Create app.py

app.py

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+import cv2
+import gradio as gr
+from transformers import pipeline
+
+# Load Hugging Face models
+pose_detection = pipeline("object-detection", model="./yolov8-pose")  # Local YOLOv8 pose model
+suspicious_activity_detection = pipeline("text-classification", model="./suspicious_activity_model")  # Local LSTM model
+
+# Function to process a single frame and predict suspicious activity
+def process_frame(frame):
+    """
+    Detect persons in the frame and determine if they exhibit suspicious behavior.
+    """
+    results = pose_detection(frame)
+
+    for person in results:
+        if person['label'] == 'person' and 'box' in person:
+            x1, y1, x2, y2 = map(int, person['box'].values())
+
+            if 'keypoints' in person:
+                keypoints = person['keypoints']
+                keypoints_input = " ".join(map(str, [kp for point in keypoints for kp in point[:2]]))
+
+                # Predict suspicious activity
+                prediction = suspicious_activity_detection(keypoints_input)[0]['label']
+                color = (0, 0, 255) if prediction == "Suspicious" else (0, 255, 0)
+                label = 'Suspicious' if prediction == "Suspicious" else 'Normal'
+
+                # Annotate frame
+                cv2.rectangle(frame, (x1, y1), (x2, y2), color, 2)
+                cv2.putText(frame, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
+            else:
+                print("No keypoints found for detected person.")
+    return frame
+
+# Gradio interface
+def live_detection(frame):
+    frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)  # Convert BGR to RGB for Gradio
+    processed_frame = process_frame(frame)
+    return cv2.cvtColor(processed_frame, cv2.COLOR_RGB2BGR)  # Convert back to BGR for display
+
+# Gradio UI
+interface = gr.Interface(
+    fn=live_detection,
+    inputs=gr.Image(source="webcam", tool="editor", type="numpy"),
+    outputs=gr.Image(type="numpy", label="Processed Video Stream"),
+    live=True,
+    description="Real-time Suspicious Activity Detection"
+)
+
+if __name__ == "__main__":
+    interface.launch(server_name="0.0.0.0", server_port=7860)