From d6cc8e1e6713a2129683496b328bde675a66370d Mon Sep 17 00:00:00 2001 From: fabio-sim <54187389+fabio-sim@users.noreply.github.com> Date: Mon, 22 Jan 2024 21:53:11 +0700 Subject: [PATCH] Initial commit --- .gitignore | 4 + LICENSE | 2 +- README.md | 82 +++ assets/DSC_0410.JPG | Bin 0 -> 391451 bytes assets/latency.png | Bin 0 -> 95276 bytes assets/sacre_coeur1.jpg | Bin 0 -> 201537 bytes assets/sacre_coeur2.jpg | Bin 0 -> 259462 bytes assets/sample.png | Bin 0 -> 978260 bytes depth_anything/blocks.py | 204 ++++++ depth_anything/dpt.py | 226 +++++++ depth_anything/util/transform.py | 273 ++++++++ eval.py | 175 +++++ export.py | 87 +++ infer.py | 87 +++ requirements.txt | 7 + torchhub/README.md | 3 + .../CODE_OF_CONDUCT.md | 80 +++ .../CONTRIBUTING.md | 31 + torchhub/facebookresearch_dinov2_main/LICENSE | 203 ++++++ .../MODEL_CARD.md | 201 ++++++ .../facebookresearch_dinov2_main/README.md | 277 ++++++++ .../facebookresearch_dinov2_main/conda.yaml | 22 + .../dinov2/__init__.py | 7 + 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.../vision_transformer.py | 439 ++++++++++++ weights/.gitkeep | 1 + weights/download.sh | 7 + 97 files changed, 9940 insertions(+), 1 deletion(-) create mode 100644 README.md create mode 100755 assets/DSC_0410.JPG create mode 100644 assets/latency.png create mode 100644 assets/sacre_coeur1.jpg create mode 100644 assets/sacre_coeur2.jpg create mode 100644 assets/sample.png create mode 100644 depth_anything/blocks.py create mode 100644 depth_anything/dpt.py create mode 100644 depth_anything/util/transform.py create mode 100644 eval.py create mode 100644 export.py create mode 100644 infer.py create mode 100644 requirements.txt create mode 100644 torchhub/README.md create mode 100644 torchhub/facebookresearch_dinov2_main/CODE_OF_CONDUCT.md create mode 100644 torchhub/facebookresearch_dinov2_main/CONTRIBUTING.md create mode 100644 torchhub/facebookresearch_dinov2_main/LICENSE create mode 100644 torchhub/facebookresearch_dinov2_main/MODEL_CARD.md create mode 100644 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torchhub/facebookresearch_dinov2_main/scripts/lint.sh create mode 100644 torchhub/facebookresearch_dinov2_main/setup.cfg create mode 100644 torchhub/facebookresearch_dinov2_main/setup.py create mode 100644 torchhub/facebookresearch_dinov2_main/utils.py create mode 100644 torchhub/facebookresearch_dinov2_main/vision_transformer.py create mode 100644 weights/.gitkeep create mode 100644 weights/download.sh diff --git a/.gitignore b/.gitignore index 68bc17f..7a57f7d 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,7 @@ +.vscode +*.onnx +megadepth_test_1500 + # Byte-compiled / optimized / DLL files __pycache__/ *.py[cod] diff --git a/LICENSE b/LICENSE index 261eeb9..77ec40e 100644 --- a/LICENSE +++ b/LICENSE @@ -186,7 +186,7 @@ same "printed page" as the copyright notice for easier identification within third-party archives. - Copyright [yyyy] [name of copyright owner] + Copyright 2024 Fabio Milentiansen Sim Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. diff --git a/README.md b/README.md new file mode 100644 index 0000000..0835ec2 --- /dev/null +++ b/README.md @@ -0,0 +1,82 @@ +[![ONNX](https://img.shields.io/badge/ONNX-grey)](https://onnx.ai/) +[![GitHub Repo stars](https://img.shields.io/github/stars/fabio-sim/Depth-Anything-ONNX)](https://github.com/fabio-sim/Depth-Anything-ONNX/stargazers) +[![GitHub all releases](https://img.shields.io/github/downloads/fabio-sim/Depth-Anything-ONNX/total)](https://github.com/fabio-sim/Depth-Anything-ONNX/releases) + +# Depth Anything ONNX + +Open Neural Network Exchange (ONNX) compatible implementation of [Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data](https://github.com/LiheYoung/Depth-Anything). + +

+ +

+Changelog + +- **22 January 2024**: Release. +
+ +## 🔥 ONNX Export + +Prior to exporting the ONNX models, please install the [requirements](/requirements.txt). + +To convert the Depth Anything models to ONNX, run [`export.py`](/export.py). The pretrained weights will be downloaded automatically. + +
+Export Example +
+python export.py --model s
+
+
+ +If you would like to try out inference right away, you can download ONNX models that have already been exported [here](https://github.com/fabio-sim/Depth-Anything-ONNX/releases). + +## ⚡ ONNX Inference + +With ONNX models in hand, one can perform inference on Python using ONNX Runtime. See [`infer.py`](/infer.py). + +
+Inference Example +
+python infer.py --img assets/DSC_0410.JPG --model weights/depth_anything_vits14.onnx --viz
+
+
+ +## 🚀 TensorRT Support + +(To be investigated) + +## ⏱️ Inference Time Comparison + +

