Spaces:
Running
on
Zero
Running
on
Zero
update gpu
Browse files
app.py
CHANGED
@@ -649,7 +649,7 @@ demo = gr.Interface(
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main_fn,
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[
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gr.Gallery(value=default_images, label="Select images", show_label=False, elem_id="images", columns=[3], rows=[1], object_fit="contain", height="auto", type="pil"),
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-
gr.Dropdown(["
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gr.Slider(0, 11, step=1, label="Layer", value=11, elem_id="layer", info="which layer of the image backbone features"),
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gr.Slider(1, 1000, step=1, label="Number of eigenvectors", value=100, elem_id="num_eig", info='increase for more object parts, decrease for whole object'),
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],
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@@ -657,7 +657,7 @@ demo = gr.Interface(
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additional_inputs=[
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gr.Dropdown(["attn", "mlp", "block"], label="Node type", value="block", elem_id="node_type", info="attn: attention output, mlp: mlp output, block: sum of residual stream"),
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gr.Slider(0.01, 1, step=0.01, label="Affinity focal gamma", value=0.3, elem_id="affinity_focal_gamma", info="decrease for more aggressive cleaning on the affinity matrix"),
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gr.Slider(100, 50000, step=100, label="num_sample (NCUT)", value=
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gr.Slider(1, 100, step=1, label="KNN (NCUT)", value=10, elem_id="knn_ncut", info="for Nyström approximation"),
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gr.Dropdown(["t-SNE", "UMAP"], label="Embedding method", value="t-SNE", elem_id="embedding_method"),
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gr.Slider(100, 1000, step=100, label="num_sample (t-SNE/UMAP)", value=300, elem_id="num_sample_tsne", info="for Nyström approximation. Adding will slow down quite a lot"),
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main_fn,
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[
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gr.Gallery(value=default_images, label="Select images", show_label=False, elem_id="images", columns=[3], rows=[1], object_fit="contain", height="auto", type="pil"),
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gr.Dropdown(["SAM(sam_vit_b)", "MobileSAM", "DiNO(dinov2_vitb14_reg)", "CLIP(openai/clip-vit-base-patch16)"], label="Model", value="SAM(sam_vit_b)", elem_id="model_name"),
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gr.Slider(0, 11, step=1, label="Layer", value=11, elem_id="layer", info="which layer of the image backbone features"),
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gr.Slider(1, 1000, step=1, label="Number of eigenvectors", value=100, elem_id="num_eig", info='increase for more object parts, decrease for whole object'),
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],
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additional_inputs=[
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gr.Dropdown(["attn", "mlp", "block"], label="Node type", value="block", elem_id="node_type", info="attn: attention output, mlp: mlp output, block: sum of residual stream"),
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gr.Slider(0.01, 1, step=0.01, label="Affinity focal gamma", value=0.3, elem_id="affinity_focal_gamma", info="decrease for more aggressive cleaning on the affinity matrix"),
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+
gr.Slider(100, 50000, step=100, label="num_sample (NCUT)", value=10000, elem_id="num_sample_ncut", info="for Nyström approximation"),
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gr.Slider(1, 100, step=1, label="KNN (NCUT)", value=10, elem_id="knn_ncut", info="for Nyström approximation"),
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gr.Dropdown(["t-SNE", "UMAP"], label="Embedding method", value="t-SNE", elem_id="embedding_method"),
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gr.Slider(100, 1000, step=100, label="num_sample (t-SNE/UMAP)", value=300, elem_id="num_sample_tsne", info="for Nyström approximation. Adding will slow down quite a lot"),
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