Update app.py

app.py

@@ -3,7 +3,7 @@ import cv2
 import numpy as np
 import torch
 
-# Load the YOLOv7 model with force_reload to ensure fresh download
+# Load the YOLOv7 model
 model = torch.hub.load('WongKinYiu/yolov7', 'yolov7', force_reload=True)
 
 def detect_objects(image):
@@ -14,23 +14,6 @@ def detect_objects(image):
     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):
-    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)
@@ -43,22 +26,13 @@ def detect_live_objects(video):
 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)
+    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)
 
 # Launch the interface
 if __name__ == "__main__":
-    app.launch(debug=True)
+    app.launch()