We develop an all-in-one computer vision toolbox named EasyCV to facilitate the use of various SOTA computer vision methods. Recently, we add YOLOX-PAI, an improved version of YOLOX, into EasyCV. We conduct ablation studies to investigate the influence of some detection methods on YOLOX. We also provide an easy use for PAI-Blade which is used to accelerate the inference process based on BladeDISC and TensorRT. Finally, we receive 42.8 mAP on COCO dateset within 1.0 ms on a single NVIDIA V100 GPU, which is a bit faster than YOLOv6. A simple but efficient predictor api is also designed in EasyCV to conduct end2end object detection. Codes and models are now available at: https://github.com/alibaba/EasyCV.
翻译:我们开发了一个名为 EasyCV 的全在计算机视觉工具箱,以便利使用各种SOTA计算机视觉方法。 最近,我们将YOLOX-PAI(经改进的YOLOX版本)添加到 ESEWCV。我们进行了反动研究,以调查某些探测方法对YOLOX的影响。我们还为PAI-Blade提供了一种方便的使用,它用来根据BladeDISC 和 TensorRT 加速推断过程。最后,我们收到42.8 mAP CO日期设置在1.0 ms之内的CoCO日期设置,该日期设置比YOLOv6要快一点。 在EnterCV 中设计了一个简单而有效的预测器,用于进行端端对天体的探测。现在可以在以下网址获得代码和模型: https://github.com/alibaba/EasyCV。