Update app.py

app.py

@@ -1,23 +1,33 @@
-import gradio as gr
-from ultralytics import YOLO
-
-# Load the YOLO model
-model = YOLO('best.pt')
-
-def predict(img):
-
-    results = model(img)
-    annotated_frame = results[0].plot()
-    return annotated_frame
-
-# Create the Gradio interface
-iface = gr.Interface(
-    fn=predict,
-    inputs=gr.Image(label="Input Image", type="filepath"),
-    outputs="image",
-    title="Rat Paw Detector",
-    description="Upload an image to detect rat paws"
-)
-
-# Launch the Gradio interface
-iface.launch(share=True)
+import gradio as gr
+from ultralytics import YOLO
+
+# Load the YOLO model
+model = YOLO('best.pt')
+
+def predict(img, confidence_threshold):
+    # Perform inference
+    results = model(img)
+    
+    # Filter predictions based on the confidence threshold
+    # The results[0].boxes.data contains the detection results, including confidence scores
+    filtered_boxes = [box for box in results[0].boxes.data if box[4] >= confidence_threshold]
+    
+    # Plot the results (with the filtered detections)
+    annotated_frame = results[0].plot(labels=filtered_boxes)
+    
+    return annotated_frame
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=predict,
+    inputs=[
+        gr.Image(label="Input Image", type="filepath"),
+        gr.Slider(minimum=0, maximum=1, default=0.5, label="Confidence Threshold", step=0.01)
+    ],
+    outputs="image",
+    title="Coin Detector",
+    description="Upload an image to detect coins. Adjust the confidence threshold to filter results."
+)
+
+# Launch the Gradio interface
+iface.launch(share=True)