datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
DataCompDR-1B
Dataset Card for DataCompDR-1B
This dataset contains synthetic captions, embeddings, and metadata for DataCompDR-1B.
The metadata has been generated using pretrained image-text models on DataComp-1B.
For details on how to use the metadata, please visit our github repository.
Dataset Details
Dataset Description
DataCompDR is an image-text dataset and an enhancement to the DataComp dataset.
We reinforce the DataComp dataset using our multi-modal… See the full description on the dataset page: https://huggingface.co/datasets/apple/DataCompDR-1B.Apples_HSI
Hyperspectral Imaging for Quality Assessment of Processed Foods: A Case Study on Sugar Content in Apple Jam
This repository accompanies our study on non-destructive sugar content estimation in apple jam using VNIR hyperspectral imaging (HSI) and machine learning. It includes a reproducible set of Jupyter notebooks covering preprocessing, dataset construction, and model training/evaluation with classical ML and deep learning.
Dataset
The Apples_HSI dataset is… See the full description on the dataset page: https://huggingface.co/datasets/issai/Apples_HSI.DataCompDR-12M
Dataset Card for DataCompDR-12M
This dataset contains synthetic captions, embeddings, and metadata for DataCompDR-12M.
The metadata has been generated using pretrained image-text models on a 12M subset of DataComp-1B.
For details on how to use the metadata, please visit our github repository.
The dataset with the original captions is now available at mlfoundations/DataComp-12M.
The UIDs per shards match between mlfoundations/DataComp-12M and apple/DataCompDR-12M.… See the full description on the dataset page: https://huggingface.co/datasets/apple/DataCompDR-12M.AppleGrowthVision
Dataset Card for AppleGrowthVision
This is a FiftyOne dataset with 11,397
groups (21,407 samples) of apple orchard imagery.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("Voxel51/AppleGrowthVision")
# Launch the App
session =… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/AppleGrowthVision.Apple-PI-GT
Apple-π: Benchmarking Thinking with VideoTowards Law-Grounded Physical Intelligence
Runmao Yao*, Kairui Hu*, Yukang Cao, Ruisi Wang,
Shulin Tian, Ziang Cao, Weichen Fan,
Ziqi Huang, Yuhao Dong, Hao Li, Zhaoxi Chen, Zhongang Cai,
Lei Yang, Ziwei Liu†
S-Lab, Nanyang Technological University · The Chinese University of Hong Kong
*Equal contribution · †Corresponding author… See the full description on the dataset page: https://huggingface.co/datasets/yaorunmao/Apple-PI-GT.DORI-Benchmark
Dataset Details
Dataset Description
DORI (Discriminative Orientation Reasoning Intelligence) is a comprehensive benchmark designed to evaluate object orientation understanding in multimodal large language models (MLLMs). The benchmark isolates and evaluates orientation perception as a primary capability, offering a systematic assessment framework that spans four essential dimensions of orientation comprehension: frontal alignment, rotational transformations… See the full description on the dataset page: https://huggingface.co/datasets/appledora/DORI-Benchmark.g1-apple2plate-teleoperationST-Align-Datasetapple_synDFNDR-12M
Dataset Card for DFNDR-12M
This dataset contains synthetic captions, embeddings, and metadata for DFNDR-12M.
The metadata has been generated using pretrained image-text models on DFN-12M, a uniformly sampled subset of 12.8M samples from DFN-2B.
For details on how to use the metadata, please visit our ml-mobileclip repository.
For code to generate multi-modal reinforced datasets at large scale see ml-mobileclip-dr repository.
A BFloat16 version of this dataset is available at… See the full description on the dataset page: https://huggingface.co/datasets/apple/DFNDR-12M.VBVR-Reorganized-Image
VBVR-Reorganized-Image
Image-mode derivative of VBVR-Reorganized.
Each sample is a triple (first_frame.png, prompt.txt, final_frame.png):
the model takes first_frame + prompt as input and should output an
image that matches final_frame. No video in this version — purely
single-image-input, single-image-output.
