cimp-denoise weights

Weights for the denoise command from the cimp-denoise package (code: 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.