wudashuo / yolov5 Goto Github PK

❔Question

根据你的显卡情况，使用最大的 --batch-size ，那我的是6g显存的，他的--batch-size怎么计算

Additional context

E:\anaconda3\envs\pytorch\python.exe C:/yolov5-master/detect.py
detect: weights=C:/Users/10980/PycharmProjects/best.pt, source=runs/detect/exp25/zidane.jpg, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=0, view_img=True, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False
YOLOv5 2021-9-21 torch 1.9.1 CUDA:0 (NVIDIA GeForce RTX 2080 Ti, 11264.0MB)

Fusing layers...
Model Summary: 224 layers, 7056607 parameters, 0 gradients, 16.3 GFLOPs
image 1/1 C:\yolov5-master\runs\detect\exp25\zidane.jpg: 384x640 2 person_heads, 2 person_vboxs, Done. (0.016s)
Speed: 0.0ms pre-process, 15.6ms inference, 0.0ms NMS per image at shape (1, 3, 640, 640)
Results saved to runs\detect\exp26
#############################################

E:\anaconda3\envs\pytorch\python.exe C:/Users/10980/PycharmProjects/msstestcapture.py
Using cache found in C:\Users\10980/.cache\torch\hub\ultralytics_yolov5_master
YOLOv5 2021-9-24 torch 1.9.1 CUDA:0 (NVIDIA GeForce RTX 2080 Ti, 11264.0MB)

Fusing layers...
Model Summary: 224 layers, 7266973 parameters, 0 gradients
Adding AutoShape...
image 1/1: 720x1280 2 persons, 2 ties
Speed: 15.6ms pre-process, 15.6ms inference, 0.0ms NMS per image at shape (1, 3, 384, 640)

Process finished with exit code 0

Run detect.py 为什么速度更快？同一张图片。看时间是跳过了pre-process.
Speed: 0.0ms pre-process, 15.6ms inference, 0.0ms NMS per image at shape (1, 3, 640, 640)
但是为什么hub 不是这样呢？ 或者怎么提升这个速度呢？
谢谢！

# Model
# model = torch.hub.load('ultralytics/yolov5', 'yolov5s')  # or yolov5m, yolov5l, yolov5x, custom

# Images
img = 'C:/yolov5-master/GettyImages-688402807_header-1024x575.jpg'  # or file, Path, PIL, OpenCV, numpy, list

# Inference
results = model(img)
# results.save()
# Results
results.print()  # or .show(), .save(), .crop(), .pandas(), etc.

E:\anaconda3\envs\pytorch\python.exe C:/Users/10980/PycharmProjects/msstestcapture.py
Using cache found in C:\Users\10980/.cache\torch\hub\ultralytics_yolov5_master
YOLOv5 2021-9-24 torch 1.9.1 CUDA:0 (NVIDIA GeForce RTX 2080 Ti, 11264.0MB)

Fusing layers...
Model Summary: 224 layers, 7266973 parameters, 0 gradients
Adding AutoShape...
image 1/1: 720x1280 2 persons, 2 ties
Speed: 15.6ms pre-process, 15.6ms inference, 0.0ms NMS per image at shape (1, 3, 384, 640)

❔Question

想问下yolov单机最多能支持多少路实时rtsp摄像头的处理，需要什么硬件支撑。

Additional context

你好
yolo 6.2 and 7.0版本皆有支援語意分割功能
不曉得能否再predict.py，除了save-txt功能外，多加一個save-json
方便我們直接在labelme軟體編輯
謝謝

❔Question请问融合BN层的功能怎么使用呢？在哪里添加？

Additional context

❔Question

想请问一下，修改模型是在哪里修改呢？

Additional context

❔Question

运行的时，有500多种分类，批次大小32，然后就报GPU内存不足。后面就把种类调到85，批次大小调成16就没报错了，请问这个怎么调参呢？

Additional context

• CentOS 7.6.1810
• 显存 16G
• Python 3.8.3
• PyTorch 1.7.1
• CUDA 10.1

你好，非常感谢你翻译了yolov5的官方文档，让我学起来轻松了很多。
我想知道如何自定义mAP值呢？例如从[email protected]改为[email protected]

❔Question

请问怎么操作可以同时保存多个rtsp流视频

Additional context

❔Question

在执行detect.py后，图片没有lable

当我训练时，会报以下错误:
Traceback (most recent call last): File "/home/code/yolov5-master/train.py", line 522, in <module> device = select_device(opt.device, batch_size=opt.batch_size) File "/home/code/yolov5-master/utils/torch_utils.py", line 78, in select_device assert batch_size % n == 0, f'batch-size {batch_size} not multiple of GPU count {n}' AssertionError: batch-size 64 not multiple of GPU count 9

