cleanup
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parent
238f159cab
commit
018d0c21c8
2 changed files with 10 additions and 10 deletions
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@ -94,7 +94,7 @@ def generate_frames():
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detections = results.pandas().xyxy[0] # Convert detections to Pandas DataFrame
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detections = results.pandas().xyxy[0] # Convert detections to Pandas DataFrame
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if detections.empty:
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if detections.empty:
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print("🚫 No objects detected.")
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print("No objects detected.")
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else:
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else:
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print(f"✅ Detected {len(detections)} objects!")
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print(f"✅ Detected {len(detections)} objects!")
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@ -111,7 +111,7 @@ def generate_frames():
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cv2.putText(frame, f"{label} ({confidence:.2f})", (x1, y1 - 10),
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cv2.putText(frame, f"{label} ({confidence:.2f})", (x1, y1 - 10),
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cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
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cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
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# Encode and yield the frame as JPEG
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# Encode and present the frame as JPEG
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_, buffer = cv2.imencode('.jpg', frame)
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_, buffer = cv2.imencode('.jpg', frame)
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yield (b'--frame\r\n'
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yield (b'--frame\r\n'
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b'Content-Type: image/jpeg\r\n\r\n' + buffer.tobytes() + b'\r\n')
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b'Content-Type: image/jpeg\r\n\r\n' + buffer.tobytes() + b'\r\n')
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@ -123,6 +123,6 @@ def video_feed():
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return Response(generate_frames(), mimetype='multipart/x-mixed-replace; boundary=frame')
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return Response(generate_frames(), mimetype='multipart/x-mixed-replace; boundary=frame')
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if __name__ == '__main__':
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if __name__ == '__main__':
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print("🚀 Server running at http://localhost:5000/video")
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print("Running at http://localhost:5000/video")
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app.run(host='0.0.0.0', port=5000, debug=True, threaded=True)
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app.run(host='0.0.0.0', port=5000, debug=True, threaded=True)
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@ -10,18 +10,18 @@ import numpy as np
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import warnings
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import warnings
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warnings.simplefilter("ignore", category=FutureWarning)
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warnings.simplefilter("ignore", category=FutureWarning) #ignore torch warnings
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app = Flask(__name__)
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app = Flask(__name__)
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YOUTUBE_URL = "https://www.youtube.com/watch?v=i3w7qZVSAsY" # Stream URL
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YOUTUBE_URL = "https://www.youtube.com/watch?v=i3w7qZVSAsY" # Stream URL example
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CONFIDENCE_THRESHOLD = 0.25 # Confidence threshold for object detection
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CONFIDENCE_THRESHOLD = 0.25 # Confidence threshold for object detection
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MODEL = "yolov5s" # YOLO model version (yolov5s, yolov5m, etc.)
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MODEL = "yolov5s" # YOLO model version (yolov5s, yolov5m, etc.)
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# Load YOLOv5 model
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# Load YOLO5 model
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print("🔄 Loading YOLOv5 model...")
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print("Loading YOLOv5 model...")
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model = torch.hub.load("ultralytics/yolov5", "custom", path=MODEL, force_reload=True)
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model = torch.hub.load("ultralytics/yolov5", "custom", path=MODEL, force_reload=True)
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print("✅ YOLOv5 loaded successfully!")
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print("YOLOv5 loaded successfully!")
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def get_stream_url():
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def get_stream_url():
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"""Fetch fresh 720p YouTube stream URL using yt-dlp."""
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"""Fetch fresh 720p YouTube stream URL using yt-dlp."""
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@ -57,7 +57,7 @@ def generate_frames():
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detections = results.pandas().xyxy[0] # Convert detections to Pandas DataFrame
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detections = results.pandas().xyxy[0] # Convert detections to Pandas DataFrame
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if detections.empty:
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if detections.empty:
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print("🚫 No objects detected in this frame.")
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print("No objects detected in this frame.")
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else:
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else:
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print(f"✅ Detected {len(detections)} objects!")
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print(f"✅ Detected {len(detections)} objects!")
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print(detections[["name", "confidence"]]) # Print detected object names and confidence
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print(detections[["name", "confidence"]]) # Print detected object names and confidence
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@ -85,6 +85,6 @@ def video_feed():
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return Response(generate_frames(), mimetype='multipart/x-mixed-replace; boundary=frame')
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return Response(generate_frames(), mimetype='multipart/x-mixed-replace; boundary=frame')
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if __name__ == '__main__':
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if __name__ == '__main__':
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print("🚀 Server running at http://localhost:5000/video")
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print("Running at http://localhost:5000/video")
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app.run(host='0.0.0.0', port=5000, debug=True, threaded=True)
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app.run(host='0.0.0.0', port=5000, debug=True, threaded=True)
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