Update

.pre-commit-config.yaml

@@ -20,7 +20,7 @@ repos:
   - id: docformatter
     args: ['--in-place']
 - repo: https://github.com/pycqa/isort
-  rev: 5.10.1
+  rev: 5.12.0
   hooks:
     - id: isort
 - repo: https://github.com/pre-commit/mirrors-mypy

README.md

@@ -4,10 +4,11 @@ emoji: 🌍
 colorFrom: pink
 colorTo: pink
 sdk: gradio
-sdk_version: 3.16.2
+sdk_version: 3.36.1
 app_file: app.py
 pinned: false
 license: mit
+suggested_hardware: t4-small
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -1,5 +1,6 @@
 #!/usr/bin/env python
 
+import os
 import pathlib
 
 import gradio as gr
@@ -19,27 +20,37 @@ def run(image_path, threshold, max_num_mask):
     return image
 
 
-TITLE = 'MaskCut'
-DESCRIPTION = 'This is an unofficial demo for https://github.com/facebookresearch/CutLER.'
+DESCRIPTION = '# [MaskCut](https://github.com/facebookresearch/CutLER)'
 
 paths = sorted(pathlib.Path('CutLER/maskcut/imgs').glob('*.jpg'))
-demo = gr.Interface(
-    fn=run,
-    inputs=[
-        gr.Image(label='Input image', type='filepath'),
-        gr.Slider(label='Threshold used for producing binary graph',
-                  minimum=0,
-                  maximum=1,
-                  value=0.15,
-                  step=0.01),
-        gr.Slider(label='The maximum number of pseudo-masks per image',
-                  minimum=1,
-                  maximum=20,
-                  value=6,
-                  step=1),
-    ],
-    outputs=gr.Image(label='Result', type='numpy'),
-    examples=[[path.as_posix(), 0.15, 6] for path in paths],
-    title=TITLE,
-    description=DESCRIPTION)
-demo.queue().launch()
+
+with gr.Blocks(css='style.css') as demo:
+    gr.Markdown(DESCRIPTION)
+    with gr.Row():
+        with gr.Column():
+            image = gr.Image(label='Input image', type='filepath')
+            threshold = gr.Slider(
+                label='Threshold used for producing binary graph',
+                minimum=0,
+                maximum=1,
+                step=0.01,
+                value=0.15)
+            max_masks = gr.Slider(
+                label='The maximum number of pseudo-masks per image',
+                minimum=1,
+                maximum=20,
+                step=1,
+                value=6)
+            run_button = gr.Button('Run')
+        with gr.Column():
+            result = gr.Image(label='Result')
+
+    inputs = [image, threshold, max_masks]
+    gr.Examples(examples=[[path.as_posix(), 0.15, 6] for path in paths],
+                inputs=inputs,
+                outputs=result,
+                fn=run,
+                cache_examples=os.getenv('CACHE_EXAMPLES') == '1')
+
+    run_button.click(fn=run, inputs=inputs, outputs=result, api_name='run')
+demo.queue(max_size=20).launch()

requirements.txt

@@ -1,9 +1,9 @@
 git+https://github.com/lucasb-eyer/pydensecrf@0d53acb
-gradio==3.16.2
+gradio==3.36.1
 numpy==1.23.5
-opencv-python==4.6.0.66
+opencv-python==4.8.0.74
 pycocotools==2.0.6
 scikit-image==0.19.2
 torch==1.13.1
 torchvision==0.14.1
-tqdm==4.64.1
+tqdm==4.65.0

style.css

@@ -0,0 +1,3 @@
+h1 {
+  text-align: center;
+}