Use PaliGemma to auto-label data for use in training fine-tuned vision models.
-
Updated
Jun 11, 2024 - Python
Use PaliGemma to auto-label data for use in training fine-tuned vision models.
EdgeSAM model for use with Autodistill.
RaidexAI is a Next.js application integrated with a machine learning model, YOLOv8, to detect anomalies in radiology images. The output is sent to a Flask server, which uses OpenCV to create Regions of Interest (ROIs) in the images and employs a Language Model (LLM) for contextual analysis, interpreting the content alongside the detected anomalies
An intuitive Python tool for annotating images with bounding boxes. Easily assign custom classes to objects and save annotations. Includes AI model integration for automated annotation. Perfect for streamlining computer vision projects. classes to these objects, and save annotations.
Application de détection de bateaux à partir de vues aériennes utilisant Yolov8.
FastViT base model for use with Autodistill.
Grounding DINO module for use with Autodistill.
GPT-4o (with Vision) module for use with Autodistill.
GroundedSAM Base Model plugin for Autodistill
CoDet base model for use with Autodistill.
OWLv2 base model for use with Autodistill.
EfficientSAM base model for use with Autodistill.
YOLO World base module for use with Autodistill.
YOLO-NAS module for use with Autodistill.
Use models on Roboflow Universe to auto-label data for use in model training.
Qwen-VL base model for use with Autodistill.
BioCLIP base model for use with Autodistill.
LLaVA base model for use with Autodistill.
A template for use in creating Autodistill Target Model packages.
Add a description, image, and links to the autodistill topic page so that developers can more easily learn about it.
To associate your repository with the autodistill topic, visit your repo's landing page and select "manage topics."