Update README and release inference code

README.md

@@ -4,7 +4,7 @@ emoji: 📸🚀🌟
 colorFrom: red
 colorTo: yellow
 sdk: gradio
-sdk_version: 3.40.0
+sdk_version: 3.40.1
 app_file: app.py
 pinned: true
 license: mit
@@ -12,10 +12,29 @@ license: mit
 
 # One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimization
 
-Paper: https://arxiv.org/abs/2306.16928
-Code: https://github.com/One-2-3-45/One-2-3-45
+<div>
+<a style="display:inline-block" href="http://one-2-3-45.com"><img src="https://img.shields.io/badge/Project_Homepage-f9f7f7?logo=data:image/webp;base64,UklGRmIRAABXRUJQVlA4IFYRAABQPwCdASrIAMgAPm00lEekpiolqDvpMIANiWJu3pE7maI+vTDkhN5f7PfmGT7nS6p8nKBr0I+YBzr/ML+2/rG/8j1Sf3/1AP6v/sOsW/bn2GP2W9Zv/zeyf/cf+Z+63tReoB/6uCx2p5E/iUkPwG1FO9t/XgHPL7RH7TzI8EvEA4Mr1T2CP0J6xH+d5J/rz2F/LG9h37l+x9+4xQ3m86D2Te/zeVV/tWyTw7s85XZ0ABD4N2CpzWHt8feKiWkqdTkRjojREWrbUDAKXlYsV7EGU9rWR2gCxVXnstqpNVhwra603swvYRlMyRzKc5nJHEEeLuV8EDee/MpPVIq2DNUcXpCZXvFLHgXBWvZWzSZCFo4iub8df+Yu9q7rw5qemOe2Nt1IIoyjBmXdjCunMherehhPjQIQGiI6PDcriy/zhhwHE7O+0gmpUsYmcDR+ixOfLPY0yjnQosZkIoK1pfttDGtirMbSMqndDVi73JMxcSlNb0MNFtgdAAXNk5Z77wgsPz9RRj9oWO/KRpXn5ra4gUt+mMgSCvFG86zgghSehTRD54z10sNxqnG3/rpKDifOvT4EQU1uA9ZckUZcUt5L5C0+dOdj1I56uLJEAsn0432gHD5wRG7dgSfYusXvhGl2uMaczlXSJ0JfX+Z0e9q7sHywvyEkWC+iJREwvtWi1K+NQAD+/JSRhGP+QTeW9xU73vXKZO+JaR/TAb6vV9dNzIjket6jYZdxK0qCcaf95QeouegLeSQL/9WeH5l2/DE2AKdYjhEYzzIefp7c6cTfM3D3q3kSFxAF/xP/f/3YUFjjOzfzl5xrD3XaWz0TAehn6+ze5pANq6t5GDX8ZOfpIBGUplJj6UZXd76ropLkDdM+d/F2Megl53hry7QvtcUGNlKgjLd7/txvzvkYIPre5sKVvAJzj9DEml706Piekk2NTtBnCMQtQAPO7/Soo3p3QbqLnMIY2PKCq3jFUkeMDAB6uvaHy7e8G/yi+LlFCfYgju+h+ha+jj6NYh6xUx/9TpQoQ1VFrpEw7pCAaQ2NbzVcj/EfBLQUWQBwliZd6FG70L3ATK7AS/cu+Pm/ASndDhIDTx08uveDvY2kW7Mqproq8D4ImWzJ7ZwM8JfrvyN9/wh0Iu00O3UbTDU58dYfWzxI1gDb2Yt6+AyvgjRY/WUM8aikx