Layout
VBVR-Reorganized-Image/
├── train/
│ ├── Pure_Reasoning/ (48 generators, 480,000 samples)
│ └── Instruction_Following/ (48 generators, 480… See the full description on the dataset page: https://huggingface.co/datasets/May-apple/VBVR-Reorganized-Image.YH_CUHKSZ_Apple_RAW_8K_Dataset
README of YH CUHKSZ Apple RAW 8K Dataset
Hao YANG, 2025
Description
This work introduces an ultra-large Apple RAW dataset accompanied by their JPEG versions, featuring 64 images captured both during the day and at night. The dataset consists of photos taken with the iPhone 14 Pro Max’s main camera at 1x zoom, saved in Apple RAW format at a resolution of 8064×6048 (8K). The dataset will be publicly available at… See the full description on the dataset page: https://huggingface.co/datasets/YarnYang/YH_CUHKSZ_Apple_RAW_8K_Dataset.DORI-instruction-tuning-dataset
DORI Spatial Reasoning Instruction Dataset
Dataset Description
This dataset contains instruction tuning data for spatial reasoning tasks across multiple question types and visual datasets.
Dataset Structure
Dataset Splits
train: 26,626 samples
test: 6,672 samples
Total: 33,298 samples
Question Types
q1
q2
q3
q4
q5
q6
q7
Source Datasets
3d_future
cityscapes
coco
coco_space_sea
get_3d
jta
kitti
nocs_real
objectron… See the full description on the dataset page: https://huggingface.co/datasets/appledora/DORI-instruction-tuning-dataset.flair
Federated Learning Annotated Image Repository (FLAIR): A large labelled image dataset for benchmarking in federated learning
FLAIR was published at NeurIPS 2022 (paper)
(Preferred) Benchmarking FLAIR is available in pfl-research (repo, paper).
The ml-flair repo contains a setup for benchmarking with TensorFlow Federated and notebooks for exploring data.
FLAIR is a large dataset of images that captures a number of characteristics encountered in federated learning (FL) and… See the full description on the dataset page: https://huggingface.co/datasets/apple/flair.VBVR-Reorganized
VBVR-Reorganized
Reorganized + prompt-cleaned + paired-variant-augmented version of VBVR
(Video-Based Visual Reasoning), prepared for video-generation training.
The dataset partitions every task into Pure_Reasoning (PR) vs
Instruction_Following (IF), rewrites Pure_Reasoning prompts to remove
leak phrases, and adds 4 paired-variant generators (G-21B/G-36B/O-18B/O-19B)
that share a first frame with their forward counterpart but require the
model to generate a different ground-truth… See the full description on the dataset page: https://huggingface.co/datasets/May-apple/VBVR-Reorganized.apple-dms-materials
Apple Dense Material Segmentation (DMS) Dataset
A pixel-level material segmentation dataset containing ~41K images with dense annotations across 57 material categories. Originally released by Apple as part of the Dense Material Segmentation (DMS) research project.
Note: This is a mirror prepared for direct use with the HuggingFace 🤗 datasets library. The source images originate from Open Images V7, and material annotations were created by Apple. Some images (~6%) from the original… See the full description on the dataset page: https://huggingface.co/datasets/AllanK24/apple-dms-materials.apple_leaf_disease_classification
Apple Leaf Disease Classification
A dataset for image classification of Apple Leaf Disease Classification. The dataset contains 7,505 images across 3 classes: Alternaria, Apple_Mosaic, Healthy.Images per class:
Alternaria: 2,523
Apple_Mosaic: 2,523
Healthy: 2,459
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{yatoo2024indigenous,
title={An indigenous dataset for the detection and classification… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/apple_leaf_disease_classification.minne-apple-segmentationA version of MinneApple with coco annotations
ThinkEditapple_banana_30hz_cmdThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "fr3",
"total_episodes": 262,
"total_frames": 109516,
"total_tasks": 2,
"total_videos": 0,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:262"
},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/yio-ye2004/apple_banana_30hz_cmd.Video-To-Dataset-Orchard-Apple
Video-To-Dataset-Orchard-Apple Dataset
Dataset Description
This dataset provides a collection of representative image frames extracted from drone video sequences captured in various agricultural environments, with a particular focus on apple orchards. It also includes scenes from grasslands and panoramic views. The frame extraction and selection process followed the "Video-To-Dataset" methodology developed by the primary author.
