Cellpose Cpsam Onnx

--- license: bsd-3-clause license_name: bsd-3-clause-code-cc-by-nc-data library_name: onnx tags: - cellpose - cell-segmentation - microscopy - onnx - biology pipeline_tag: image-segmentation --- # Cellpose cpsam — ONNX ONNX export of the [Cellpose](https://github.com/MouseLand/cellpose) **cpsam** (Cellpose-SAM) model for cell segmentation in microscopy images. ## Model Details - **Architecture**: ViT-L based Transformer (SAM backbone + Cellpose readout) - **Parameters**: 304M - **Input**: `pixel_values` — float32 tensor `(1, 3, 256, 256)` (one tile) - **Output**: `output` — float32 tensor `(1, 3, 256, 256)` — channels are `(dY, dX, cellprob)` - **Opset**: 14 The model weights are stored as external data (`model.onnx.data`) due to the 2GB protobuf limit. Both files must be in the same directory for inference. ## Usage ### Python (onnxruntime) ```python import onnxruntime as ort import numpy as np sess = ort.InferenceSession("model.onnx", providers=["CUDAExecutionProvider"]) tile = np.zeros((1, 3, 256, 256), dtype=np.float32) # your preprocessed tile output = sess.run(None, {"pixel_values": tile})[0] # (1, 3, 256, 256) dY, dX, cellprob = output[0, 0], output[0, 1], output[0, 2] ``` ### Rust (cellpose-rs) ```rust use cellpose_rs::{CellposeSession, SegmentParams, preprocess}; let mut session = CellposeSession::new(Path::new("model.onnx"), false)?; let chw = preprocess::build_chw_image(phase, fluo, h, w); let masks = session.segment(&chw, h, w, SegmentParams::default())?; ``` See [cellpose-rs](https://github.com/keejkrej/cellpose-rs) for the full Rust inference library. ## Post-processing The raw output requires Cellpose flow dynamics post-processing: 1. Threshold `cellprob > 0` to get foreground 2. Scale flows: `dP = dP * foreground / 5.0` 3. 200-step Euler integration with bilinear interpolation 4. Histogram-based seed detection (max-pool kernel=5, threshold=10) 5. Connected-component labelling of seeds 6. Assign each foreground pixel to its nearest seed 7. Remove masks >40% of image area, fill holes, remove masks <15px ## License The Cellpose **code** is © 2020 Howard Hughes Medical Institute, licensed under the [BSD 3-Clause License](https://github.com/MouseLand/cellpose/blob/main/LICENSE). ⚠️ The Cellpose-SAM model is trained on data licensed under **CC-BY-NC**. See the [upstream notice](https://gi...