Update app.py

app.py

@@ -3,20 +3,20 @@ from ultralyticsplus import YOLO, render_result
 import cv2
 import torch
 
-# Verify torch version
-print(f"Using torch version: {torch.__version__}")
+# Check versions
+print(f"Torch version: {torch.__version__}")
+print(f"Ultralytics version: {YOLO.__version__}")
 
-# Load model with compatibility fix
+# Load model with safe serialization
 def load_model():
-    try:
-        model = YOLO('foduucom/plant-leaf-detection-and-classification')
-        model.overrides['conf'] = 0.25
-        model.overrides['iou'] = 0.45
-        model.overrides['agnostic_nms'] = False
-        model.overrides['max_det'] = 1000
-        return model
-    except Exception as e:
-        raise RuntimeError("Error loading model. Please check the requirements versions.") from e
+    model = YOLO('foduucom/plant-leaf-detection-and-classification')
+    model.overrides.update({
+        'conf': 0.25,
+        'iou': 0.45,
+        'agnostic_nms': False,
+        'max_det': 1000
+    })
+    return model
 
 model = load_model()
 
@@ -25,8 +25,8 @@ def detect_leaves(image):
     image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
     cv2.imwrite('temp_image.jpg', image)
     
-    # Perform prediction
-    results = model.predict('temp_image.jpg')
+    # Predict with numpy fix
+    results = model.predict(source='temp_image.jpg', imgsz=640)
     
     # Process results
     num_leaves = len(results[0].boxes)
@@ -34,23 +34,17 @@ def detect_leaves(image):
     
     return render, num_leaves
 
-# Create Gradio interface
-with gr.Blocks(theme=gr.themes.Soft(), title="Leaf Detection") as demo:
-    gr.Markdown("## 🍃 Plant Leaf Detection & Counter")
-    gr.Markdown("Upload a plant image to analyze leaf count and species")
-    
-    with gr.Row():
-        input_image = gr.Image(label="Input Image", type="numpy")
-        output_image = gr.Image(label="Detected Leaves", interactive=False)
-    
-    leaf_count = gr.Number(label="Total Leaves Detected", precision=0)
-    
-    submit_btn = gr.Button("Analyze Image", variant="primary")
-    submit_btn.click(
-        fn=detect_leaves,
-        inputs=[input_image],
-        outputs=[output_image, leaf_count]
-    )
+# Create simplified interface
+interface = gr.Interface(
+    fn=detect_leaves,
+    inputs=gr.Image(label="Upload Plant Image"),
+    outputs=[
+        gr.Image(label="Detection Result"),
+        gr.Number(label="Leaves Count")
+    ],
+    title="🍃 Plant Leaf Detector",
+    description="Upload a plant image to detect and count leaves"
+)
 
 if __name__ == "__main__":
-    demo.launch(server_port=7860, show_error=True)
+    interface.launch(server_port=7860)