tessl/pypi-scikit-image

Comprehensive image processing and computer vision library for Python with algorithms for filtering, morphology, segmentation, and feature detection

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Name: tessl/pypi-scikit-image
Author: tessl

Example images, datasets, and synthetic data generation functions for testing algorithms, learning image processing techniques, and algorithm development.

Capabilities

Standard Test Images

def camera():
    """512×512 grayscale cameraman image."""

def astronaut():
    """512×512 color astronaut image."""

def coins():
    """303×384 grayscale coins image."""

def checkerboard():
    """200×200 checkerboard pattern."""

def horse():
    """328×400 binary horse silhouette."""

def rocket():
    """121×81 grayscale rocket image."""

def cat():
    """300×451 color cat image."""

def coffee():
    """400×600 color coffee image."""

Scientific Images

def brain():
    """Brain MRI slice."""

def cell():
    """Fluorescence microscopy cell image."""

def cells3d():
    """3D fluorescence cell image stack."""

def hubble_deep_field():
    """Hubble space telescope deep field image."""

Synthetic Data Generation

def binary_blobs(length=512, blob_size_fraction=0.1, n_dim=2, volume_fraction=0.5, seed=None):
    """Generate synthetic binary image with blob-like objects."""

def shepp_logan_phantom():
    """Generate Shepp-Logan phantom for tomography."""

Utilities

def data_dir():
    """Path to data directory."""

def download_all():
    """Download all remote datasets."""

Types

from numpy.typing import NDArray
import numpy as np

TestImage = NDArray[np.number]
SyntheticImage = NDArray[np.number]

Install with Tessl CLI

npx tessl i tessl/pypi-scikit-image

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