Upload app.py

app.py

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+from flask import Flask, Response, render_template, request
+import torch
+from ultralytics import YOLO
+import cv2
+import numpy as np
+
+app = Flask(__name__)
+
+# Load YOLOv8 model
+model = YOLO("yolov8x.pt")
+
+# Store user-provided IP Webcam URL
+IP_WEBCAM_URL = None
+
+def generate_frames():
+    global IP_WEBCAM_URL
+    if not IP_WEBCAM_URL:
+        return
+
+    cap = cv2.VideoCapture(IP_WEBCAM_URL)
+
+    while True:
+        success, frame = cap.read()
+        if not success:
+            break
+
+        # Perform YOLOv8 object detection
+        results = model.predict(frame)
+        
+        for result in results:
+            for box in result.boxes:
+                x1, y1, x2, y2 = map(int, box.xyxy[0])
+                label = result.names[int(box.cls[0])]
+                conf = box.conf[0].item()
+
+                # Draw bounding box
+                cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
+                cv2.putText(frame, f"{label} {conf:.2f}", (x1, y1 - 10),
+                            cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
+
+        # Encode frame as JPEG
+        _, buffer = cv2.imencode('.jpg', frame)
+        frame_bytes = buffer.tobytes()
+
+        yield (b'--frame\r\n'
+               b'Content-Type: image/jpeg\r\n\r\n' + frame_bytes + b'\r\n')
+
+    cap.release()
+
+@app.route('/', methods=['GET', 'POST'])
+def index():
+    global IP_WEBCAM_URL
+    if request.method == 'POST':
+        IP_WEBCAM_URL = request.form['ip_url']
+    return render_template('index.html', ip_url=IP_WEBCAM_URL)
+
+@app.route('/video_feed')
+def video_feed():
+    return Response(generate_frames(), mimetype='multipart/x-mixed-replace; boundary=frame')
+
+if __name__ == '__main__':
+    app.run(host="0.0.0.0", port=5000, debug=True)