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.
☆1,724Updated 3 weeks 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).☆2,385Updated 3 months ago
- Automatically find issues in image datasets and practice data-centric computer vision.☆1,108Updated 5 months ago
- The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling.☆453Updated 3 months ago
- Code release for "Cut and Learn for Unsupervised Object Detection and Instance Segmentation" and "VideoCutLER: Surprisingly Simple Unsupe…☆1,028Updated 3 months ago
- MetaSeg: Packaged version of the Segment Anything repository☆984Updated last week
- Code release for "Detecting Twenty-thousand Classes using Image-level Supervision".☆1,970Updated last year
- Computer Vision dataset analysis☆304Updated last year
- Personalize Segment Anything Model (SAM) with 1 shot in 10 seconds☆1,615Updated last year
- An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come☆865Updated 9 months ago
- Segment Anything Labelling Tool☆1,047Updated last year
- Segment Anything in High Quality [NeurIPS 2023]☆4,061Updated 2 months ago
- Hiera: A fast, powerful, and simple hierarchical vision transformer.☆1,020Updated last year
- Easily compute clip embeddings and build a clip retrieval system with them☆2,641Updated 3 weeks ago
- SAM with text prompt☆2,368Updated last week
- A python library for self-supervised learning on images.☆3,524Updated 3 weeks ago
- 🦘 Explore multimedia datasets at scale☆1,064Updated 9 months ago
- This repository is a curated collection of the most exciting and influential CVPR 2023 papers. 🔥 [Paper + Code]☆655Updated 3 months ago
- The implementation of "Prismer: A Vision-Language Model with Multi-Task Experts".☆1,309Updated last year
- [CVPR 2023] OneFormer: One Transformer to Rule Universal Image Segmentation☆1,660Updated 11 months ago
- Official code for "FeatUp: A Model-Agnostic Frameworkfor Features at Any Resolution" ICLR 2024☆1,576Updated last year
- Automatically create Faiss knn indices with the most optimal similarity search parameters.☆870Updated last year
- Robust fine-tuning of zero-shot models☆735Updated 3 years ago
- Automated dense category annotation engine that serves as the initial semantic labeling for the Segment Anything dataset (SA-1B).☆2,274Updated 2 years ago
- [ECCV 2024] Official implementation of the paper "Semantic-SAM: Segment and Recognize Anything at Any Granularity"☆2,717Updated last month
- FFCV: Fast Forward Computer Vision (and other ML workloads!)☆2,961Updated last year
- [CVPR 2023] Official Implementation of X-Decoder for generalized decoding for pixel, image and language☆1,328Updated last year
- Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine.☆4,147Updated this week
- [NeurIPS 2023] Official implementation of the paper "Segment Everything Everywhere All at Once"☆4,712Updated last year
- Data Labeling, Tracking and Annotation with AI☆350Updated last year
- [ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model☆1,891Updated 9 months ago