Add ExecuTorch WebGPU program for depth-anything-v2-small

NOTICE

@@ -1,6 +1,6 @@
 This repository contains a modified version of depth-anything/Depth-Anything-V2-Small-hf.
 
 Modifications by Meta Platforms, Inc.: conversion to the ExecuTorch program format (.pte) for the
-ExecuTorch WebGPU backend, and quantization as described in README.md.
+ExecuTorch WebGPU backend.
 
 The original work and these modifications are distributed under the license in LICENSE.

README.md

@@ -2,9 +2,9 @@
 license: apache-2.0
 base_model:
 - depth-anything/Depth-Anything-V2-Small-hf
-base_model_relation: quantized
 library_name: executorch
 pipeline_tag: depth-estimation
+inference: false
 tags:
 - executorch
 - webgpu
@@ -15,8 +15,7 @@ tags:
 
 This repository contains an [ExecuTorch](https://github.com/pytorch/executorch) conversion of
 [depth-anything/Depth-Anything-V2-Small-hf](https://huggingface.co/depth-anything/Depth-Anything-V2-Small-hf) for the ExecuTorch **WebGPU** backend, so the model runs entirely in a web browser on
-the visitor's GPU. It powers the corresponding demo in the
-ExecuTorch WebGPU Playground (launching soon on [executorch.ai](https://executorch.ai)).
+the visitor's GPU. It powers the corresponding demo in the ExecuTorch WebGPU Playground (launching soon on [executorch.ai](https://executorch.ai)).
 
 - **Base model:** [depth-anything/Depth-Anything-V2-Small-hf](https://huggingface.co/depth-anything/Depth-Anything-V2-Small-hf)
 - **Format:** ExecuTorch `.pte` programs delegated to the WebGPU backend
@@ -25,6 +24,32 @@ ExecuTorch WebGPU Playground (launching soon on [executorch.ai](https://executor
 
 > **Note:** This is the Small variant, which is licensed Apache-2.0 (the larger Depth Anything V2 variants use a different license).
 
+## About the original model
+
+The Small variant of Depth Anything V2, a monocular depth estimation model trained on about 595K synthetic labeled images and 62M+ real unlabeled images.
+
+- **Developed by:** Lihe Yang et al. (HKU and TikTok)
+- **Paper:** [Depth Anything V2](https://arxiv.org/abs/2406.09414)
+- 24.8M parameters
+- Predicts relative depth from a single image
+
+For training data, evaluation results and full details, see the original model card: [depth-anything/Depth-Anything-V2-Small-hf](https://huggingface.co/depth-anything/Depth-Anything-V2-Small-hf).
+
+## Intended use and limitations
+
+Relative depth maps for photos and camera frames.
+
+Outputs relative (not metric) depth. Accuracy drops on reflective or transparent surfaces and unusual scenes.
+
+## What changed in this conversion
+
+- Fixed 224x224 input (upstream processes larger images)
+
+## Inputs and outputs
+
+- Input `[1, 3, 224, 224]` float32 RGB, ImageNet-normalized: `(x / 255 - mean) / std`, mean 0.485/0.456/0.406, std 0.229/0.224/0.225
+- Output `[1, 224, 224]` float32 relative inverse depth (larger means closer)
+
 ## Files
 
 | File | Size | SHA-256 |
@@ -35,10 +60,13 @@ Full checksums are in `manifest.json`. The playground verifies them after downlo
 
 ## Running it
 
-These programs need the ExecuTorch WebGPU runtime compiled to WebAssembly
-([backends/webgpu](https://github.com/pytorch/executorch/tree/main/backends/webgpu)). The easiest way to
-try the model is the ExecuTorch WebGPU Playground (launching soon on [executorch.ai](https://executorch.ai)),
-which downloads these files once, caches them in the browser, and runs everything locally.
+These programs were exported with the ExecuTorch WebGPU backend
+([backends/webgpu](https://github.com/pytorch/executorch/tree/main/backends/webgpu)) and validated with the
+WebAssembly runtime build used by the ExecuTorch WebGPU Playground (launching soon on [executorch.ai](https://executorch.ai)). That runtime build is not published yet; until it is,
+the playground is the supported way to run them. It downloads these files once, caches them in the browser,
+and runs everything locally.
+
+Requirements: a browser with WebGPU enabled.
 
 ## Provenance
 
@@ -47,8 +75,23 @@ which downloads these files once, caches them in the browser, and runs everythin
 - **Reproduce:** `python recipes/depth-anything-v2-small.py --out out/depth-anything-v2-small` (recipe in `export/`)
 - Re-running the recipe produces byte-identical files.
 
+## Citation
+
+If you use this model, please cite the original work:
+
+```bibtex
+@misc{yang2024depth,
+  title={Depth Anything V2},
+  author={Lihe Yang and Bingyi Kang and Zilong Huang and Zhen Zhao and Xiaogang Xu and Jiashi Feng and Hengshuang Zhao},
+  year={2024},
+  eprint={2406.09414},
+  archivePrefix={arXiv},
+  primaryClass={cs.CV}
+}
+```
+
 ## License
 
 This is a derivative of the upstream model and is distributed under the same terms
 (`apache-2.0`); see `LICENSE`.
-Modifications (conversion to the ExecuTorch format and quantization) by Meta Platforms, Inc.
+Modifications (conversion to the ExecuTorch format) by Meta Platforms, Inc.