Pytorch implementation of YOLOX、PPYOLO、PPYOLOv2、FCOS an so on.

Last update: Jan 2, 2023

Related tags

Deep Learning yolo yolov3 fcos ppyolo yolox ppyolov2

Overview

简体中文 | English

miemiedetection

概述

miemiedetection是女装大佬咩酱基于YOLOX进行二次开发的个人检测库（使用的深度学习框架为pytorch），支持Windows、Linux系统，以女装大佬咩酱的名字命名。miemiedetection是一个不需要安装的检测库用户可以直接更改其代码改变执行逻辑，所见即所得！所以往miemiedetection里加入新的算法是一件很容易的事情（可以参考PPYOLO的写法往miemiedetection里加入新的算法）。得益于YOLOX的优秀架构，miemiedetection里的算法训练速度都非常快，数据读取不再是训练速度的瓶颈！目前miemiedetection支持YOLOX、PPYOLO、PPYOLOv2等算法，预计未来会加入更多算法，所以请大家点个star吧！

安装依赖

pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple

torch版本建议1.9.1+cu102或者更高；torchvision版本建议0.10.1+cu102或者更高。

支持的算法

传送门

cv算法交流q群：645796480 但是关于仓库的疑问尽量在Issues上提，避免重复解答。

B站不定时女装: _糖蜜

知乎不定时谢邀、写文章: 咩咩2013

西瓜视频: 咩咩2013

本人微信公众号：miemie_2013

技术博客：https://blog.csdn.net/qq_27311165

AIStudio主页：asasasaaawws

欢迎在GitHub或上面的平台关注我（求粉）~

打赏

如果你觉得这个仓库对你很有帮助，可以给我打钱↓

咩酱爱你哟！

引用

 @article{yolox2021,
  title={YOLOX: Exceeding YOLO Series in 2021},
  author={Ge, Zheng and Liu, Songtao and Wang, Feng and Li, Zeming and Sun, Jian},
  journal={arXiv preprint arXiv:2107.08430},
  year={2021}
}

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Comments

yolox_head_fast.py中当G == 0的返回loss有问题

if G == 0: # 所有图片都没有gt时 obj_targets = torch.zeros((N, A, 1), dtype=torch.float32, device=obj_preds.device) num_fg = 1 # 所有图片都没有gt时，设为1 loss_obj = self.bcewithlog_loss(obj_preds, obj_targets) loss_obj = loss_obj.sum() / num_fg losses = { "loss_obj": loss_obj, } return losses yolox_head_fast.py中的这一段是不是错了这个losses和下面的对不上 return ( loss, reg_weight * loss_iou, loss_obj, loss_cls, loss_l1, num_fg / max(num_gts, 1), )

opened by xiaoxuebajie 0
训练中途出现fast_cocoeval问题

你好，很高兴这里有你的辛苦整理，对我有很大的帮助，但是当我浮现代码跑了2个epoch时候，出现如下错误，请问怎么解决啊

File "C:\D_installation_packet\Anaconda\installion_package\envs\yolox\lib\site-packages\torch\utils\cpp_extension.py", line 1079, in load return _jit_compile( └ <function _jit_compile at 0x00000213A2B06550>

File "C:\D_installation_packet\Anaconda\installion_package\envs\yolox\lib\site-packages\torch\utils\cpp_extension.py", line 1292, in _jit_compile _write_ninja_file_and_build_library( └ <function _write_ninja_file_and_build_library at 0x00000213A2B06670>

File "C:\D_installation_packet\Anaconda\installion_package\envs\yolox\lib\site-packages\torch\utils\cpp_extension.py", line 1404, in _write_ninja_file_and_build_library _run_ninja_build( └ <function _run_ninja_build at 0x00000213A2B06AF0>

File "C:\D_installation_packet\Anaconda\installion_package\envs\yolox\lib\site-packages\torch\utils\cpp_extension.py", line 1683, in _run_ninja_build raise RuntimeError(message) from e └ "Error building extension 'fast_cocoeval'"

RuntimeError: Error building extension 'fast_cocoeval'

Process finished with exit code 0

opened by Wisdom2wisdom 0
训练自定义数据集时出了个错

An error has been caught in function 'launch', process 'MainProcess' (5932), t hread 'MainThread' (20804): Traceback (most recent call last):

