Spaces:
Running
on
Zero
Running
on
Zero
better api name
Browse files
app.py
CHANGED
@@ -10,7 +10,6 @@ if USE_HUGGINGFACE_SPACE: # huggingface ZeroGPU, dynamic GPU allocation
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USE_HUGGINGFACE_SPACE = False # run on local machine
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BATCH_SIZE = 1
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import os
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import gradio as gr
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import torch
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@@ -19,8 +18,7 @@ from PIL import Image
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import numpy as np
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import time
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import threading
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-
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import gradio as gr
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from backbone import extract_features, download_all_models, get_model
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from backbone import MODEL_DICT, LAYER_DICT, RES_DICT
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@@ -657,7 +655,8 @@ with demo:
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embedding_method_dropdown, num_sample_tsne_slider, knn_tsne_slider,
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perplexity_slider, n_neighbors_slider, min_dist_slider, sampling_method_dropdown
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],
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outputs=[output_gallery, logging_text]
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)
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with gr.Tab('NCut'):
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@@ -715,7 +714,8 @@ with demo:
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perplexity_slider, n_neighbors_slider, min_dist_slider, sampling_method_dropdown,
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old_school_ncut_checkbox
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],
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outputs=[output_gallery, logging_text]
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)
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with gr.Tab('Recursive Cut'):
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@@ -781,7 +781,8 @@ with demo:
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false_placeholder, number_placeholder, true_placeholder,
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l2_num_eig_slider, l3_num_eig_slider, metric_dropdown,
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],
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outputs=[l1_gallery, l2_gallery, l3_gallery, logging_text]
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)
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@@ -816,7 +817,8 @@ with demo:
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perplexity_slider, n_neighbors_slider, min_dist_slider, sampling_method_dropdown,
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place_holder_false, max_frame_number
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],
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outputs=[video_output_gallery, logging_text]
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)
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with gr.Tab('Text'):
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USE_HUGGINGFACE_SPACE = False # run on local machine
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BATCH_SIZE = 1
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import gradio as gr
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import torch
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import numpy as np
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import time
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import threading
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import os
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from backbone import extract_features, download_all_models, get_model
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from backbone import MODEL_DICT, LAYER_DICT, RES_DICT
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embedding_method_dropdown, num_sample_tsne_slider, knn_tsne_slider,
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perplexity_slider, n_neighbors_slider, min_dist_slider, sampling_method_dropdown
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],
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outputs=[output_gallery, logging_text],
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api_name="API_AlignedCut"
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)
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with gr.Tab('NCut'):
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perplexity_slider, n_neighbors_slider, min_dist_slider, sampling_method_dropdown,
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old_school_ncut_checkbox
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],
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outputs=[output_gallery, logging_text],
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api_name="API_NCut",
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)
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with gr.Tab('Recursive Cut'):
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false_placeholder, number_placeholder, true_placeholder,
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l2_num_eig_slider, l3_num_eig_slider, metric_dropdown,
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],
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outputs=[l1_gallery, l2_gallery, l3_gallery, logging_text],
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api_name="API_RecursiveCut"
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)
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perplexity_slider, n_neighbors_slider, min_dist_slider, sampling_method_dropdown,
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place_holder_false, max_frame_number
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],
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outputs=[video_output_gallery, logging_text],
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api_name="API_VideoCut",
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)
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with gr.Tab('Text'):
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