Read cvat training set
Project description
cvat_reader
Package to read cvat training set zip file into numpy array image and annotations.
The cvat format is usefull because it contains the original video file. The original video file has two main advantage over image files:
- The original video file is much better compressed than a bunch of image files.
- The image files are re-compressed versions of the video file and therefore lower in quality
Install
pip install cvat_reader
Example
import cv2
from cvat_reader import open_cvat
with open_cvat("training.zip") as dataset:
print(dataset.labels)
labels = {}
for label in dataset.labels:
h = label['color'].lstrip('#')
labels[label['name']] = tuple(int(h[i:i + 2], 16) for i in (0, 2, 4))
for frame in dataset:
if frame.annotations:
img = frame.image.copy()
for label in dataset.labels:
for annotation in frame.annotations:
color = labels[annotation.label]
(x1, y1), (x2, y2) = annotation.bounding_box
cv2.rectangle(img, (x1, y1), (x2, y2), color)
cv2.imshow('image', img)
cv2.waitKey(0)
Support
cvat_reader
currently supports the following types of annotations:
- BoundingBox
Media types supported: all types cv2 supports
Changelog
0.1.1 (2021-10-25)
Bugfix:
- data directory sometimes contains non-video files. Those files should not be picked as video files. This bugfix solves this by verifying if cv2 can load the file.
0.1.0 (2021-10-22)
Feature:
- Properly read tracks and interpolate
Project details
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cvat_reader-0.1.1.tar.gz
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