5MTFi6ZEWeffMc8ruwWeKmfwJtpDxNYhJgSN5gZoOS+XedZmwoYfiuaf9hhPdDtJCM429liA9mZQ2GNfMOPtcLJV/4xTUuWJx4/d43remtcIdsy1GlD79SNNSlfWuSCF8LIopGEcQwZnBVOBmJ7O2bQvBHNAQ6dlz+Pc8zL7MgsN7uff5PDGyXHqV4lCh2Q/xbeZaYVv1agSO4QU5FvEX/6AQpNxQqgtvrXM+XsXTWYJpiO7+ucPvPudldDswT7/ITpp7AdSJ9OjPYr3cMRBVy5sXXkyY8SVv0z//QqGJbxMA3IV81dfN5dUNNlMvl+EBv6Qrnq42ZAEXMEbW/zcmuvIO+539I0BKM+COuGTuEmhulQBlMmdlBNVaII5lFuENjHGpIPNULKARA/PhM9jOvRG2xs8SFCjLZ9ZNLyWznJxq3sZWeGUNXcyJPKDr3WAWCmP8tNyjKQk6aKOD1s/+2MCNQ9b4Zb2XJJLW4kBOS6P10n42Scz8D1K6GTeouELbGApoVNEYjw2jdbNqsNLZiJi6XfSs7Kz5ozupOLJsYOzfLQTjDz7BZOzEYFoB+acySl5Qs3mO84Mw6pIb9MqHhzFqtmrsD4V6uwssP9SUvJTMA4orRWZAMdCA9lMHQi6XBPR9CBidQdudyeYtUj5gWMyzdcSkG8l/2zbzpz8THi23y/8+Ijg5naj6GtYnpJna+6QpI6dlY+E2KF7bOK2ctKwBjClUvAjHXa1162i6DsToHLQE4stmDJdvI1POb9Hj0Mq+azo1wrOfqVFcAS5XNc37IJeYBs/cQYZ08mg2vXWWJYVWz648jTHABHf+LiHsy4WRaVo4oOOSyeampoUYSM9WUJ3iOlTMis5U2DCrGoAiATOAyyuwMcYgTni5FGSpdE5BnoS6ORUiYapPetM/XmsvikTkKNn4z4jhiLFFcU+bH1pZ2DseVK9vCgY5s9ZDjNb9Ky+8fwn9dJtsZ6M7opvXhqde9Ljos6KWQ/8hj3pswa2lLZ7WRc9xaxTjq1sytCxfOd+J+VrsXedNuuYDMwumYIzF1Xsbz1VCURDw6C1twAPizF49s4JfToWsGhgG4wtBE5NAU4KvnGleFGzv54AwBR9qqPVD9bcN7ZmZhphTcAGnR2oOcvT98FmknnVXqJYdHSeP9nWG6A8YUUgDmy7rYLtbxgpid5ysrxvLeyMOeTaQXuNZXn5kQeqDGELMfQ5U2PAk+/DhnbWTsirG5NAP0tgGbSNGM5cv9+trgSk6sXdw1lZOLrfqLGZ8Dt19DWcxmjsbDU30CoSc1alYxX5G+uIHy72tQxjzsot1O4iZeNO34PItzBoeg0Fq+YQZGsHdknwJkAbffRl96xFsDxM6l4g22OaMEHxLMC9uFFE8Ee/xf+krkjv7YCfJrCM3Nw6xfyrhtxN3x2GxSg4YTu2dtjb3zVI/6jYNwgGiaDWoh5I29uQ8ZvES8Ros5jgxDzeKB1tJ3HtDM9SFGNJfQiLiSyYZQLBjCcGbi3+vlythB3k6af+P5rDqah2oPFl29Ngnw/tmpkmRIvri5i55FPeY9J4nXfvWYHTHdoB0oVA2NEk2nropP+T7GXhAxA2NgyGtzHaVU2yxiSju87w8MLIo1eac26wOnbEo/oD6Zcb8vyu0x7ug9iERQ5FlppDnIktT6QC6Kk3qBxovLzOPdEvYQoytaN256n2dmkxAaq78klv6PnU7HiH3e/I9RC27VOP0j6JDW19KvC9/uN9tfOi6WMr0IGKpTsZAUZXm+Ukyk/Rpu9ZPIH5/3CL+yfj3ROts+BWIZNj8lpFHfmYhmN/J0+/lDIGmbRVMbvmif9tqr53fqb8EkFpdMHnK8jc0oIYu2Io5SWOzHc7GMdwt5RB8LR5jUjV6Xv+rR7N4IcTQRphe7WarFsxHmihpNr8sLroqsVxBH+6dOjC5DPhRV6aJB9ZB0NjpLtbjRsEKe1By1huo8rJa+DS73fTUfxWPaJjQsasBOcc6xwuob3OBjTFjUOxfiBbhMDNUFcamlMphrkbmTe2smHz0hrScXZjoHxphV537e8PNenBpI//N58bUOcmV4Lo1H1BLLjNTw1gK+rKFgaU/WOZQ0DZ1kRRqCa86XYnFposmkLgDNooS/yeW/RGfvopRDH40d2TeW8t1+2fDHQcwocSXolq+dxC6JMGsu2rCrhdjzhqd1KPMp5EVGQuCyLc8LfjUhQ8fSs63P9aVDYZBDhO8oWSI2Lbk7cRpKJ38ww9dD0b0OjvucHkJl1zIwyQFqKKEfIN7RPvV8Q1Xxot6Y5f8/UqOCOVZRt+IM1JFcJ4AstPMOXs9hAyZzEs1EY9lv3976/18LNNvL8K7RPNH1uz3qwAajMXLaOTEK7IzCjex3YZQ0LCICPzWVKMNbkSFpmy5ow1A54fK4F45T0apL1FE8dc/Jy6ERymiJ8ZvT+BJHUtbS5oB72w8NeIb0zTuqTzYwMQiKeCI+DlJTd6R3dgbvDETb7XtLT1L5quVxBiyJLxgARoeWU1DY3eWTFJkicFp/UqIFCYgLUhQgGm/1gAxylWf4wZmbQy6RGlY3/pfn5qxqFq8Xmza7Unght3AckydGZ6u6yWcooxZwILsHaklA/Bu2HRlCLzLer57IQWfvHUjJ8pqEoZ/TE0WqZc4SF6CBVC4KGEIqyPnH/+chaIQRfGuKg0rKAAc5tB+7vGl4ck72A+dA9iW0UUwXqD6Y333q9MEdov8hbXuiRkRMv1CEm0h1N8yhxOEe1SLWxlCmvUHcVvhojM6S4ODYr2rxHxOqx63MVVCk6PpQAB2gn4D/9+QHVBBqAxLV8Pggh6aRlEmPuHNEc+b/1Zqh4lvwxUgyMFngOgTAhqZAZqBpRRD41KfU7wEbzruYQhOIxxPMbGIe93LRFgYZLz21sLmS/02JhQ1eY6cSu/iumOWleWujzjCcB9qxDpOBlsugpiveHwunOO9Lu66uGNeKuw6Aqo+zTcdEX+BOlserNtSeyYmhQrwLA+mnEqaAtKv5eAyTC03krdlSEI+++xVMU+kqsGF+6H9yNBQj5aZxmOzd7BejBdBBInEjlj868zR80jlgVKb+yQ7XkdiFIvQl/XvaFpPGqYb4UR70U0jNe/I9UuFggu8M90wyOi7Ihm3t9FZTBPv4zmee4ue5pVKpdsOOZLwBSODTdpUJb6ctU3I9n0KAUBM4+RkNoQzCyb+iXoXl22CL2eQWlOlBi8IG84Y2bMIiLnPs5qeUth9zlniN14oQNTtVJibuIgkylT50ExHyuqz1ra2+wW3QDltErT6yyrKnL8rmkPesI3aPAL880z4U6TWXqcU6hkryL8W5gdI94KYuDTBEim0GM6IAAKf8JZNX3sM/OIB9h3XbFUuNXRocJY9iqQAGdinm3YPLbRBxP5S5EWwlTdIVK5yjUpV+tCN0HXOVf7xj9pnyIMPDz/Znf4zufz+0zonywFQLgAdKiVwC5a6EDC2rmxYC4L82QIO17SKc8NCAJZPTWwwrPGgb0nhQdi3g32QzHUAqE2qhq2jyM7WINI34P28PN5IE