DataXujing / Pytorch_YOLO-v4
Pytorch YOLO v4 训练自己的数据集超详细教程!!! (提供PDF训练教程下载)
☆30Updated 4 years ago
Alternatives and similar repositories for Pytorch_YOLO-v4:
Users that are interested in Pytorch_YOLO-v4 are comparing it to the libraries listed below
- Learning YOLOv3 from scratch 从零开始学习YOLOv3代码☆215Updated 3 years ago
- Prepare VOC format datasets for ultralytics/yolov3 & yolov5☆197Updated last year
- Simple implementation of augmentation for small object detection☆220Updated 4 years ago
- Yolov5 distillation training | Yolov5知识蒸馏训练,支持训练自己的数据☆213Updated 2 years ago
- Pytorch复现YOLOv3,使用最新的DIOU loss训练☆69Updated 4 years ago
- Using model pruning method to obtain compact models Pruned-YOLOv5 based on YOLOv5.☆58Updated 3 years ago
- 布匹缺陷识别练习赛☆45Updated 4 years ago
- 最简单的VOC转COCO, 一条指令完整转换☆83Updated 5 years ago
- imgaug--Bounding Boxes augment☆90Updated 5 years ago
- ☆68Updated 3 years ago
- yolov5 5.0 version distillation || yolov5 5.0版本知识蒸馏,yolov5l >> yolov5s☆157Updated 3 years ago
- Tips on how to find suitable object detection anchors☆145Updated 4 years ago
- ☆76Updated 3 years ago
- ☆91Updated 3 years ago
- change the vocdataset 2 cocodataset pattern☆69Updated 6 years ago
- yolov5 v1版本中文注释☆58Updated 4 years ago
- a data augment tool for object detection☆90Updated 6 years ago
- Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression (AAAI 2020)☆47Updated 3 years ago
- ppyolo in pytorch. 44.8% box mAP.☆108Updated 3 years ago
- yolov5的注释版本☆270Updated 4 years ago
- annotations of yolov5-5.0☆232Updated 3 years ago
- 基于pytorch版ssd进行改进注入CBAM空间通道注意力机制,加入FPN,类别损失函数改为focalloss☆39Updated 3 years ago
- A resnet18 version of CenterNet(objects as points)☆124Updated 3 years ago
- 计算机视觉方面的分类、对象检测、图像分割、人脸检测、OCR等中文翻译☆110Updated 3 years ago
- 这个是一个在SSD的基础上用于生成绘制mAP代码所用的txt的例子。(目的是生成txt)☆129Updated 4 years ago
- ghostnet_cifar10☆114Updated 4 years ago
- ☆62Updated 5 years ago
- ☆106Updated 3 years ago
- 本仓库主要包含了针对目标检测数据集的增强手段和源码:图像的旋转,镜像,裁剪,亮度/对比度的变换等☆134Updated 4 years ago
- yolov5 with more backbone☆17Updated 2 years ago