使用transformer.js在浏览器中运行yolov9模型
安装
npm i @xenova/transformers代码
import { AutoModel, AutoProcessor, RawImage } from '@xenova/transformers'; // Load model const model = await AutoModel.from_pretrained('Xenova/yolov9-c', { // quantized: false, // (Optional) Use unquantized version. }) // Load processor const processor = await AutoProcessor.from_pretrained('Xenova/yolov9-c'); // processor.feature_extractor.do_resize = false; // (Optional) Disable resizing // processor.feature_extractor.size = { width: 128, height: 128 } // (Optional) Update resize value // 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 { outputs } = await model({ images: pixel_values }) const predictions = outputs.tolist(); for (const [xmin, ymin, xmax, ymax, score, id] of predictions) { 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 [176.86, 335.53, 399.82, 418.13] with score 0.94. // Found "car" at [447.50, 378.46, 639.81, 477.57] with score 0.93. // Found "bicycle" at [351.90, 527.82, 463.50, 587.76] with score 0.90. // Found "person" at [472.44, 430.52, 533.74, 533.30] with score 0.89. // Found "bicycle" at [448.97, 477.34, 555.42, 537.63] with score 0.88. // Found "bicycle" at [0.59, 518.69, 109.53, 584.31] with score 0.88. // Found "traffic light" at [208.55, 55.80, 233.99, 101.63] with score 0.86. // Found "person" at [550.75, 260.98, 591.90, 331.24] with score 0.86. // ...在线例子:https://xenova-yolov9-web.static.hf.space/index.html
https://huggingface.co/Xenova/yolov9-c
https://github.com/WongKinYiu/yolov9
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