50uRx/XFn2a8h2Qgla55PnsIT7KbDBo0Nd4XUkCWINxReQK0/NZEDZrUuZghyZYnnIuIi0pTpecJWliTLvfxyiRkIsb9t2mT6VzM8H2HN8nq0rF7BC27r0JoLl/5YgZQZmw763cQ625wkmPOX0vr1M35fZYv06zKm1ux/L+W6O3ju3VdFudKgEgRIeT+bIOQKoKaT+knRugmPDGt1JAt6bKTT2bvIYnf5OvZs9id5x+qy5UeotL3uxYiBj7SyGxTCHdovbak2BG5hGmuVWxRojEJS9IEqUKwy133zg24keiFy0bXsG125D1XgQ/uI3IM8dijJ4N6jHObWneJl3zHvKb+cX97XFAv5VV5ySEfm0Iglkir9QaTOXP9SuTeCao7Q3fULO6Jcp+sOU6x+jCjlsmHiF7oDCAb/RYITB9oIcAGGQJkT6ccTNJPlyPiNf4/nefe5V4j5RWLTDm7Wb/kt426CIGzE2ekBjrvExlch914MGYjMJcBllUj/LTfXTYLSqPwPzU/xBVSUOR9o7wFnFBZTaI0ApgY11rRsoEgTu9yRgBxw0h71O/RjpN5Ku/U/er87C9/jHzucfXpRDcP1JxOOxoJziSE01YxnPjmyDigmCcur63bY/xXdZeNQNprWvE3mAIP14fFkdJ4+0vwkAP+BXokPPQBkZuEWFAUEz1H/YQf4Q9bCQZXl/WSpUpG/TjBo8EpZLTJ2Jwa1G3H2hVIUlifUnV/SvKDYbpUvl6mKuwdgglJxkJOXjtf84FjvjeHUOzf8ZhLw3PH53rUrDz0INySaGJ/n4a/iuvLMaL146Ii98kND4sM0nElTIxnJe+LJF/8aimynAAiTshwnKc7MHqCtuDaUFfEQCGw0tmys5yKZM5zzawr6LW7MdQs9XUDiyTrX+YcI0uPZZ43oMnO737u5Tmc/sAeKCNGIWt8kw87EMQ+BP5NMrf8b8wDvSD2XVEZu7xqwNCizeSYQJGVJVSAdJ27XwXrFfHtdHHrlojW+3BFzE5rOzDsUsA00zYHxt+e9zo9Yn0sImcxGhbDFBGD892Rgz9G+eor3huRF8h4p1qYpjTe/ykVkhWyvHRjNNevOV7Gk1jhgiwOajzrXwNsIJNUvAQQB017GRYgey7MAEeBoAx5RuxYU+oMH6DNk5eYcrJDxo48XGbO4QhCMRgAA"></a>
+<a style="display:inline-block; margin-left: .5em" href="https://arxiv.org/abs/2306.16928"><img src="https://img.shields.io/badge/2306.16928-f9f7f7?logo=data:image/png;base64,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"></a>
+<a style="display:inline-block; margin-left: .5em" href='https://github.com/One-2-3-45/One-2-3-45'><img src='https://img.shields.io/github/stars/One-2-3-45/One-2-3-45?style=social' /></a>
+</div>
 
-## BibTeX
+
+This space hosts the demo for [One-2-3-45](http://One-2-3-45.com), powered by the [inference model](https://huggingface.co/One-2-3-45/code).
