Create app.py

app.py

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+import gradio as gr
+import cv2
+import numpy as np
+import torch
+
+# Load the YOLOv7 model
+model = torch.hub.load('WongKinYiu/yolov7', 'yolov7')
+
+def detect_objects(image):
+    img = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+    results = model(img)  # Perform inference
+
+    # Process results
+    detections = results.xyxy[0].numpy()  # Get detections in xyxy format
+    annotated_image = image.copy()
+
+    for *box, conf, cls in detections:
+        # Draw bounding boxes on the image
+        x1, y1, x2, y2 = map(int, box)
+        cv2.rectangle(annotated_image, (x1, y1), (x2, y2), (255, 0, 0), 2)
+        label = f'{model.names[int(cls)]}: {conf:.2f}'
+        cv2.putText(annotated_image, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 0), 2)
+
+    return annotated_image
+
+def detect_live_objects(video):
+    # Capture frames from the video feed and process them
+    img = cv2.cvtColor(video, cv2.COLOR_RGB2BGR)
+    results = model(img)
+
+    # Process results
+    detections = results.xyxy[0].numpy()
+    annotated_image = video.copy()
+
+    for *box, conf, cls in detections:
+        x1, y1, x2, y2 = map(int, box)
+        cv2.rectangle(annotated_image, (x1, y1), (x2, y2), (255, 0, 0), 2)
+        label = f'{model.names[int(cls)]}: {conf:.2f}'
+        cv2.putText(annotated_image, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 0), 2)
+
+    return annotated_image
+
+# Create Gradio interface
+with gr.Blocks() as app:
+    gr.Markdown("# YOLOv7 Object Detection App")
+    
+    with gr.Tab("Image Classification"):
+        image_input = gr.Image(label="Upload Image", type="numpy")
+        output_image = gr.Image(label="Detected Objects", type="numpy")
+        
+        classify_button = gr.Button("Detect Objects")
+        
+        classify_button.click(fn=detect_objects, inputs=image_input, outputs=output_image)
+
+    with gr.Tab("Live Detection"):
+        video_input = gr.Video(label="Webcam Feed", type="numpy")
+        output_video = gr.Video(label="Live Detected Objects", type="numpy")
+
+        video_button = gr.Button("Start Live Detection")
+        
+        video_button.click(fn=detect_live_objects, inputs=video_input, outputs=output_video)
+
+# Launch the interface
+if __name__ == "__main__":
+    app.launch(debug=True)