add a slider for threshold

app.py

@@ -16,7 +16,7 @@ output_layer_ir = compiled_model.output("boxes")
 ##### 
 #Inference
 ##### 
-def predict(img: np.ndarray) -> str:
+def predict(img: np.ndarray, threshold) -> str:
     # input: numpy array of image in RGB (see defaults for https://www.gradio.app/docs/#image)
 
     # Text detection models expect an image in BGR format.
@@ -34,7 +34,7 @@ def predict(img: np.ndarray) -> str:
     # Remove zero only boxes.
     boxes = boxes[~np.all(boxes == 0, axis=1)]
 
-    result = convert_result_to_image(image, resized_image, boxes, conf_labels=False)
+    result = convert_result_to_image(image, resized_image, boxes, threshold=threshold, conf_labels=False)
     
     #plt.figure(figsize=(10, 6))
     #plt.axis("off")
@@ -106,7 +106,10 @@ enable_queue=True
 
 gr.Interface(
     fn=predict,
-    inputs=gr.inputs.Image(),
+    inputs=[
+        gr.inputs.Image(),
+        gr.Slider(minimum=.1, maximum=1, value=.3)
+    ],
     outputs=gr.outputs.Image(type='filepath'),
     title=title,
     description=description,