ttach
albumentations
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ttach | albumentations | |
---|---|---|
1 | 28 | |
938 | 13,272 | |
- | 1.8% | |
0.0 | 8.3 | |
8 months ago | 5 days ago | |
Python | Python | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ttach
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Setting up Google Colab for Deep Learning
While Colab usually comes pre-installed with most of the basic dependencies like Tensorflow, PyTorch, scikit-learn, pandas and many more, there are chances that you have to install external packages at times. You can do that using the !pip install command. For example we can install the ttach library which is used for augmentation of images during test phase. This can be done using:
albumentations
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Augment specific classes?
You can use albumentations if you are comfortable with using open source libraries https://github.com/albumentations-team/albumentations
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Ask HN: What side projects landed you a job?
One of the members of the core team of our open-source library https://albumentations.ai/
It was not the only reason he was hired; it was a solid addition to his already good performance at the interviews.
Or at least that is what the hiring manager later said.
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The Lack of Compensation in Open Source Software Is Unsustainable
I am one of the creators and maintainers of https://albumentations.ai/.
- 12800+ stars
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Burn Deep Learning Framework Release 0.7.0: Revamped (de)serialization, optimizer & module overhaul, initial ONNX support and tons of new features.
Is something planned to support data augmentations? Something like https://albumentations.ai/
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What are the best programs/scripts for image augmentation of YOLO5 training dataset. Something like roboflow but free)
I think this is the most popular open source project: https://github.com/albumentations-team/albumentations
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Data augmentation PyTorch transforms for object detection data with bounding boxes
The other common one is Albumentations and many modern object detection models perform online augmentation during the training process.
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DATA AUGMENTATION IN NATURAL LANGUAGE PROCESSING
Shuffle Sentences Transform:- it involves the shuffling of sentences in the text to create an augmented version of the original text, this technique can be achieved using the Albumentation package.
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[P] Albumentations 1.0 is released (a Python library for image augmentation)
Full release notes: https://github.com/albumentations-team/albumentations/releases/tag/1.0.0
If you want to know what changed in the latest versions, please refer to the [Release Notes](https://github.com/albumentations-team/albumentations/releases) page.
What are some alternatives?
imgaug - Image augmentation for machine learning experiments.
YOLO-Mosaic - Perform mosaic image augmentation on data for training a YOLO model
labelme2coco - A lightweight package for converting your labelme annotations into COCO object detection format.
autoalbument - AutoML for image augmentation. AutoAlbument uses the Faster AutoAugment algorithm to find optimal augmentation policies. Documentation - https://albumentations.ai/docs/autoalbument/
Mask-RCNN-TF2 - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow 2.0
BlenderProc - A procedural Blender pipeline for photorealistic training image generation
image-statistics-matching - Methods for alignment of global image statistics aimed at unsupervised Domain Adaptation and Data Augmentation
TTNet-Real-time-Analysis-System-for-Table-Tennis-Pytorch - Unofficial implementation of "TTNet: Real-time temporal and spatial video analysis of table tennis" (CVPR 2020)
cvlib - A simple, high level, easy to use, open source Computer Vision library for Python.
SickZil-Machine - Manga/Comics Translation Helper Tool
VoTT - Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.