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--- |
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library_name: transformers.js |
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license: cc-by-nc-4.0 |
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pipeline_tag: depth-estimation |
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--- |
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https://huggingface.co/depth-anything/Depth-Anything-V2-Large with ONNX weights to be compatible with Transformers.js. |
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## Usage (Transformers.js) |
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If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@xenova/transformers) using: |
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```bash |
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npm i @xenova/transformers |
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``` |
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**Example:** Depth estimation w/ `onnx-community/depth-anything-v2-large`. |
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```js |
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import { pipeline } from '@xenova/transformers'; |
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// Create depth estimation pipeline |
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const depth_estimator = await pipeline('depth-estimation', 'onnx-community/depth-anything-v2-large'); |
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// Predict depth of an image |
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const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cats.jpg'; |
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const { depth } = await depth_estimator(url); |
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// Visualize the output |
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depth.save('depth.png'); |
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``` |
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/qsFAeXvMgph3Dm15nTICU.png) |
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--- |
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Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using [🤗 Optimum](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`). |