File "tools\train.py", line 137, in launch( └ <function launch at 0x0000022C3AC6AAF0>

File "D:\YoLo\miemiedetection-main\mmdet\core\launch.py", line 98, in launch main_func(*args) │ └ (╒═══════════════════════╤═══════════════════════════════════════════════════════════════════════════════════════════ ════════... └ <function main at 0x0000022C3AC6AE50>

File "tools\train.py", line 115, in main trainer.train() │ └ <function Trainer.train at 0x0000022C3D390430> └ <mmdet.core.trainer.Trainer object at 0x0000022C3D421880>

File "D:\YoLo\miemiedetection-main\mmdet\core\trainer.py", line 101, in train self.before_train() │ └ <function Trainer.before_train at 0x0000022C3D3909D0> └ <mmdet.core.trainer.Trainer object at 0x0000022C3D421880>

File "D:\YoLo\miemiedetection-main\mmdet\core\trainer.py", line 504, in before_train self.train_loader = self.exp.get_data_loader( │ │ │ └ <function PPYOLOE_Method_Exp.get_data_loader at 0x0000022C3D3F8B80> │ │ └ ╒═══════════════════════╤══════════════════════════════════════════════════════════════════════════════ ══════════════════════... │ └ <mmdet.core.trainer.Trainer object at 0x0000022C3D421880> └ <mmdet.core.trainer.Trainer object at 0x0000022C3D421880>

File "D:\YoLo\miemiedetection-main\mmdet\exp\ppyoloe\ppyoloe_method_base.py", line 260, in get_data_loader train_dataset = PPYOLOE_COCOTrainDataset( └ <class 'mmdet.data.datasets.coco.PPYOLOE_COCOTrainDataset'>

File "D:\YoLo\miemiedetection-main\mmdet\data\datasets\coco.py", line 780, in init train_records = data_clean(train_dataset, train_img_ids, _catid2clsid, train_pre_path, 'train', xy_plus_1=True) │ │ │ │ └ 'datasets\Go_Black_White_COCO/train2017' │ │ │ └ {0: 0, 1: 1, 2: 2, 3: 3} │ │ └ ['000001', '000002', '000004', '000005', '000006', '000007', '000008', '000009', '0000 10', '000011', '000012', '000013', '000... │ └ <pycocotools.coco.COCO object at 0x0000022C3D5233D0> └ <function data_clean at 0x0000022C3C6B28B0>

File "D:\YoLo\miemiedetection-main\mmdet\data\datasets\coco.py", line 229, in data_clean img_anno = coco.loadImgs(img_id)[0] │ │ └ '000001' │ └ <function COCO.loadImgs at 0x0000022C3D39A3A0> └ <pycocotools.coco.COCO object at 0x0000022C3D5233D0>

File "D:\Anaconda3\lib\site-packages\pycocotools\coco.py", line 229, in loadImgs return [self.imgs[id] for id in ids] │ │ └ '000001' │ └ {'000001': {'file_name': '000001.jpg', 'height': 640, 'width': 640, 'id': '000001'}, '000002': {'file_name': '00000 2.jpg', 'h... └ <pycocotools.coco.COCO object at 0x0000022C3D5233D0>

File "D:\Anaconda3\lib\site-packages\pycocotools\coco.py", line 229, in return [self.imgs[id] for id in ids] │ │ │ └ '0' │ │ └ '0' │ └ {'000001': {'file_name': '000001.jpg', 'height': 640, 'width': 640, 'id': '000001'}, '000002': {'file_name': '00000 2.jpg', 'h... └ <pycocotools.coco.COCO object at 0x0000022C3D5233D0>

KeyError: '0'

opened by MrAccelerator 0
支持ppyoloe plus 的转换么？
我自己在aistudio（白嫖v100）上训练了个ppyoloe plus模型，用ppyoloe 的权重转换脚本转换报错：脚本命令：

python tools/convert_weights.py -f exps/ppyoloe/ppyoloe_crn_s_300e_coco.py -c model_final.pdparams -oc ppyoloe_crn_s_300e_coco.pth -nc 1
opened by ChaoII 0