Add mode.

app.py

@@ -36,21 +36,24 @@ def run_inference(onnx_session, input_size, image):
     onnx_result = (onnx_result - min_value) / (max_value - min_value)
     onnx_result *= 255
     onnx_result = onnx_result.astype('uint8')
-    onnx_result[onnx_result >= 125] = 255
-    onnx_result[onnx_result < 125] = 0
 
     return onnx_result
 
 # Load model
 onnx_session = onnxruntime.InferenceSession("u2net.onnx")
 
-def create_rgba(image):
+def create_rgba(mode, image):
     out = run_inference(
         onnx_session,
         320,
         image,
     )
     resize_image = cv.resize(out, dsize=(image.shape[1], image.shape[0]))
+
+    if mode == "binary":
+        resize_image[resize_image > 255] = 255
+        resize_image[resize_image < 125] = 0
+
     mask = Image.fromarray(resize_image)
 
     rgba_image = Image.fromarray(image).convert('RGBA')
@@ -59,6 +62,6 @@ def create_rgba(image):
     return rgba_image
 
 css = ".output_image {height: 100% !important; width: 100% !important;}"
-inputs = gradio.inputs.Image()
+inputs = [gradio.inputs.Radio(["binary", "smooth"]), gradio.inputs.Image()]
 outputs = gradio.outputs.Image()
 gradio.Interface(fn=create_rgba, inputs=inputs, outputs=outputs, css=css).launch()