datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
amazon-berkeley-objects
Amazon Berkeley Objects (ABO)
A Hugging Face packaging of the Amazon Berkeley Objects (ABO) dataset. The
data content is the official CC BY 4.0 release from
https://amazon-berkeley-objects.s3.amazonaws.com/index.html. This mirror
changes only the packaging: files are grouped into typed Parquet shards, and
every original media file is preserved byte-for-byte and never transcoded.
Images use the datasets Image() feature, 3D product models use the native
Mesh() feature (original… See the full description on the dataset page: https://huggingface.co/datasets/suvadityamuk/amazon-berkeley-objects.kaputt
Kaputt: A Large-Scale Dataset for Visual Defect Detection
Abstract
We present a novel large-scale dataset for defect detection in a logistics
setting. Recent work on industrial anomaly detection has primarily focused on
manufacturing scenarios with highly controlled poses and a limited number of
object categories. Existing benchmarks like MVTec-AD (Bergmann et al., 2021) and
VisA (Zou et al., 2022) have reached saturation, with state-of-the-art methods
achieving… See the full description on the dataset page: https://huggingface.co/datasets/amazon/kaputt.amazon-products
Dataset Creation and Processing Overview
This dataset underwent a comprehensive process of loading, cleaning, processing, and preparing, incorporating a range of data manipulation and NLP techniques to optimize its utility for machine learning models, particularly in natural language processing.
Data Loading and Initial Cleaning
Source: Loaded from the Hugging Face dataset repository bprateek/amazon_product_description.
Conversion to Pandas DataFrame: For ease of data… See the full description on the dataset page: https://huggingface.co/datasets/cvnberk/amazon-products.amazon-from-space
Description
Dataset from the Kaggle Planet: Understanding the Amazon from Space competition (2017). This is the JPG (visual RGB) variant of the release.
The images are 256x256 pixel chips cut from Planet's PlanetScope scenes of the Amazon basin (~3 m ground sample distance). Each chip is tagged with one atmospheric label and zero or more land cover / land use labels.
Labels (17):
atmospheric (exactly one per chip): clear, partly_cloudy, cloudy, haze. Chips tagged cloudy have no… See the full description on the dataset page: https://huggingface.co/datasets/timm/amazon-from-space.amazon-products
Dataset Creation and Processing Overview
This dataset underwent a comprehensive process of loading, cleaning, processing, and preparing, incorporating a range of data manipulation and NLP techniques to optimize its utility for machine learning models, particularly in natural language processing.
Data Loading and Initial Cleaning
Source: Loaded from the Hugging Face dataset repository bprateek/amazon_product_description.
Conversion to Pandas DataFrame: For ease of data… See the full description on the dataset page: https://huggingface.co/datasets/aksingh4539047/amazon-products.