Improve model card: Add pipeline tag, paper link, code link, and usage
Browse filesThis PR improves the model card by:
- Adding the `pipeline_tag: depth-estimation` to enhance discoverability on the Hugging Face Hub.
- Including a direct link to the paper [Manipulation as in Simulation: Enabling Accurate Geometry Perception in Robots](https://huggingface.co/papers/2509.02530).
- Providing a clear link to the main GitHub repository: https://github.com/ByteDance-Seed/manip-as-in-sim-suite.
- Adding a sample usage section with a code snippet from the GitHub README to demonstrate how to perform inference with the Camera Depth Model (CDM).
README.md
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license: cc-by-nc-4.0
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license: cc-by-nc-4.0
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pipeline_tag: depth-estimation
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# Manipulation as in Simulation: Enabling Accurate Geometry Perception in Robots
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This repository contains the Camera Depth Models (CDMs) from the paper [Manipulation as in Simulation: Enabling Accurate Geometry Perception in Robots](https://huggingface.co/papers/2509.02530).
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CDMs are proposed as a simple plugin for daily-use depth cameras, taking RGB images and raw depth signals as input to output denoised, accurate metric depth. This enables policies trained purely in simulation to transfer directly to real robots, effectively bridging the sim-to-real gap for manipulation tasks.
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* **Project page:** https://manipulation-as-in-simulation.github.io/
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* **Code repository:** https://github.com/ByteDance-Seed/manip-as-in-sim-suite
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## Usage
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To run depth inference on RGB-D camera data, follow the example from the [GitHub repository's CDM section](https://github.com/ByteDance-Seed/manip-as-in-sim-suite/tree/main/cdm):
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```bash
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cd cdm
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python infer.py \
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--encoder vitl \
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--model-path /path/to/model.pth \
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--rgb-image /path/to/rgb.jpg \
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--depth-image /path/to/depth.png \
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--output result.png
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```
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