fastdup
CVPR2024-Papers-with-Code
| fastdup | CVPR2024-Papers-with-Code | |
|---|---|---|
| 18 | 1 | |
| 1,408 | 16,155 | |
| 1.0% | - | |
| 9.4 | 6.5 | |
| 28 days ago | 9 days ago | |
| Python | ||
| GNU General Public License v3.0 or later | - |
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fastdup
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Visualize your dataset using DINOv2 embedding
Visualizing your dataset (especially large ones) in a low-dimensional embedding space can tell you a lot about the patterns and clusters in your dataset.
We recently release a notebook showing how you can visualize your dataset using DINOv2 models by running it on your CPU.
Yes! No GPUs needed.
We used it to find clusters of similar images, duplicates, and outliers in a subset of the LAION dataset
Try it on your own dataset:
Colab notebook - https://colab.research.google.com/github/visual-layer/fastdup/blob/main/examples/dinov2_notebook.ipynb
GitHub repo - https://github.com/visual-layer/fastdup
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[R][P] How to extract feature vectors of large datasets using DINOv2 on CPU
Run 1M images from the LAION dataset through the DINOv2 model and cluster the images using a free tool - fastdup.
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Computer Vision pre-trained model for finding how similar two photos of a room are
Another option could be fastdup (https://github.com/visual-layer/fastdup) which is probably most helpful for analysis type objectives.
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Find image duplicates and outliers – A free, scalable, efficient tool
I recently stumbled upon fastdup a tool that lets you gain insights from a large image/video collection.
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How can we match images in our database?
There is this fastdup framework which supposedly allows you to find duplicates and similar images. i haven't used it though
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Measure Images Similarity
I came across fastdup recently https://github.com/visual-layer/fastdup
- Dedup-ing LAION (60M duplicates) and ImageNet (1.2M duplicates) with fastdup
- [R] Dedup-ing LAION (60M duplicates) and ImageNet (1.2M duplicates) with fastdup
CVPR2024-Papers-with-Code
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23 useful GitHub Repos every developer should follow
Repo Link: https://github.com/amusi/CVPR2021-Papers-with-Code
What are some alternatives?
sahi - Framework agnostic sliced/tiled inference + interactive ui + error analysis plots
best_AI_papers_2021 - A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.
computervision-recipes - Best Practices, code samples, and documentation for Computer Vision.
tinyml-papers-and-projects - This is a list of interesting papers and projects about TinyML.
pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
freeCodeCamp - freeCodeCamp.org's open-source codebase and curriculum. Learn to code for free.
dhash - Python library to calculate the difference hash (perceptual hash) for a given image, useful for detecting duplicates
Computer-Vision-Video-Lectures - A curated list of free, high-quality, university-level courses with video lectures related to the field of Computer Vision.
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
realworld - "The mother of all demo apps" — Exemplary fullstack Medium.com clone powered by React, Angular, Node, Django, and many more
plakakia - Python image tiling library for image processing, object detection, etc.
AvatarMe - Public repository for the CVPR 2020 paper AvatarMe and the TPAMI 2021 AvatarMe++