visual-layer / fastdupLinks
fastdup is a powerful, free tool designed to rapidly generate valuable insights from image and video datasets. It helps enhance the quality of both images and labels, while significantly reducing data operation costs, all with unmatched scalability.
☆1,706Updated last week
Alternatives and similar repositories for fastdup
Users that are interested in fastdup are comparing it to the libraries listed below
Sorting:
- Automatically find issues in image datasets and practice data-centric computer vision.☆1,103Updated 3 months ago
- Images to inference with no labeling (use foundation models to train supervised models).☆2,335Updated 2 months ago
- Code release for "Detecting Twenty-thousand Classes using Image-level Supervision".☆1,956Updated last year
- The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling.☆452Updated 2 months ago
- MetaSeg: Packaged version of the Segment Anything repository☆985Updated this week
- Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine.☆4,104Updated 11 months ago
- An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come☆860Updated 8 months ago
- Easily compute clip embeddings and build a clip retrieval system with them☆2,606Updated last year
- Code release for "Cut and Learn for Unsupervised Object Detection and Instance Segmentation" and "VideoCutLER: Surprisingly Simple Unsupe…☆1,021Updated last month
- Computer Vision dataset analysis☆302Updated 11 months ago
- A python library for self-supervised learning on images.☆3,478Updated this week
- This repository is a curated collection of the most exciting and influential CVPR 2023 papers. 🔥 [Paper + Code]☆656Updated last month
- Segment Anything Labelling Tool☆1,049Updated last year
- 🦘 Explore multimedia datasets at scale☆1,061Updated 7 months ago
- ICLR2024 Spotlight: curation/training code, metadata, distribution and pre-trained models for MetaCLIP; CVPR 2024: MoDE: CLIP Data Expert…☆1,484Updated this week
- Robust fine-tuning of zero-shot models☆724Updated 3 years ago
- Segment Anything in High Quality [NeurIPS 2023]☆4,021Updated 3 weeks ago
- Personalize Segment Anything Model (SAM) with 1 shot in 10 seconds☆1,601Updated last year
- FFCV: Fast Forward Computer Vision (and other ML workloads!)☆2,950Updated last year
- The implementation of "Prismer: A Vision-Language Model with Multi-Task Experts".☆1,308Updated last year
- [CVPR 2023] OneFormer: One Transformer to Rule Universal Image Segmentation☆1,643Updated 9 months ago
- [CVPR 2023] Official Implementation of X-Decoder for generalized decoding for pixel, image and language☆1,324Updated last year
- Easy & Modular Computer Vision Detectors, Trackers & SAM - Run YOLOv9,v8,v7,v6,v5,R,X in under 10 lines of code.☆615Updated last year
- Automatically create Faiss knn indices with the most optimal similarity search parameters.☆867Updated last year
- A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.☆2,707Updated last month
- Hiera: A fast, powerful, and simple hierarchical vision transformer.☆1,004Updated last year
- Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.☆4,836Updated 10 months ago
- Official codebase used to develop Vision Transformer, SigLIP, MLP-Mixer, LiT and more.☆3,032Updated 2 months ago
- Grounded Language-Image Pre-training☆2,468Updated last year
- [NeurIPS 2023] Official implementation of the paper "Segment Everything Everywhere All at Once"☆4,664Updated 11 months ago