How ahojnnes/scikit-image works
scikit-image is a Python image-processing library. Users supply or load image arrays, apply processing and analysis algorithms, and use the resulting images, labels, measurements, or visualizations. Its major capabilities are organized as domain modules rather than a single enforced pipeline, so the graph shows independent processing branches. The tree and README support these subsystem boundaries; sampled source confirms examples of color conversion, thresholding, geometric transforms, feature detection, measurements, drawing, and region-adjacency graphs, but does not establish wiring among all modules.
Main entry points: io Image I/O · viewer Interactive viewer · data Sample data · colorconv.py Color conversion
Components 16
Image input
- Image I/O
skimage/io - Sample data
skimage/data
Image processing
- Color conversion
skimage/color/colorconv.py - Filtering
skimage/filters - Intensity adjustment
skimage/exposure - Geometric transforms
skimage/transform - Restoration
skimage/restoration - Morphology
skimage/morphology
Image analysis
- Segmentation
skimage/segmentation - Feature detection
skimage/feature - Measurement
skimage/measure - Image graphs
skimage/future/graph
Results and viewing
- Raster drawing
skimage/draw/draw.py - Interactive viewer
skimage/viewer
Shared utilities
- Array utilities
skimage/util
Other components
- Python user
Connections 16
- Python user → Image I/O: loads images
- Python user → Sample data: requests samples
- Python user → Color conversion: calls conversions
- Python user → Filtering: calls filters
- Python user → Intensity adjustment: adjusts intensity
- Python user → Geometric transforms: transforms images
- Python user → Restoration: restores images
- Python user → Morphology: applies morphology
- Python user → Segmentation: segments images
- Python user → Feature detection: detects features
- Python user → Measurement: measures regions
- Python user → Image graphs: builds image graphs
- Python user → Raster drawing: draws primitives
- Python user → Interactive viewer: opens viewer
- Python user → Array utilities: uses array helpers
- Image I/O → Interactive viewer: displays images