DETR:使用变压器进行端到端物体检测-开源

上传者: 42131541 | 上传时间: 2021-08-07 18:09:18 | 文件大小: 237KB | 文件类型: ZIP
PyTorch 训练代码和 DETR(检测转换器)的预训练模型。 我们用 Transformer 替换了完全复杂的手工对象检测管道,并将 Faster R-CNN 与 ResNet-50 匹配,使用一半的计算能力 (FLOP) 和相同数量的参数在 COCO 上获得 42 个 AP。 50 行 PyTorch 中的推理。 这是什么。 与传统的计算机视觉技术不同,DETR 将目标检测作为直接集预测问题来处理。 它由一个基于集合的全局损失和一个 Transformer 编码器-解码器架构组成,它通过二分匹配强制进行独特的预测。 给定一组固定的学习对象查询集,DETR 会推理对象和全局图像上下文的关系,以直接并行输出最终的预测集。 由于这种并行特性,DETR 非常快速和高效。

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