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why change from python3.6 to python3.7? #7631
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👋 Hello @fei4xu, 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 (train.py), validation (val.py), inference (detect.py) and export (export.py) on macOS, Windows, and Ubuntu every 24 hours and on every commit. |
@fei4xu Python 3.6 has reached end of life and is no longer officially supported: https://endoflife.date/python |
Thanks, so I can safely guess that there isn't a technical reason (like library dependency) to drop python 3.6 support. Actually I just tried, on Jetson Nano (python 3.6.9), with the latest code on master branch, if I ignore this change (a19406b) and change opencv from 4.1.2 to Python version itself and the dependent libraries' version are alwasy a headache for new users. I don't want to let new users like me spend lots of time upgrading python versions. so maybe we can still leave a note on the readme page that python3.6 still works but not recommanded? Thanks again for the great work! |
@fei4xu we can try to revert cv2 dependency to 4.1.1, but we can no longer state support for 3.6 as we no longer test for it. |
@fei4xu good news 😃! Your original issue may now be fixed ✅ in PR #7645. This PR drops cv2 requirements to >=4.1.1. I think the second change that would be needed for native Jetson support would be to do a soft test of python version (display a warning) rather than a hard test. To receive this update:
Thank you for spotting this issue and informing us of the problem. Please let us know if this update resolves the issue for you, and feel free to inform us of any other issues you discover or feature requests that come to mind. Happy trainings with YOLOv5 🚀! |
@fei4xu unofficial 3.6.9 support seems to work across most operating systems (macos and ubuntu). See https://github.com/ultralytics/yolov5/runs/6234184629?check_suite_focus=true |
Hi all, sorry for reviving this, but it might help the OP. Question though: I had to add a swapfile to make inference run because Yolov5 consumes a lot of memory (1.9/2 GB RAM and 2.1 GB of swap). Are these numbers normal for Yolov5? I am only interested in running inference on this device, no training. Anything I can tune to fit in 2GB RAM? Already switched to lightdm which saves me ~500 MB. |
@StephenBeirlaen great, thanks for the confirmation! Most of our focus has been on efficient resource utilization during training, i.e. reducing CUDA memory requirements, and not especially on edge device inference, so I can't provide you specifics there. But that said, torch is primarily a training framework and you can definitely realize performance gains by exporting to TRT for CUDA deployments, i.e.:
Usage: git clone https://github.com/ultralytics/yolov5 -b update/bench_gpu # clone
cd yolov5
pip install -qr requirements.txt coremltools onnx onnxruntime-gpu openvino-dev # install
pip install -U nvidia-tensorrt --index-url https://pypi.ngc.nvidia.com # TensorRT
python utils/benchmarks.py --weights yolov5s.pt --img 640 --device 0 Colab Pro+ V100 High-RAM Results
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Hi,
I have a Jetson Nano with has python 3.6 and its pytorch version for python3.6.
I checked the readme.md and found that the required python version was changed from 3.6 to 3.7 recently ( commit ff8646c 2022/1/26) and then released as v6.1 tag. I didn't see any python or library upgrade around those commits.
I'd like to check if this is a planned version upgrade or python3.6 is still supported.
Thanks,
Fei
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