| --- |
| license: cc-by-4.0 |
| tags: |
| - electron-microscopy |
| - stem |
| - denoising |
| - flow-matching |
| library_name: pytorch |
| --- |
| |
| # cimp-denoise weights |
|
|
| Weights for the `denoise` command from the `cimp-denoise` package |
| (code: [github.com/benke97/cimp-denoise](https://github.com/benke97/cimp-denoise)). It denoises STEM images by |
| rendering a frame as it would look after a longer exposure. The model is a conditional flow-matching U-Net (x2x), |
| steered by CMMP, a frozen encoder that describes an acquisition from its metadata or from the image itself. |
|
|
| | file | what it is | trained from | |
| |---|---|---| |
| | `cmmp.pt` | frozen CMMP encoder pair (image + 7-number acquisition metadata) | CMMP | |
| | `x2x.pt` | flow denoiser, metadata mode | `x2x_v2_local` ep500 | |
| | `x2x_cmmp.pt` | flow denoiser, CMMP mode (also trained with CMMP image embeddings as sources) | `x2x_v3_imgsrc` ep100 | |
| | `supervised.pt` | supervised denoiser; supplies the "clean look" target in CMMP mode | `sup_v1` ep100 | |
|
|
| ## Use |
|
|
| ``` |
| pip install git+https://github.com/benke97/cimp-denoise |
| denoise frame.emd # downloads these files to ~/.cache/cimp-denoise on first use |
| ``` |
|
|
| Defaults: 8 draws × 4 sampler steps, about 5 s per 512 × 512 px and 90 s per 2048 × 2048 px on a desktop GPU. |
| Metadata mode (Velox .emd) is told min(recorded dwell, 1 µs) → 16× that. CMMP mode needs only the image. |
|
|
| ## Limitations |
|
|
| - Trained on HAADF data from one microscope. BF and DF channels are processed, but the models were not trained on them. |
| - Very faint lattice fringes near the noise level can be smoothed away. |
| - Images must be at least 128 px per side. |
|
|
