Active Learning with Auto Labeling
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Updated
Jan 20, 2022 - Python
Active Learning with Auto Labeling
Awesome (Image/Video) Interactive Segmentation for Auto Labeling and Annotation
This work generates 2D and 3D landmark labels from videos with only two or three uncalibrated, handheld cameras moving in the wild. NeurIPS 2022.
The Official PyTorch Implementation of DiscoBox.
Channel state information Auto-Labeling System
It's a simulator based on Unity for RoboMaster. You can use it to get some labeled dataset for deep learning
Synthetic dataset generation with Stable Diffusion and generating of segmentation mask using Grounding DINO and Segment Anythin Model
⚡️ Automates the process of assigning labels to your pull requests based on the target branch
🏗 hCaptcha image label binary model factory (PyTorch Training, Cluster-based Auto Label Tools, Export ONNX model, ONNX model inference)
Recognize Any Regions
Promises and Pitfalls of Threshold-based Auto-labeling ( NeurIPS 2023)
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).
A smart automated GitHub bot for managing GitHub projects.
Images to inference with no labeling (use foundation models to train supervised models).
Effortless AI-assisted data labeling with AI support from YOLO, Segment Anything, MobileSAM!!
Easiest way to use AI models without coding (Web UI & API support)
An open source python library for automated prediction engineering
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