Update the order of model options by the superiority and popularity of them.

app.py

@@ -74,12 +74,12 @@ class ImagePreprocessor():
 usage_to_weights_file = {
     'General': 'BiRefNet',
     'General-HR': 'BiRefNet_HR',
+    'Matting-HR': 'BiRefNet_HR-matting',
+    'Matting': 'BiRefNet-matting',
+    'Portrait': 'BiRefNet-portrait',
     'General-reso_512': 'BiRefNet-reso_512',
     'General-Lite': 'BiRefNet_lite',
     'General-Lite-2K': 'BiRefNet_lite-2K',
-    'Matting': 'BiRefNet-matting',
-    'Matting-HR': 'BiRefNet_HR-matting',
-    'Portrait': 'BiRefNet-portrait',
     'DIS': 'BiRefNet-DIS5K',
     'HRSOD': 'BiRefNet-HRSOD',
     'COD': 'BiRefNet-COD',
@@ -175,7 +175,11 @@ def predict(images, resolution, weights_file):
 examples = [[_] for _ in glob('examples/*')][:]
 # Add the option of resolution in a text box.
 for idx_example, example in enumerate(examples):
-    examples[idx_example].append('1024x1024')
+    if 'My_' in example_resolution:
+        example_resolution = '2048x2048'
+    else:
+        example_resolution = '1024x1024'
+    examples[idx_example].append(example_resolution)
 examples.append(examples[-1].copy())
 examples[-1][1] = '512x512'
 
@@ -212,7 +216,7 @@ tab_text = gr.Interface(
     ],
     outputs=ImageSlider(label="BiRefNet's prediction", type="pil"),
     examples=examples_url,
-    api_name="text",
+    api_name="URL",
     description=descriptions+'\nTab-URL is partially modified from https://huggingface.co/spaces/not-lain/background-removal, thanks to this great work!',
 )
 
@@ -230,8 +234,8 @@ tab_batch = gr.Interface(
 
 demo = gr.TabbedInterface(
     [tab_image, tab_text, tab_batch],
-    ['image', 'text', 'batch'],
-    title="BiRefNet demo for subject extraction (general / matting / salient / camouflaged / portrait).",
+    ['image', 'URL', 'batch'],
+    title="BiRefNet demo for subject extraction and background removal ([CAAI AIR'24] Bilateral Reference for High-Resolution Dichotomous Image Segmentation).",
 )
 
 if __name__ == "__main__":

app_local.py

@@ -74,12 +74,12 @@ class ImagePreprocessor():
 usage_to_weights_file = {
     'General': 'BiRefNet',
     'General-HR': 'BiRefNet_HR',
+    'Matting-HR': 'BiRefNet_HR-matting',
+    'Matting': 'BiRefNet-matting',
+    'Portrait': 'BiRefNet-portrait',
     'General-reso_512': 'BiRefNet-reso_512',
     'General-Lite': 'BiRefNet_lite',
     'General-Lite-2K': 'BiRefNet_lite-2K',
-    'Matting': 'BiRefNet-matting',
-    'Matting-HR': 'BiRefNet_HR-matting',
-    'Portrait': 'BiRefNet-portrait',
     'DIS': 'BiRefNet-DIS5K',
     'HRSOD': 'BiRefNet-HRSOD',
     'COD': 'BiRefNet-COD',
@@ -175,7 +175,11 @@ def predict(images, resolution, weights_file):
 examples = [[_] for _ in glob('examples/*')][:]
 # Add the option of resolution in a text box.
 for idx_example, example in enumerate(examples):
-    examples[idx_example].append('1024x1024')
+    if 'My_' in example_resolution:
+        example_resolution = '2048x2048'
+    else:
+        example_resolution = '1024x1024'
+    examples[idx_example].append(example_resolution)
 examples.append(examples[-1].copy())
 examples[-1][1] = '512x512'
 
@@ -212,7 +216,7 @@ tab_text = gr.Interface(
     ],
     outputs=gr.Image(label="BiRefNet's prediction", type="pil", format='png'),
     examples=examples_url,
-    api_name="text",
+    api_name="URL",
     description=descriptions+'\nTab-URL is partially modified from https://huggingface.co/spaces/not-lain/background-removal, thanks to this great work!',
 )
 
@@ -230,8 +234,8 @@ tab_batch = gr.Interface(
 
 demo = gr.TabbedInterface(
     [tab_image, tab_text, tab_batch],
-    ['image', 'text', 'batch'],
-    title="BiRefNet demo for subject extraction (general / matting / salient / camouflaged / portrait).",
+    ['image', 'URL', 'batch'],
+    title="BiRefNet demo for subject extraction and background removal ([CAAI AIR'24] Bilateral Reference for High-Resolution Dichotomous Image Segmentation).",
 )
 
 if __name__ == "__main__":