| # EMcopilot: Your label-free copilot for automated electron microscopy image analysis | |
| ## Training and Code Details | |
| For detailed training procedures and source code, please refer to our GitHub repository: | |
| [EMcopilot GitHub Repository](https://github.com/WenhaoYuan337/EMcopilot) | |
| ## Usage | |
| 1. **Train and predict segmentation models**: | |
| * `00_01_sam_binary_masking.py` - Generates coarse masks using the SAM model. | |
| 3. **Generate and analyze synthetic masks**: | |
| * `02_01_sam_mask_analysis.py` - Analyzes SAM mask properties and extracts morphology prior. | |
| * `02_02_random_mask_generate.py` - Generates synthetic masks by augmenting existing masks. | |
| 5. **Generate and evaluate images**: | |
| * `03_01_p2p_train.py` - Trains a Pix2Pix model for mask-to-EMimage translation. | |
| * `04_01_pix2pix_predict.py` - Runs inference using the trained Pix2Pix model. | |
| 6. **Domain Adaptation**: | |
| * `05_01_domain_adaptation.py` - Applies domain adaptation, including noise and contrast augmentation. | |
| 7. **UNet++ Training and Inference**: | |
| * `06_01_unet++_train.py` - Trains a CBAM-enhanced UNet++ model for segmentation. | |
| * `07_01_unet++_predict.py` - Performs inference using the trained UNet++ model. | |
| 8. **Analyze DM4 microscopy data**: | |
| * `08_01_in_situ_analysis.py` - Analyze HAADF-STEM images of supported nanoparticles in real time. | |
| ## Installation | |
| Install required packages using: | |
| ```bash | |
| pip install -r requirements.txt | |
| ``` | |
| ## Citation | |
| If you find our code or data useful in your research, please cite our paper: | |
| ``` | |
| @misc{yuan2024deepgenerativemodelsassistedautomated, | |
| title={Deep Generative Models-Assisted Automated Labeling for Electron Microscopy Images Segmentation}, | |
| author={Wenhao Yuan and Bingqing Yao and Shengdong Tan and Fengqi You and Qian He}, | |
| year={2024}, | |
| eprint={2407.19544}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cond-mat.mtrl-sci}, | |
| url={https://arxiv.org/abs/2407.19544}, | |
| } | |
| ``` | |
| Copyright | 2025 Qian's Lab@NUS | |