Latency Comparison + +We report the inference time, or latency, of only the model; that is, the time taken for preprocessing, postprocessing, or copying data between the host & device is not measured. The average inference time is defined as the median over all samples in the [MegaDepth](https://arxiv.org/abs/1804.00607) test dataset. We use the data provided by [LoFTR](https://arxiv.org/abs/2104.00680) [here](https://github.com/zju3dv/LoFTR/blob/master/docs/TRAINING.md) - a total of 806 images. + +Each image is resized such that its size is 518x518 before being fed into the model. The inference time is then measured for all model variants (S, B, L). See [eval.py](/eval.py) for the measurement code. + +All experiments are conducted on an i9-12900HX CPU and RTX4080 12GB GPU with `CUDA==11.8.1`, `torch==2.1.2`, and `onnxruntime==1.16.3`. + +### Notes + +- Currently, the inference speed is bottlenecked by Conv operations. +- ONNXRuntime performs slightly (20-25%) faster for the ViT-L model variant. + +## Credits +If you use any ideas from the papers or code in this repo, please consider citing the authors of [Depth Anything](https://arxiv.org/abs/2401.10891) and [DINOv2](https://arxiv.org/abs/2304.07193). Lastly, if the ONNX versions helped you in any way, please also consider starring this repository. + +```bibtex +@article{depthanything, + title={Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data}, + author={Yang, Lihe and Kang, Bingyi and Huang, Zilong and Xu, Xiaogang and Feng, Jiashi and Zhao, Hengshuang}, + journal={arXiv:2401.10891}, + year={2024} +} +``` + +```bibtex +@misc{oquab2023dinov2, + title={DINOv2: Learning Robust Visual Features without Supervision}, + author={Oquab, Maxime and Darcet, Timothée and Moutakanni, Theo and Vo, Huy V. and Szafraniec, Marc and Khalidov, Vasil and Fernandez, Pierre and Haziza, Daniel and Massa, Francisco and El-Nouby, Alaaeldin and Howes, Russell and Huang, Po-Yao and Xu, Hu and Sharma, Vasu and Li, Shang-Wen and Galuba, Wojciech and Rabbat, Mike and Assran, Mido and Ballas, Nicolas and Synnaeve, Gabriel and Misra, Ishan and Jegou, Herve and Mairal, Julien and Labatut, Patrick and Joulin, Armand and Bojanowski, Piotr}, + journal={arXiv:2304.07193}, + year={2023} +} +``` + diff --git a/assets/DSC_0410.JPG b/assets/DSC_0410.JPG new file mode 100755 index 0000000000000000000000000000000000000000..117569e91296c1f9647978443fb77092e2fe64d9 GIT binary patch literal 391451 zcmbUIbyQo=`vw38*J6d@1PU!)+$E(gR*Ji~xD@viytoxwph%J8P@q_GcXxLJ1SdfQ zgs}O1e`k09**|u7a_*euwg#Q)vH)0|};{Sg9ca#6S z6cYyv3x^O77w>Ct zQ!q9m3-?e0!e`Vpv~(|CvU6~935$q|iAzYneJ8J=sHFT}TSr$<-@wqw(#qP#*3RC+ z!_&*#$Jg&m*w^rg$f)R;XZ+4DC@d;2DJ`q1t*ign(Ad=6-P7CGKQK5n zJUufzH@~pBw7j(q+1cHL?jIb&&o3^ou5S>xcmLtSK;!&>mj92q$kDhk|9b{_|KY;G z^g$n3K2H{$IfU-?)|m#8?>UhlfQD00EG92t~-4_V!s9O`UO@yTO%8Y+iBtRzO8vTpDDW zf8bE&Xt9-#@mF@*vv8*p`n12%ACodM+BI;M0N$5X6C06_07kGe%tbTI5a#);ffz1q z{VJa)m%%C+ziWWDN^YjZ#XL$BC0YYls4X;*`N1!&FBy=_xfjuIP|dzaLvymQAaYlv z+kg9+L)+lTL;h}Dp%X8a)tP^L#ex6GFtp!>7MIJb@K|eSuF&7%E-2|b!RgP*va+Z= zrGv`Ta9ynL8GEgKaB8JFEmdRvg+G6`TN>>yM`-tSe-wNk9QO!Sp<-tQV6{8;dIl{o zbfUQ7qYcz3v0tsPY%Zu38*60!$H_#+;z(KDqy-M!e^Tw3*SYjhJoP>5m2CgMx%OcR 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