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--- |
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library_name: transformers.js |
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license: gpl-3.0 |
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pipeline_tag: object-detection |
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--- |
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https://github.com/WongKinYiu/yolov9 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:** Perform object-detection with `Xenova/yolov9-e`. |
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```js |
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import { AutoModel, AutoProcessor, RawImage } from '@xenova/transformers'; |
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// Load model |
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const model = await AutoModel.from_pretrained('Xenova/yolov9-e', { |
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// quantized: false, // (Optional) Use unquantized version. |
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}) |
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// Load processor |
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const processor = await AutoProcessor.from_pretrained('Xenova/yolov9-e'); |
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// processor.feature_extractor.do_resize = false; // (Optional) Disable resizing |
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// processor.feature_extractor.size = { width: 128, height: 128 } // (Optional) Update resize value |
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// Read image and run processor |
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const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/city-streets.jpg'; |
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const image = await RawImage.read(url); |
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const { pixel_values } = await processor(image); |
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// Run object detection |
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const { outputs } = await model({ images: pixel_values }) |
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const predictions = outputs.tolist(); |
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for (const [xmin, ymin, xmax, ymax, score, id] of predictions) { |
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const bbox = [xmin, ymin, xmax, ymax].map(x => x.toFixed(2)).join(', ') |
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console.log(`Found "${model.config.id2label[id]}" at [${bbox}] with score ${score.toFixed(2)}.`) |
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} |
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// Found "car" at [179.43, 337.57, 399.15, 418.16] with score 0.94. |
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// Found "car" at [447.38, 378.70, 640.22, 477.43] with score 0.93. |
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// Found "bicycle" at [352.49, 528.11, 463.47, 588.33] with score 0.90. |
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// Found "bicycle" at [0.82, 519.37, 110.09, 584.06] with score 0.89. |
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// Found "bicycle" at [448.96, 476.38, 556.01, 538.31] with score 0.89. |
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// Found "person" at [550.09, 261.24, 592.19, 331.37] with score 0.88. |
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// Found "person" at [472.53, 430.68, 534.50, 532.82] with score 0.87. |
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// Found "person" at [393.59, 481.02, 442.97, 587.68] with score 0.85. |
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// ... |
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``` |
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## Demo |
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Test it out [here](https://huggingface.co/spaces/Xenova/yolov9-web)! |
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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`). |