Python utility package for common computer vision tasks.
Project description
vito - Vision Tools
Python utilities for common computer vision tasks. The goal of this package is to provide a lightweight, python-only package helping you with standard/recurring image manipulation tasks.
Dependencies
numpy
PIL
Examples
- Pseudocoloring:
from vito import imutils
from vito import imvis
# Load a single-channel image
peaks = imutils.imread('peaks.png', mode='L')
# Colorize it
colorized = imvis.pseudocolor(peaks, limits=None, color_map=colormaps.colormap_parula_rgb)
imvis.imshow(colorized)
- Optical flow:
from vito import flow
from vito import imvis
# Load optical flow file
flow_uv = flow.floread('color_wheel.flo')
# Colorize it
colorized = flow.flow_to_color(flow_uv)
imvis.imshow(colorized)
Changelog
0.2.0
- Optical flow (Middlebury .flo format) I/O and visualization
- Support saving images
- Colorization to visualize tracking results
0.1.1
- Changed supported python versions for legacy tests
0.1.0
- First actually useful release
- Contains most of the functionality of
pvt
(a library I developed throughout my studies)cam_projections
- projective geometry, lens distortion/rectification (Plumb Bob model), etc.colormaps
- colormap definitions for visualization (jet, parula, magma, viridis, etc.)imutils
- image loading, conversion, RoI handling (e.g. apply functions on several patches of an image)imvis
- visualization helpers, e.g. pseudocoloring or overlaying imagespyutils
- common python functions (timing code, string manipulation, list sorting/search, etc.)
0.0.1
- Initial public release
- Contains common python/language and camera projection utils
TODO List
- anonymization utils
- augmentation
Project details
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