The dataset is designed to support research… See the full description on the dataset page: https://huggingface.co/datasets/miroslavjaros/Video-To-Dataset-Orchard-Apple.Video-To-Dataset-Orchard-Apple
Video-To-Dataset-Orchard-Apple Dataset
Dataset Description
This dataset provides a collection of representative image frames extracted from drone video sequences captured in various agricultural environments, with a particular focus on apple orchards. It also includes scenes from grasslands and panoramic views. The frame extraction and selection process followed the "Video-To-Dataset" methodology developed by the primary author.
The dataset is designed to support… See the full description on the dataset page: https://huggingface.co/datasets/sulaqy/Video-To-Dataset-Orchard-Apple.apple-dms-materials-v2
Apple Dense Material Segmentation (DMS) – Stratified 80/10/10 Split
A pixel-level material segmentation dataset containing ~41K images with dense annotations across 57 material categories. Originally released by Apple as part of the Dense Material Segmentation (DMS) research project.
This version uses a custom stratified 80/10/10 split (vs Apple's original 54/23/23) to maximise training data while maintaining representative validation and test sets.
Why a Custom Split?… See the full description on the dataset page: https://huggingface.co/datasets/AllanK24/apple-dms-materials-v2.DFNDR-12M-bf16
Dataset Card for DFNDR-12M-BFloat16
This dataset contains synthetic captions, embeddings, and metadata for DFNDR-12M.
The metadata has been generated using pretrained image-text models on DFN-12M, a uniformly sampled subset of 12.8M samples from DFN-2B.
For details on how to use the metadata, please visit our ml-mobileclip repository.
For code to generate multi-modal reinforced datasets at large scale see ml-mobileclip-dr repository.
The float32 version of this dataset is… See the full description on the dataset page: https://huggingface.co/datasets/apple/DFNDR-12M-bf16.piper_dual_weigh_apple_eef_xyz3d_100DET-COMPASS
Superpowering Open-Vocabulary Object Detectors for X-ray Vision
ICCV 2025
Pablo Garcia-Fernandez,
Lorenzo Vaquero,
Mingxuan Liu,
Feng Xue,
Daniel Cores,
Nicu Sebe,
Manuel Mucientes,
Elisa Ricci
DET-COMPASS
This is the official repository of Superpowering Open-Vocabulary Object Detectors for X-ray Vision (ICCV'25)
Dataset Summary
Object detection in security X-ray scans has advanced significantly in recent years. However, evaluating Open-vocabulary Object… See the full description on the dataset page: https://huggingface.co/datasets/hpu-apple/DET-COMPASS.ApplesM5-Dataset
🍎 ApplesM5: Synthetic Apple Detection Benchmark
This repository hosts the data files (images and annotations) used in the Synetic AI research paper, "Better Than Real: Synthetic Apple Detection for Orchards." This dataset was created through procedural content generation and physically-based rendering (PBR) to provide a clean, highly generalized training signal for robust agricultural AI.
The data demonstrates that training exclusively on this synthetic dataset yields superior… See the full description on the dataset page: https://huggingface.co/datasets/SyneticAI/ApplesM5-Dataset.apple_on_plate_l1This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": null,
"total_episodes": 54,
"total_frames": 8757,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 10,
"splits": {
"train": "0:54"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path": null… See the full description on the dataset page: https://huggingface.co/datasets/globcy/apple_on_plate_l1.apple_on_plate_l1_absolThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": null,
"total_episodes": 54,
"total_frames": 8757,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 10,
"splits": {
"train": "0:54"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path": null… See the full description on the dataset page: https://huggingface.co/datasets/globcy/apple_on_plate_l1_absol.apple_v0This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "panda",
"total_episodes": 100,
"total_frames": 24867,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 15,
"splits": {
"train": "0:100"},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/HomeRobotics/apple_v0.