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.
☆1,800Updated 4 months ago
Alternatives and similar repositories for fastdup
Users that are interested in fastdup are comparing it to the libraries listed below
Sorting:
- Images to inference with no labeling (use foundation models to train supervised models).☆2,526Updated 7 months ago
- Automatically find issues in image datasets and practice data-centric computer vision.☆1,134Updated this week
- Code release for "Detecting Twenty-thousand Classes using Image-level Supervision".☆1,990Updated last year
- Computer Vision dataset analysis☆310Updated last year
- Interactively explore unstructured datasets from your dataframe.☆1,210Updated 2 weeks ago
- The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling.☆456Updated 6 months ago
- An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come☆867Updated last year
- Code release for "Cut and Learn for Unsupervised Object Detection and Instance Segmentation" and "VideoCutLER: Surprisingly Simple Unsupe…☆1,050Updated 6 months ago
- MetaSeg: Packaged version of the Segment Anything repository☆987Updated last week
- Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine.☆4,237Updated last month
- 🦘 Explore multimedia datasets at scale☆1,060Updated last year
- Hiera: A fast, powerful, and simple hierarchical vision transformer.☆1,044Updated last year
- Easily compute clip embeddings and build a clip retrieval system with them☆2,705Updated 4 months ago
- SAM with text prompt☆2,499Updated 3 months ago
- Segment Anything Labelling Tool☆1,048Updated last year
- Segment Anything in High Quality [NeurIPS 2023]☆4,135Updated 3 months ago
- Official code for "FeatUp: A Model-Agnostic Frameworkfor Features at Any Resolution" ICLR 2024☆1,616Updated last year
- NeurIPS 2025 Spotlight; ICLR2024 Spotlight; CVPR 2024; EMNLP 2024☆1,770Updated 2 weeks ago
- A curated list of plugins that you can add to your FiftyOne install!☆134Updated last week
- Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.☆652Updated last week
- This repository contains the code of the CVPR 2022 paper "Image Segmentation Using Text and Image Prompts".☆1,300Updated last year
- [CVPR 2023] Official Implementation of X-Decoder for generalized decoding for pixel, image and language☆1,337Updated 2 years ago
- FFCV: Fast Forward Computer Vision (and other ML workloads!)☆2,988Updated last year
- Robust fine-tuning of zero-shot models☆756Updated 3 years ago
- Grounded Language-Image Pre-training☆2,553Updated last year
- Tools for converting Label Studio annotations into common dataset formats☆294Updated last year
- [ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model☆1,928Updated last year
- Automated dense category annotation engine that serves as the initial semantic labeling for the Segment Anything dataset (SA-1B).☆2,297Updated 2 years ago
- Personalize Segment Anything Model (SAM) with 1 shot in 10 seconds☆1,638Updated last year
- [NeurIPS 2023] Official implementation of the paper "Segment Everything Everywhere All at Once"☆4,754Updated last year