output shape 600x600, different binarize

app.py

@@ -36,12 +36,7 @@ config['no_aug'] = True
 config['interpolation'] = 'bilinear'
 
 # Inference function
-def query_image(input_img, query, eval_threshold, crop_mode, crop_pct):
-
-    if eval_threshold == 0:
-        binarize = False
-    else:
-        binarize = True
+def query_image(input_img, query, binarize, eval_threshold, crop_mode, crop_pct):
 
     if crop_mode == 'center':
         crop_mode = None
@@ -101,10 +96,10 @@ the model will binarize each propability based on set eval_threshold.
 demo = gr.Interface(
     query_image, 
     #inputs=[gr.Image(), "text", "checkbox", gr.Slider(0, 1, value=0.25)],
-    inputs=[gr.Image(type='numpy', label='input_img').style(height=200, width=600), "text", gr.Slider(0, 1, value=0.25), 
+    inputs=[gr.Image(type='numpy', label='input_img').style(height=200, width=600), "text", "checkbox", gr.Slider(0, 1, value=0.25), 
             gr.Radio(["center", "squash", "border"], label='crop_mode'), gr.Slider(0, 1, value=1)],  
     #outputs="image",
-    outputs=gr.Image(type='numpy', label='output').style(height=600, width=600),
+    outputs=gr.Image(type='numpy', label='output').style(height=610, width=600),
     title="Object Detection Using Textual Queries",
     description=description,
     examples=[