glenn-jocher
commented
3 years ago Hello, thank you for your interest in our work! This issue seems to lack the minimum requirements for a proper response, or is insufficiently detailed for us to help you. Please note that most technical problems are due to:
- Your modified or out-of-date code. If your issue is not reproducible in a new
git cloneversion of this repo we can not debug it. Before going further run this code and verify your issue persists:$ git clone https://github.com/ultralytics/yolov5 yolov5_new # clone latest $ cd yolov5_new $ python detect.py # verify detection
CODE TO REPRODUCE YOUR ISSUE HERE
- **Your custom data.** If your issue is not reproducible in one of our 3 common datasets ([COCO](https://github.com/ultralytics/yolov5/blob/master/data/coco.yaml), [COCO128](https://github.com/ultralytics/yolov5/blob/master/data/coco128.yaml), or [VOC](https://github.com/ultralytics/yolov5/blob/master/data/voc.yaml)) we can not debug it. Visit our [Custom Training Tutorial](https://docs.ultralytics.com/yolov5/tutorials/train_custom_data) for guidelines on training your custom data. Examine `train_batch0.jpg` and `test_batch0.jpg` for a sanity check of your labels and images.
- **Your environment.** If your issue is not reproducible in one of the verified environments below we can not debug it. If you are running YOLOv5 locally, verify your environment meets all of the [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) dependencies specified below. If in doubt, download Python 3.8.0 from https://www.python.org/, create a new [venv](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/), and then install requirements.
If none of these apply to you, we suggest you close this issue and raise a new one using the **Bug Report template**, providing screenshots and **minimum viable code to reproduce your issue**. Thank you!
## Requirements
Python 3.8 or later with all [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) dependencies installed, including `torch>=1.6`. To install run:
```bash
$ pip install -r requirements.txtEnvironments
YOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):
- Google Colab Notebook with free GPU:
- Kaggle Notebook with free GPU: https://www.kaggle.com/models/ultralytics/yolov5
- Google Cloud Deep Learning VM. See GCP Quickstart Guide
- Docker Image https://hub.docker.com/r/ultralytics/yolov5. See Docker Quickstart Guide
Status
If this badge is green, all YOLOv5 GitHub Actions Continuous Integration (CI) tests are passing. These tests evaluate proper operation of basic YOLOv5 functionality, including training (train.py), testing (test.py), inference (detect.py) and export (export.py) on MacOS, Windows, and Ubuntu.
gofugoo
github-actions[bot]
I trained my custom data on google lab.
python3.8 train.py --data ../data_bbox/data2/custom.yaml --cfg ../data_bbox/data2/yolov5s.yaml --weights ../data_bbox/data2/ys_best_2020_11_15.pt --batch-size 200 --epochs 16000 --rect --img-size 512 --cache-images --hyp runs/evolve/hyp_evolved.yaml --resume