SaaSHub helps you find the best software and product alternatives Learn more →
Fastdup Alternatives
Similar projects and alternatives to fastdup
-
CLIP
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
-
computervision-recipes
Discontinued Best Practices, code samples, and documentation for Computer Vision.
-
dhash
Python library to calculate the difference hash (perceptual hash) for a given image, useful for detecting duplicates
-
WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
-
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
-
flockfysh
Discontinued A simple data vending machine that pops more out that what comes in. Use flockfysh to seamlessly pool existing datasets with quality web-scraped data to get top notch datasets.
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
fastdup reviews and mentions
-
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
-
[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.
-
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.
-
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.
-
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
-
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
-
A note from our sponsor - SaaSHub
www.saashub.com | 19 Apr 2024
Stats
visual-layer/fastdup is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
The primary programming language of fastdup is Python.