Effortless AI-assisted data labeling with AI support from YOLO, Segment Anything (SAM+SAM2), MobileSAM!!
Images to inference with no labeling (use foundation models to train supervised models).
A continuously updated collection of CodeLLM papers maintained by PurCL group @ Purdue
Recognize Any Regions
The Official PyTorch Implementation of DiscoBox.
It's a simulator based on Unity for RoboMaster. You can use it to get some labeled dataset for deep learning
🏗 hCaptcha image label binary model factory (PyTorch Training, Cluster-based Auto Label Tools, Export ONNX model, ONNX model inference)
Easiest way to use AI models without coding (Web UI & API support)
An open source python library for automated prediction engineering
This work generates 2D and 3D landmark labels from videos with only two or three uncalibrated, handheld cameras moving in the wild. NeurIPS 2022.
Centralized Reusable GitHub Actions
HuaHuoLabel is a multifunctional AI data label tool, which supports data label of five computer vision tasks, including single-category classification, multi-category classification, semantic segmentation, object detection and instance segmentation. It can also do image editing, dataset management, auto-labeling, and pseudo label generation.
This code is for converting COCO json annotations to YOLO txt format (which both are common in object detection projects).
Promises and Pitfalls of Threshold-based Auto-labeling (NeurIPS 2023, Spotlight)
A smart automated GitHub bot for managing GitHub projects.
An simplified and automation labeling tool
Pearls from Pebbles: Improved Confidence Functions for Auto-labeling (NeurIPS 2024)
Awesome (Image/Video) Interactive Segmentation for Auto Labeling and Annotation
Automate video data creation. Extract frames, generate annotations, export in various formats (YOLOv8, YOLO1.1). Integrate with Roboflow, CVAT. Built with Python and Streamlit.
Synthetic dataset generation with Stable Diffusion and generating of segmentation mask using Grounding DINO and Segment Anythin Model
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