Spaces:
Runtime error
Runtime error
fixed types for examples
Browse files- README.md +1 -1
- app.py +11 -7
- apps/infer.py +1 -1
README.md
CHANGED
@@ -5,7 +5,7 @@ emoji: 🤼
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colorFrom: indigo
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colorTo: yellow
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sdk: gradio
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sdk_version: 3.1.
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app_file: app.py
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pinned: true
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python_version: 3.8.13
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colorFrom: indigo
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colorTo: yellow
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sdk: gradio
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sdk_version: 3.1.4
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app_file: app.py
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pinned: true
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python_version: 3.8.13
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app.py
CHANGED
@@ -4,7 +4,7 @@
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import glob
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import gradio as gr
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import os
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import
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import subprocess
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@@ -16,7 +16,8 @@ if os.getenv('SYSTEM') == 'spaces':
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'pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html'.split())
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subprocess.run(
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'pip install https://download.is.tue.mpg.de/icon/HF/kaolin-0.11.0-cp38-cp38-linux_x86_64.whl'.split())
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subprocess.run(
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subprocess.run(
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'pip install git+https://github.com/Project-Splinter/human_det.git'.split())
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subprocess.run(
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@@ -93,10 +94,12 @@ def generate_image(seed, psi):
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return img
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random.seed(2022)
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model_types = ['ICON', 'PIFu', 'PaMIR']
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with gr.Blocks() as demo:
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gr.Markdown(description)
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@@ -119,11 +122,12 @@ with gr.Blocks() as demo:
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gr.Examples(examples=examples,
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inputs=[inp, radio_choice],
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cache_examples=
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fn=generate_model,
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outputs=out_lst)
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out_vid = gr.Video(
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out_vid_download = gr.File(
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label="Download Video, welcome share on Twitter with #ICON")
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import glob
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import gradio as gr
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import os
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import numpy as np
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import subprocess
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'pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html'.split())
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subprocess.run(
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'pip install https://download.is.tue.mpg.de/icon/HF/kaolin-0.11.0-cp38-cp38-linux_x86_64.whl'.split())
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subprocess.run(
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'pip install https://download.is.tue.mpg.de/icon/HF/pytorch3d-0.7.0-cp38-cp38-linux_x86_64.whl'.split())
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subprocess.run(
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'pip install git+https://github.com/Project-Splinter/human_det.git'.split())
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subprocess.run(
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return img
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model_types = ['ICON', 'PIFu', 'PaMIR']
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examples_names = glob.glob('examples/*.png')
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examples_types = np.random.choice(
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model_types, len(examples_names), p=[0.6, 0.2, 0.2])
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examples = [list(item) for item in zip(examples_names, examples_types)]
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with gr.Blocks() as demo:
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gr.Markdown(description)
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gr.Examples(examples=examples,
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inputs=[inp, radio_choice],
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cache_examples=False,
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fn=generate_model,
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outputs=out_lst)
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out_vid = gr.Video(
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label="Image + Normal + SMPL Body + Clothed Human")
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out_vid_download = gr.File(
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label="Download Video, welcome share on Twitter with #ICON")
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apps/infer.py
CHANGED
@@ -458,7 +458,7 @@ def generate_model(in_path, model_type):
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del locals()[element]
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gc.collect()
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torch.cuda.empty_cache()
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return [smpl_glb_path, smpl_obj_path,smpl_npy_path,
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refine_glb_path, refine_obj_path,
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video_path, video_path, overlap_path]
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del locals()[element]
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gc.collect()
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torch.cuda.empty_cache()
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return [smpl_glb_path, smpl_obj_path,smpl_npy_path,
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refine_glb_path, refine_obj_path,
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video_path, video_path, overlap_path]
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