chitra
pytest-visual
chitra | pytest-visual | |
---|---|---|
1 | 1 | |
223 | 16 | |
0.0% | - | |
3.2 | 8.7 | |
about 1 month ago | 26 days ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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chitra
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Answer: Resizing image and its bounding box
Another way of doing this is to use CHITRA
pytest-visual
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[P] Elevate Your ML Testing with pytest-visual
I’ve developed a tool called pytest-visual, aiming to make ML code testing more efficient and meaningful. Traditional unit testing often misses visual and functional aspects of ML workflows such as data augmentation and model structures.
What are some alternatives?
tf-keras-vis - Neural network visualization toolkit for tf.keras
torchview - torchview: visualize pytorch models
img2dataset - Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine.
dvclive - 📈 Log and track ML metrics, parameters, models with Git and/or DVC
gallery - BentoML Example Projects 🎨
nannyml - nannyml: post-deployment data science in python
review_object_detection_metrics - Object Detection Metrics. 14 object detection metrics: mean Average Precision (mAP), Average Recall (AR), Spatio-Temporal Tube Average Precision (STT-AP). This project supports different bounding box formats as in COCO, PASCAL, Imagenet, etc.
tfgraphviz - A visualization tool to show a TensorFlow's graph like TensorBoard
albumentations - Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
receptive_field_analysis_toolbox - A toolbox for receptive field analysis and visualizing neural network architectures
pytorch-toolbelt - PyTorch extensions for fast R&D prototyping and Kaggle farming
tf-explain - Interpretability Methods for tf.keras models with Tensorflow 2.x