+            label = result['label']
+            score = result['score']
+            x1, y1, x2, y2 = box
+            cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
+            cv2.putText(frame, f"{label}: {score:.2f}", (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
+        
+        return frame
 
     def play(self):
         while True:
@@ -20,6 +41,9 @@ class VideoPlayer:
                     print("End of video")
                     break
 
+                # Process the frame using Hugging Face (can be changed to any other task)
+                self.frame = self.process_frame(self.frame)
+
             # Show the current frame
             cv2.imshow('Video Player', self.frame)