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I can not train yolov5 in jupyter #10384
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👋 Hello @mohammadRezapor, thank you for your interest in YOLOv5 🚀! Please visit our ⭐️ Tutorials to get started, where you can find quickstart guides for simple tasks like Custom Data Training all the way to advanced concepts like Hyperparameter Evolution. If this is a 🐛 Bug Report, please provide screenshots and minimum viable code to reproduce your issue, otherwise we can not help you. If this is a custom training ❓ Question, please provide as much information as possible, including dataset images, training logs, screenshots, and a public link to online W&B logging if available. For business inquiries or professional support requests please visit https://ultralytics.com or email support@ultralytics.com. RequirementsPython>=3.7.0 with all requirements.txt installed including PyTorch>=1.7. To get started: git clone https://github.com/ultralytics/yolov5 # clone
cd yolov5
pip install -r requirements.txt # install EnvironmentsYOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):
StatusIf this badge is green, all YOLOv5 GitHub Actions Continuous Integration (CI) tests are currently passing. CI tests verify correct operation of YOLOv5 training, validation, inference, export and benchmarks on MacOS, Windows, and Ubuntu every 24 hours and on every commit. |
@mohammadRezapor seems to be caused by comet. Can you try |
@mohammadRezapor read your own error message, it's saying your data yaml is incorrect. To train correctly your data must be in YOLOv5 format. Please see our Train Custom Data tutorial for full documentation on dataset setup and all steps required to start training your first model. A few excerpts from the tutorial: 1.1 Create dataset.yamlCOCO128 is an example small tutorial dataset composed of the first 128 images in COCO train2017. These same 128 images are used for both training and validation to verify our training pipeline is capable of overfitting. data/coco128.yaml, shown below, is the dataset config file that defines 1) the dataset root directory # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/coco128 # dataset root dir
train: images/train2017 # train images (relative to 'path') 128 images
val: images/train2017 # val images (relative to 'path') 128 images
test: # test images (optional)
# Classes (80 COCO classes)
names:
0: person
1: bicycle
2: car
...
77: teddy bear
78: hair drier
79: toothbrush
1.2 Create LabelsAfter using a tool like Roboflow Annotate to label your images, export your labels to YOLO format, with one
The label file corresponding to the above image contains 2 persons (class 1.3 Organize DirectoriesOrganize your train and val images and labels according to the example below. YOLOv5 assumes ../datasets/coco128/images/im0.jpg # image
../datasets/coco128/labels/im0.txt # label Good luck 🍀 and let us know if you have any other questions! |
Thanks for the help, after starting tarining, I get the following error and traning stops. What is the reason for this error and how can I fix it? "OMP: Error #15: Initializing libiomp5md.dll, but found libiomp5md.dll already initialized. |
@mohammadRezapor it appears you may have environment problems. Please ensure you meet all dependency requirements if you are attempting to run YOLOv5 locally. If in doubt, create a new virtual Python 3.9 environment, clone the latest repo (code changes daily), and 💡 ProTip! Try one of our verified environments below if you are having trouble with your local environment. RequirementsPython>=3.7.0 with all requirements.txt installed including PyTorch>=1.7. To get started: git clone https://github.com/ultralytics/yolov5 # clone
cd yolov5
pip install -r requirements.txt # install Models and datasets download automatically from the latest YOLOv5 release when first requested. EnvironmentsYOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):
StatusIf this badge is green, all YOLOv5 GitHub Actions Continuous Integration (CI) tests are currently passing. CI tests verify correct operation of YOLOv5 training, validation, inference, export and benchmarks on MacOS, Windows, and Ubuntu every 24 hours and on every commit. |
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When I try to train the yolov5 model in jupyter I get the following error.
YOLOv5 Component
Training, PyTorch Hub
Bug
Environment
-YOLO : Yolov5 torch 1.13 cu116
-OS: windows 10
-Python: 3.9.7
Minimal Reproducible Example
#!python train.py --img 415 --batch 16 --epochs 30 --data Face-Detection-14/data.yaml --weights yolov5s.pt --cache
Additional
No response
Are you willing to submit a PR?
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