Welcome to MMYOLO’s documentation!¶
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Get Started
Recommended Topics
- Contributing to OpenMMLab
- Model design instructions
- Algorithm principles and implementation
- Replace the backbone network
- Model Complexity Analysis
- Annotation-to-deployment workflow for custom dataset
- 1. Prepare custom dataset
- 2. Use the software of labelme to annotate
- 3. Convert the dataset into COCO format
- 4. Divide dataset into training set, validation set and test set
- 5. Create a new config file based on the dataset
- 6. Visual analysis of datasets
- 7. Optimize Anchor size
- 8. Visualization the data processing part of config
- 9. Train
- 10. Inference
- 11. Deployment
- Appendix
- Visualization
- MMDeploy deployment tutorial
- EasyDeploy deployment tutorial
- Troubleshooting steps for common errors
- MMYOLO industry examples
- MM series repo essential basics
- Dataset preparation and description
Common Usage
- Resume training
- Automatic mixed precision（AMP）training
- TTA Related Notes
- Plugins
- Freeze layers
- Output prediction results
- Set the random seed
- Module combination
- Use mim to run scripts from other OpenMMLab repositories
- Apply multiple Necks
- Specify specific GPUs during training or inference
- Single and multi-channel application examples
Useful Tools
Basic Tutorials
Advanced Tutorials
API Reference