Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -25,14 +25,14 @@ def run_theia(image, pred_iou_thresh, stability_score_thresh):
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"LiheYoung/depth-anything-large-hf",
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]
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feature_means, feature_vars = load_feature_stats(target_model_names, stat_file_root="feature_stats")
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-
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mask_generator, sam_model = prepare_mask_generator('cuda')
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depth_anything_model_name = "LiheYoung/depth-anything-large-hf"
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depth_anything_decoder, _ = prepare_depth_decoder(depth_anything_model_name, 'cuda')
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image = torchvision.transforms.Resize(size=(224, 224))(image)
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images = [image]
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-
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theia_decode_results, gt_results = decode_everything(
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theia_model=theia_model,
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feature_means=feature_means,
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@@ -70,10 +70,13 @@ with gr.Blocks() as demo:
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with gr.Row():
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with gr.Column():
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input_image = gr.Image(label="Input Image", type="pil")
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submit_button = gr.Button("Submit")
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with gr.Column():
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dinov2_output = gr.Gallery(label="DINOv2", type="numpy")
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sam_output = gr.Gallery(label="SAM", type="numpy")
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"LiheYoung/depth-anything-large-hf",
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]
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feature_means, feature_vars = load_feature_stats(target_model_names, stat_file_root="feature_stats")
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+
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mask_generator, sam_model = prepare_mask_generator('cuda')
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depth_anything_model_name = "LiheYoung/depth-anything-large-hf"
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depth_anything_decoder, _ = prepare_depth_decoder(depth_anything_model_name, 'cuda')
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image = torchvision.transforms.Resize(size=(224, 224))(image)
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images = [image]
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+
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theia_decode_results, gt_results = decode_everything(
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theia_model=theia_model,
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feature_means=feature_means,
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with gr.Row():
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with gr.Column():
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input_image = gr.Image(label="Input Image", type="pil")
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+
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with gr.Accordion("Advanced Settings", open=False):
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pred_iou_thresh = gr.Slider(0.05, 0.95, step=0.05, value=0.5, label="SAM Pred IoU Thresh")
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stability_score_thresh = gr.Slider(0.05, 0.95, step=0.05, value=0.7, label="SAM Stability Score Thresh")
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submit_button = gr.Button("Submit")
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with gr.Column():
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dinov2_output = gr.Gallery(label="DINOv2", type="numpy")
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sam_output = gr.Gallery(label="SAM", type="numpy")
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