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README.md
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---
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library_name: transformers.js
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pipeline_tag: object-detection
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license: agpl-3.0
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---
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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.
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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('onnx-community/yolov10s', {
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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('onnx-community/yolov10s');
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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 { output0 } = await model({ images: pixel_values });
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const predictions = output0.tolist()[0];
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const threshold = 0.5;
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for (const [xmin, ymin, xmax, ymax, score, id] of predictions) {
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if (score < threshold) continue;
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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 [448.81, 378.16, 639.25, 477.85] with score 0.95.
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// Found "car" at [177.93, 338.54, 398.13, 417.66] with score 0.93.
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// Found "bicycle" at [449.25, 475.36, 555.90, 537.42] with score 0.92.
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// Found "bicycle" at [1.46, 517.67, 109.81, 584.15] with score 0.90.
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// Found "bicycle" at [351.74, 524.63, 464.50, 588.63] with score 0.87.
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// Found "person" at [550.09, 260.31, 591.83, 332.18] with score 0.85.
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// Found "person" at [474.90, 429.96, 533.88, 535.70] with score 0.83.
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// Found "traffic light" at [208.08, 55.58, 233.91, 102.01] with score 0.78.
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// ...
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```
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