一个功能完整的 SemanticKITTI 数据集处理工具包，支持点云可视化、语义分割评估和多种数据格式转换。
Offline-first edge vision engineering workbench for YOLO data, experiments, benchmarking, and RDK X5/Linux delivery on macOS.
All-in-one AI workbench program for Vision AI model inference, evaluation, benchmarking, optimization & dataset management
Image board browser to search up references for SD models.
Dataset operations and release-governance toolchain for the HeOCR Hebrew OCR/HTR ecosystem.
Standalone Python scripts for computer vision: image augmentation (rotate, flip, perspective with Pillow/OpenCV), dataset splitting (scikit-learn), and model testing (TensorFlow + matplotlib).
Waveform Database (WFDB) implementation in pure Rust.
TGC developer: t.me/forget_git
OpenAxiom — A local PySide6 UI Lab annotation MVP and batch-safe YOLO label tool.
Some small tools that you might need when cleaning data and creating training sets.大家在进行数据清洗和训练集制造时可能会需要的一些小工具。
Automatically translate structured datasets (CSV, JSON, JSONL, TSV, Parquet) using LLMs via Ollama — with caching, parallelism, checkpointing, and retry support.
Utility tools for dataset preparation and management, including image renaming, CSV to Excel conversion, and AI-powered image labeling.
Dataset cleaning, merging, splitting and labeling tools for YOLO workflows
Browser-local computer-vision annotation examples, validators, converters, and dataset templates for COCO, YOLO, Pascal VOC, and MOT.
Offline image batch processing and augmentation toolkit — YAML-driven, reproducible, metadata-traceable pipelines for pre-training data preparation.
Modular desktop toolkit for image collection curation — dataset prep, quality scoring, deduplication, cropping, and more.
An interactive desktop tool (Python/PyQt6) to run YOLO object detection, visualize results, and automatically crop images. Perfect for streamlining dataset preparation!
Toolkit for extracting Fandom wiki dialogue and web text into fine-tuning datasets for local LLMs
Open-source data annotation tools for computer vision, image annotation, COCO to CVAT conversion, bounding boxes, semantic segmentation and AI dataset preparation by US-DATA.
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