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@@ -1,38 +1,38 @@
-# Use a smaller CUDA image (runtime, not devel)
-FROM pytorch/pytorch:1.11.0-cuda11.3-cudnn8-runtime
-
-# Install minimal system dependencies
-RUN apt-get update && apt-get install -y \
-    libglib2.0-0 \
-    libsm6 \
-    libxrender-dev \
-    libxext6 \
-    libgl1-mesa-glx \
-    git \
-    && apt-get clean \
-    && rm -rf /var/lib/apt/lists/*
-
-# Install mmcv using mim (official way)
-RUN pip install openmim
-RUN mim install mmengine
-RUN mim install mmcv==2.0.1
-
-# Install mmsegmentation from pip (not git)
-RUN pip install mmsegmentation==1.0.0
-
-# Install your app dependencies
-RUN pip install \
-    gradio==4.29.0 \
-    huggingface-hub==0.22.2 \
-    pillow==10.1.0 \
-    opencv-python-headless==4.8.1.78 \
-    ftfy==6.1.1 \
-    regex==2023.12.25
-
-WORKDIR /app
-COPY . .
-
-# Force CPU mode if CUDA not available
-ENV CUDA_VISIBLE_DEVICES=""
-
+# Use a smaller CUDA image (runtime, not devel)
+FROM pytorch/pytorch:1.11.0-cuda11.3-cudnn8-runtime
+
+# Install minimal system dependencies
+RUN apt-get update && apt-get install -y \
+    libglib2.0-0 \
+    libsm6 \
+    libxrender-dev \
+    libxext6 \
+    libgl1-mesa-glx \
+    git \
+    && apt-get clean \
+    && rm -rf /var/lib/apt/lists/*
+
+# Install mmcv using mim (official way)
+RUN pip install openmim
+RUN mim install mmengine
+RUN mim install mmcv==2.0.1
+
+# Install mmsegmentation from pip (not git)
+RUN pip install mmsegmentation==1.0.0
+
+# Install your app dependencies
+RUN pip install \
+    gradio==4.44.1 \
+    huggingface-hub==0.22.2 \
+    pillow==10.1.0 \
+    opencv-python-headless==4.8.1.78 \
+    ftfy==6.1.1 \
+    regex==2023.12.25
+
+WORKDIR /app
+COPY . .
+
+# Force CPU mode if CUDA not available
+ENV CUDA_VISIBLE_DEVICES=""
+
 CMD ["python", "app.py"]

app.py

@@ -265,6 +265,8 @@ body, .gradio-container { background: linear-gradient(180deg, #e7f3fb 0%, #d9eef
 /* Compact slider styling */
 .compact-slider { max-width: 320px; }
 .compact-slider .wrap { padding: 0 !important; }
+/* Remove component box chrome where undesired */
+.no-box .gr-box { box-shadow: none !important; border: none !important; background: transparent !important; padding: 0 !important; }
 /* Compact legend styling */
 .legend-box { width: 220px; max-height: 480px; overflow: auto; background: transparent; border: none; padding: 4px 4px; }
 """
@@ -286,13 +288,13 @@ with gr.Blocks(css=SEA_CSS) as demo:
 
     with gr.Row():
         inp = gr.Image(type="numpy", label="Input image", height=320)
-        mix = gr.Slider(0.0, 1.0, value=0.5, step=0.05, label="Segmentation mix (0=image, 1=seg)", container=False, elem_classes=["compact-slider"])
+        mix = gr.Slider(0.0, 1.0, value=0.5, step=0.05, label="Segmentation mix (0=image, 1=seg)", elem_classes=["compact-slider", "no-box"])
     if example_paths:
         gr.Examples(examples=example_paths, inputs=inp, label="Examples from ./images")
 
     with gr.Row():
         out = gr.Image(type="numpy", label="Segmentation overlay", height=512)
-        legend = gr.HTML(value="", elem_classes=["legend-box"], container=False)
+        legend = gr.HTML(value="", elem_classes=["legend-box", "no-box"]) 
     btn = gr.Button("Segment")
 
     # Hold last input image and segmentation RGB to re-blend without re-inference