README.md

---
library_name: transformers.js
pipeline_tag: object-detection
license: agpl-3.0
---

# YOLOv10: Real-Time End-to-End Object Detection

ONNX weights for https://github.com/THU-MIG/yolov10.

Latency-accuracy trade-offs             |  Size-accuracy trade-offs
:-------------------------:|:-------------------------:
![latency-accuracy trade-offs](https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/cXru_kY_pRt4n4mHERnFp.png)  |  ![size-accuracy trade-offs](https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/8apBp9fEZW2gHVdwBN-nC.png)

## Usage (Transformers.js)

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:
```bash
npm i @xenova/transformers
```

**Example:** Perform object-detection.
```js
import { AutoModel, AutoProcessor, RawImage } from '@xenova/transformers';

// Load model
const model = await AutoModel.from_pretrained('onnx-community/yolov10b', {
    // quantized: false,    // (Optional) Use unquantized version.
})

// Load processor
const processor = await AutoProcessor.from_pretrained('onnx-community/yolov10b');

// Read image and run processor
const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/city-streets.jpg';
const image = await RawImage.read(url);
const { pixel_values } = await processor(image);

// Run object detection
const { output0 } = await model({ images: pixel_values });
const predictions = output0.tolist()[0];
const threshold = 0.5;
for (const [xmin, ymin, xmax, ymax, score, id] of predictions) {
    if (score < threshold) continue;
    const bbox = [xmin, ymin, xmax, ymax].map(x => x.toFixed(2)).join(', ')
    console.log(`Found "${model.config.id2label[id]}" at [${bbox}] with score ${score.toFixed(2)}.`)
}
// Found "car" at [447.84, 378.56, 639.25, 478.67] with score 0.94.
// Found "car" at [176.77, 336.73, 398.79, 418.09] with score 0.94.
// Found "bicycle" at [351.96, 526.97, 463.51, 588.49] with score 0.93.
// Found "bicycle" at [449.39, 477.36, 555.63, 538.10] with score 0.91.
// Found "person" at [474.16, 429.78, 534.73, 534.29] with score 0.91.
// Found "bicycle" at [1.51, 517.97, 110.14, 584.14] with score 0.90.
// Found "person" at [31.05, 469.64, 79.11, 567.90] with score 0.90.
// Found "person" at [394.04, 479.20, 442.46, 587.36] with score 0.89.
// ...
```