--- 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/yolov10l', { // quantized: false, // (Optional) Use unquantized version. }) // Load processor const processor = await AutoProcessor.from_pretrained('onnx-community/yolov10l'); // 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 "person" at [473.05, 430.35, 533.53, 532.43] with score 0.92. // Found "car" at [447.48, 378.60, 639.69, 478.38] with score 0.92. // Found "person" at [549.94, 260.96, 591.81, 331.22] with score 0.91. // Found "person" at [33.50, 469.62, 78.99, 571.88] with score 0.90. // Found "car" at [177.90, 337.14, 399.34, 418.01] with score 0.90. // Found "traffic light" at [208.80, 55.90, 233.13, 101.39] with score 0.90. // Found "bicycle" at [449.02, 477.23, 555.98, 537.56] with score 0.89. // Found "bicycle" at [352.45, 527.27, 463.67, 588.07] with score 0.89. // ... ```