+
+Please refer to our [GitHub repo](https://github.com/One-2-3-45/One-2-3-45) for full code release.
+
+## Local Deployment of the Demo
+```bash
+# Minimum GPU: NVIDIA A10 or RTX 3090
+# 1. Install the requirements
+sudo apt-get install libsparsehash-dev
+pip install -r requirements.txt
+
+# 2. Run the demo
+python app.py
+```
+
+## Citation
 
 ```bibtex
 @misc{liu2023one2345,

app.py

@@ -3,26 +3,25 @@ from huggingface_hub import snapshot_download
 
 is_local_run = False
 
-code_dir = snapshot_download("One-2-3-45/code", token=os.environ['TOKEN']) if not is_local_run else "../code"
+code_dir = snapshot_download("One-2-3-45/code") if not is_local_run else "../code" # , token=os.environ['TOKEN']
 
 sys.path.append(code_dir)
 
-elev_est_dir = os.path.join(code_dir, "one2345_elev_est/")
+elev_est_dir = os.path.abspath(os.path.join(code_dir, "one2345_elev_est"))
 sys.path.append(elev_est_dir)
 
 if not is_local_run:
-    import subprocess
-    subprocess.run(["sh", os.path.join(elev_est_dir, "install.sh")], cwd=elev_est_dir)
+    import pip
+    pip.main(['install', elev_est_dir])
     # export TORCH_CUDA_ARCH_LIST="7.0;7.2;8.0;8.6"
     # export IABN_FORCE_CUDA=1
     os.environ["TORCH_CUDA_ARCH_LIST"] = "8.0;8.6"
     os.environ["IABN_FORCE_CUDA"] = "1"
     os.environ["FORCE_CUDA"] = "1"
-    subprocess.run(["pip", "install", "inplace_abn"]) 
+    pip.main(["install", "inplace_abn"]) 
     # FORCE_CUDA=1 pip install --no-cache-dir git+https://github.com/mit-han-lab/torchsparse.git@v1.4.0
-    subprocess.run(["pip", "install", "--no-cache-dir", "git+https://github.com/mit-han-lab/torchsparse.git@v1.4.0"])
+    pip.main(["install", "--no-cache-dir", "git+https://github.com/mit-han-lab/torchsparse.git@v1.4.0"])
 
-import inspect
 import shutil
 import torch
 import fire
@@ -61,7 +60,7 @@ _BBOX_2 = "Bounding box adjusted. Continue adjusting or **Run Generation**."
 _BBOX_3 = "Bounding box predicted. Adjust it using sliders or **Run Generation**."
 _SAM = "Preprocessing the input image... (safety check, SAM segmentation, *etc*.)"
 _GEN_1 = "Predicting multi-view images... (may take \~13 seconds) <br> Images will be shown in the bottom right blocks."
-_GEN_2 = "Predicting nearby views and generating mesh... (may take \~35 seconds) <br> Mesh will be shown on the right."
+_GEN_2 = "Predicting nearby views and generating mesh... (may take \~33 seconds) <br> Mesh will be shown on the right."
 _DONE = "Done! Mesh is shown on the right. <br> If it is not satisfactory, please select **Retry view** checkboxes for inaccurate views and click **Regenerate selected view(s)** at the bottom."
 _REGEN_1 = "Selected view(s) are regenerated. You can click **Regenerate nearby views and mesh**. <br> Alternatively, if the regenerated view(s) are still not satisfactory, you can repeat the previous step (select the view and regenerate)."
 _REGEN_2 = "Regeneration done. Mesh is shown on the right."
