Segmentation datasets
For an open source dataset for image segmentation, the strongest matches are openimages/dataset (Open Images is a large-scale computer vision dataset that), albertpumarola/3dpeople-dataset (This dataset contains ~2 million images with pixel-level body) and cvdfoundation/open-images-dataset (The Open Images Dataset provides pixel-level segmentation masks and). Each is ranked by relevance to your query, popularity and recent activity.
Find the best open-source segmentation datasets for computer vision. Compare top-rated options by task, format, and activity to find the best fit.
Segmentation datasets
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- openimages/dataset
openimages/dataset
4,366View on GitHubThis project is a computer vision dataset and image annotation repository designed for training and evaluating machine learning models. It provides a large collection of labeled images, serving as an object detection benchmark and a source of pixel-level segmentation data. The repository distinguishes itself as a multimodal visual dataset by pairing images with synchronized voice, text, and mouse traces to support narrative understanding. It further enables the analysis of model fairness through the inclusion of demographic attributes and exhaustive annotations. The dataset covers a broad ra
Open Images is a large-scale computer vision dataset that provides pixel-level segmentation annotations across multiple object categories, directly matching your search for an open-source image segmentation dataset for training and evaluation.
PythonDiverse Visual DatasetsImage LabelingComputer Vision Benchmarks - albertpumarola/3dpeople-dataset
albertpumarola/3DPeople-Dataset
First dataset of dressed humans with specific geometry representation for the clothes. It contains ~2 Million images with 40 male/40 female performing 70 actions. Every subject-action sequence is captured from 4 camera views and annotated with: RGB, 3D skeleton, body part and cloth segmentation…
This dataset contains ~2 million images with pixel-level body part and cloth segmentation, multiple object categories, and a large scale, making it a direct fit for training and evaluating image segmentation models.
Jupyter Notebook3D Human Mesh RecoveryHuman Digitalization - cvdfoundation/open-images-dataset
cvdfoundation/open-images-dataset
1,104View on GitHubThis project provides a collection of command-line tools and scripts designed to automate the ingestion, migration, and preparation of large-scale annotated image datasets. It serves as a utility for managing the retrieval of image collections paired with bounding box and segmentation annotations, facilitating their integration into machine learning data pipelines. The toolset enables the bulk transfer of image data and metadata manifests into private cloud storage environments. It utilizes manifest-driven orchestration to process structured resource locations, ensuring that raw image files r
The Open Images Dataset provides pixel-level segmentation masks and hundreds of object categories at scale, making it a strong candidate for training and evaluating image segmentation models.
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