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app.py

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+import gradio as gr
+import torch
+import numpy as np
+import cv2
+import os
+import tempfile
+from pathlib import Path
+from ultralytics import YOLO
+
+# Load the YOLO model
+model_path = Path(__file__).parent / "best.pt"
+model = YOLO(model_path)
+
+def process_video(video_path):
+    """
+    Process a video with the YOLO model and return the processed video path
+    """
+    if not video_path:
+        return None
+    
+    # Create temporary file for output
+    temp_output_path = tempfile.NamedTemporaryFile(suffix='.mp4', delete=False).name
+    
+    # Process video with YOLO
+    cap = cv2.VideoCapture(video_path)
+    width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+    fps = int(cap.get(cv2.CAP_PROP_FPS))
+    
+    # Define codec and create VideoWriter object
+    output = cv2.VideoWriter(
+        temp_output_path, 
+        cv2.VideoWriter_fourcc(*'mp4v'), 
+        fps, 
+        (width, height)
+    )
+    
+    # Process each frame
+    while cap.isOpened():
+        ret, frame = cap.read()
+        if not ret:
+            break
+            
+        # Run YOLOv8 inference on the frame
+        results = model(frame)
+        
+        # Visualize the results on the frame
+        annotated_frame = results[0].plot()
+        
+        # Write the frame to the output video
+        output.write(annotated_frame)
+        
+    # Release resources
+    cap.release()
+    output.release()
+    
+    return temp_output_path
+
+# Create the Gradio interface
+with gr.Blocks() as app:
+    gr.Markdown("# Vehicle Detection with YOLOv12")
+    gr.Markdown("Upload a video and click 'Submit' to detect vehicles using a fine-tuned YOLOv12 model.")
+    
+    with gr.Row():
+        input_video = gr.Video(label="Upload Video")
+        output_video = gr.Video(label="Processed Video")
+    
+    submit_btn = gr.Button("Submit")
+    submit_btn.click(
+        fn=process_video,
+        inputs=[input_video],
+        outputs=[output_video]
+    )
+
+if __name__ == "__main__":
+    app.launch()

best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f6f009561338788061ccc2da8817872cc324e5a044a1d2e7a9dc43d96e844fac
+size 5544083

requirements.txt

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+gradio>=4.0.0
+torch>=2.0.0
+opencv-python>=4.5.0
+numpy>=1.22.0
+ultralytics>=8.0.0