Make the option of model and resolution available to both image and url inference tab.

app.py

@@ -121,7 +121,11 @@ tab_image = gr.Interface(
 
 tab_text = gr.Interface(
     fn=predict,
-    inputs=gr.Textbox(label="Paste an image URL"),
+    inputs=[
+        gr.Textbox(label="Paste an image URL"),
+        gr.Textbox(lines=1, placeholder="Type the resolution (`WxH`) you want, e.g., `1024x1024`. Higher resolutions can be much slower for inference.", label="Resolution"),
+        gr.Radio(list(usage_to_weights_file.keys()), value='General', label="Weights", info="Choose the weights you want.")
+    ]
     outputs=ImageSlider(label="BiRefNet's prediction", type="pil"),
     examples=["https://hips.hearstapps.com/hmg-prod/images/gettyimages-1229892983-square.jpg"],
     api_name="text"
@@ -130,7 +134,7 @@ tab_text = gr.Interface(
 demo = gr.TabbedInterface(
     [tab_image, tab_text],
     ["image", "text"],
-    title="BiRefNet demo for subject extraction (general / salient / camouflaged / portrait)."
+    title="BiRefNet demo for subject extraction (general / salient / camouflaged / portrait).",
     description=('Upload a picture, our model will extract a highly accurate segmentation of the subject in it.\n)'
                  ' The resolution used in our training was `1024x1024`, thus the suggested resolution to obtain good results!\n'
                  ' Our codes can be found at https://github.com/ZhengPeng7/BiRefNet.\n'