@@ -361,8 +360,7 @@ def stage2_run(models, device, tmp_dir,
         zero123_infer(model, tmp_dir, indices=rerun_all, device=device, ddim_steps=stage2_steps, scale=scale)
     
     dataset = tmp_dir
-    main_dir_path = os.path.dirname(os.path.abspath(
-            inspect.getfile(inspect.currentframe())))
+    main_dir_path = os.path.dirname(__file__)
     torch.cuda.empty_cache()
     os.chdir(os.path.join(code_dir, 'SparseNeuS_demo_v1/'))
 

pre-requirements.txt

@@ -1,67 +0,0 @@
---extra-index-url https://download.pytorch.org/whl/cu118
-torch>=2.0.0
-torchvision>=0.13.1
-albumentations>=0.4.3
-opencv-python>=4.5.5.64
-pudb>=2019.2
-imageio>=2.9.0
-imageio-ffmpeg>=0.4.2
-pytorch-lightning>=1.4.2
-omegaconf>=2.1.1
-test-tube>=0.7.5
-streamlit>=0.73.1
-einops>=0.3.0
-torch-fidelity>=0.3.0
-transformers>=4.22.2
-kornia>=0.6
-webdataset>=0.2.5
-torchmetrics>=0.6.0
-fire>=0.4.0
-gradio>=3.21.0
-diffusers>=0.12.1
-datasets[vision]>=2.4.0
-carvekit-colab>=4.1.0
-rich>=13.3.2
-plotly>=5.13.1
--e git+https://github.com/CompVis/taming-transformers.git#egg=taming-transformers
-# elev est
-dl_ext
-easydict
-glumpy
-gym
-h5py
-loguru
-matplotlib
-# mplib
-multipledispatch
-open3d
-packaging
-Pillow
-pycocotools
-motion-planning
-pyrender
-PyYAML
-scikit_image
-scikit_learn
-scipy
-screeninfo
-setuptools
-tensorboardX
-termcolor
-tqdm
-transforms3d
-trimesh
-yacs
-# zarr
-# sapien
-pyglet==1.5.27
-# wis3d
-gdown
-git+https://github.com/NVlabs/nvdiffrast.git
-git+https://github.com/openai/CLIP.git
-# segment anything
-onnxruntime 
-onnx
-git+https://github.com/facebookresearch/segment-anything.git
-# rembg
-rembg

requirements.txt

@@ -1,6 +1,67 @@
+--extra-index-url https://download.pytorch.org/whl/cu118
+numpy
+torch>=2.0.0
+torchvision
+albumentations>=0.4.3
+opencv-python>=4.5.5.64
+pudb>=2019.2
+imageio>=2.9.0
+imageio-ffmpeg>=0.4.2
+pytorch-lightning>=1.4.2
+omegaconf>=2.1.1
+test-tube>=0.7.5
+streamlit>=0.73.1
+einops>=0.3.0
+torch-fidelity>=0.3.0
+transformers>=4.22.2
+kornia>=0.6
+webdataset>=0.2.5
+torchmetrics>=0.6.0
+fire>=0.4.0
+gradio>=3.40.1
+diffusers>=0.12.1
+datasets[vision]>=2.4.0
+carvekit-colab>=4.1.0
+rich>=13.3.2
+plotly>=5.13.1
+-e git+https://github.com/CompVis/taming-transformers.git#egg=taming-transformers
+# elev est
+dl_ext
+easydict
+glumpy
+gym
+h5py
+loguru
+matplotlib
+# mplib
+multipledispatch
+packaging
+Pillow
+pycocotools
+motion-planning
+pyrender
+PyYAML
+scikit_image
+scikit_learn
+scipy
+screeninfo
+setuptools
+tensorboardX
+tqdm
+transforms3d
+trimesh
+yacs
+gdown
+git+https://github.com/NVlabs/nvdiffrast.git
+git+https://github.com/openai/CLIP.git
+# segment anything
+onnxruntime 
+onnx
+git+https://github.com/facebookresearch/segment-anything.git
+# rembg
+rembg
 # sparseneus
 # -e git+https://github.com/mit-han-lab/torchsparse.git@v1.4.0#egg=torchsparse
-numpy
 pyhocon
 icecream
 PyMCubes