为此我注释掉 untils/torch_utils.py文件中的以下两行：
if n > 1 and batch_size: # check that batch_size is compatible with device_count assert batch_size % n == 0, f'batch-size {batch_size} not multiple of GPU count {n}'

当我再运行时，将device设置为1，但最终会占用所有的gpu（linux系统**有9个gpu，会被全部占用）

我的安装包如下所示：
_libgcc_mutex 0.1 main https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
ca-certificates 2021.1.19 h06a4308_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
certifi 2020.12.5 py38h06a4308_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
cudatoolkit 10.1.243 h6bb024c_0
ld_impl_linux-64 2.33.1 h53a641e_7 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libffi 3.3 he6710b0_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libgcc-ng 9.1.0 hdf63c60_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libstdcxx-ng 9.1.0 hdf63c60_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
ncurses 6.2 he6710b0_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
numpy 1.20.2
openssl 1.1.1k h27cfd23_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
Pillow 8.2.0
pip 21.0.1 py38h06a4308_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
python 3.8.8 hdb3f193_4 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
readline 8.1 h27cfd23_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
setuptools 52.0.0 py38h06a4308_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
sqlite 3.35.4 hdfb4753_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
tk 8.6.10 hbc83047_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
torch 1.7.1+cu101
torchvision 0.8.2
typing-extensions 3.7.4.3
wheel 0.36.2 pyhd3eb1b0_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
xz 5.2.5 h7b6447c_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
zlib 1.2.11 h7b6447c_3 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main

absl-py 0.12.0
cachetools 4.2.1
certifi 2020.12.5
chardet 4.0.0
cycler 0.10.0
Cython 0.29.22
google-auth 1.28.1
google-auth-oauthlib 0.4.4
greenlet 1.0.0
grpcio 1.37.0
idna 2.10
kiwisolver 1.3.1
Markdown 3.3.4
matplotlib 3.3.4
mkl-fft 1.3.0
mkl-random 1.1.1
mkl-service 2.3.0
numpy 1.20.2
oauthlib 3.1.0
olefile 0.46
opencv-python 4.5.1.48
pandas 1.2.3
Pillow 8.2.0
pip 21.0.1
protobuf 3.15.8
pyasn1 0.4.8
pyasn1-modules 0.2.8
pycairo 1.19.1
pycocotools 2.0.2
pyparsing 2.4.7
python-dateutil 2.8.1
pytz 2021.1
PyYAML 5.4.1
reportlab 3.5.66
requests 2.25.1
requests-oauthlib 1.3.0
rsa 4.7.2
scipy 1.6.2
seaborn 0.11.1
setuptools 52.0.0.post20210125
six 1.15.0
SQLAlchemy 1.4.5
tensorboard 2.4.1
tensorboard-plugin-wit 1.8.0
thop 0.0.31.post2005241907
torch 1.7.1+cu101
torchvision 0.8.2
tornado 6.1
tqdm 4.60.0
typing-extensions 3.7.4.3
urllib3 1.26.4
Werkzeug 1.0.1
wheel 0.36.2

Search before asking

• I have searched the YOLOv5 issues and discussions and found no similar questions.

Question

使用yolov5s，3090显卡，batch=64，epoch=300，单卡和8卡大家训练时间分别多少？我8卡怎么要25小时，这个正常吗？

Additional

No response

❔Question

我修改了一下网络，train.py训练出来的P R map这些结果挺正常的，但是我用训练出来的权重跑 val.py 的时候P R map就全部都是0，这是怎么回事？

Additional context

Search before asking

• I have searched the YOLOv5 issues and discussions and found no similar questions.

Question

YOLO v5的mosaic-9启用问题：需要设置哪些参数，如何启用Mosaic-9？
I would like to know that how to set the config for mosiac-9 and how to activate it ?
thanks a lot !

Additional

No response

❔Question

我下载的caltech数据集12万张，只检测行人一个类的，然后跑了50个epoch后得到的模型检测时效果不好，想问下我该如何进一步优化呢，是在这个模型的基础上继续加大epoch训练吗还是怎么做呢？求大佬指点一波

Additional context

Search before asking

• I have searched the YOLOv5 issues and discussions and found no similar questions.

Question

在代码中如何设置并实现呢？谢谢

Additional

No response