seung-lab
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crackle
Public3D dense segmentation compression codec based on crack codes.seuron
Public- Serialize dict of integers to bytes and read with near zero parsing. Specialization for int to int.
cloud-volume
PublicRead and write Neuroglancer datasets programmatically.- compressed_segmentation for Neuroglancer volumes. This is the PyPI package fork.
- Skeletonize densely labeled 3D image segmentations with TEASAR. (Medial Axis Transform)
network-speed
Public- Threaded Python and CLI client library for AWS S3, Google Cloud Storage (GCS), in-memory, and the local filesystem.
- Scalable Neuroglancer compatible Downsampling, Meshing, Skeletonizing, Contrast Normalization, Transfers and more.
- Dijkstra's Shortest Path for 6, 18, and 26-Connected 3D (Volumetric) Image Volumes
- Compresso: Efficient Compression of Segmentation Data For Connectomics
- Multiplatform 3D numpy image browser based viewer with voxel painting.
- Connected components on discrete and continuous multilabel 3D & 2D images. Handles 26, 18, and 6 connected variants; periodic boundaries (4, 8, & 6)
- Remap, mask, renumber, unique, and in-place transposition of 3D labeled images. Point cloud too.
DracoPy
Public- Zebrafish Hindbrain Connectome
- Compose chunk operators to create a pipeline for local or distributed petabyte-scale computation
- Marching Cubes & Mesh Simplification on multi-label 3D images.
- Multilabel and Grey 3D morphological image processing functions. Dilate, Erode, Opening, Closing.
- A unified framework for skeletonization, morphological analysis, and connectivity analysis.
- Cython bindings for fpzip, a floating point image compression algorithm.
- Euclidean distance & signed distance transform for multi-label 3D anisotropic images using marching parabolas.