datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
DeepLearningProject
Deep Learning Project
Dataset Summary
This repository contains the datasets, trained models, notebooks, experiments, feature-extraction outputs, and supporting resources developed for a deep learning project focused on fire detection, fire severity classification, and related computer vision tasks.
The project covers multiple stages of a deep learning workflow, including binary fire classification, three-class fire severity classification, feature extraction… See the full description on the dataset page: https://huggingface.co/datasets/AbdullahImran/DeepLearningProject.VHR-10The VHR-10 dataset mirrored from https://github.com/chaozhong2010/VHR-10_dataset_coco
NWPU VHR-10 data set is a challenging ten-class geospatial object detection data set. This dataset contains a total of 800 VHR optical remote sensing images, where 715 color images were acquired from Google Earth with the spatial resolution ranging from 0.5 to 2 m, and 85 pansharpened color infrared images were acquired from Vaihingen data with a spatial resolution of 0.08 m. The data set is divided into two… See the full description on the dataset page: https://huggingface.co/datasets/satellite-image-deep-learning/VHR-10.deep_learning_2025_vision_jointThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "omy",
"total_episodes": 50,
"total_frames": 10128,
"total_tasks": 1,
"total_videos": 0,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 20,
"splits": {
"train": "0:50"
},
"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/Jeongeun/deep_learning_2025_vision_joint.SODA-ASODA-A comprises 2513 high-resolution images of aerial scenes, which has 872069 instances annotated with oriented rectangle box annotations over 9 classes.
Website
actresses
Dataset Card for "actresses"
More Information needed
ROCOv2-X-Ray-radiology
ROCOv2 X-Ray Subset
Radiographs extracted from ROCOv2 (Radiology Objects in COntext, version 2), for training vision-language models on X-ray interpretation.
What this is
ROCOv2 spans many imaging modalities. This subset keeps only the X-ray studies, so that a model can be trained on a single modality rather than learning across CT, MRI, ultrasound and radiography at once.
Rows
4,254
Split
train
Size
~977 MB
Modality
X-ray only… See the full description on the dataset page: https://huggingface.co/datasets/deepLEARNING786/ROCOv2-X-Ray-radiology.ROCOv2-X-Ray-radiology_-cycle-1
ROCOv2 X-Ray, Report Generation Pilot (Cycle 1)
A 28-row pilot testing whether short ROCO captions can be expanded into report-shaped training pairs.
Why this exists
ROCOv2 captions are one or two clipped sentences, often written to make a teaching point rather than to read as a radiological finding. A vision-language model trained directly on them learns to produce clipped captions, not reports.
This pilot tested a different approach: take the caption and its… See the full description on the dataset page: https://huggingface.co/datasets/deepLEARNING786/ROCOv2-X-Ray-radiology_-cycle-1.Deep_Learningdeep_learning_2025This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "omy",
"total_episodes": 50,
"total_frames": 10128,
"total_tasks": 1,
"total_videos": 0,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 20,
"splits": {
"train": "0:50"
},
"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/Jeongeun/deep_learning_2025.radimagenet-vqa-500-test
🩺 RadImageNet VQA 500 Test Subset
This dataset contains a curated 500-example test audit subset for Medical Visual Question Answering based on RadImageNet.
📊 Dataset Summary
Total Samples: 500 test VQA pairs
Modalities: CT, MRI, X-ray (Abdomen, Brain, Chest/Lung, Ankle/Foot, Hip, Knee)
Question Types: Open-ended & Closed (Yes/No)
Organization: VQA-DeepLearning
💻 Usage
from datasets import load_dataset
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/VQA-DeepLearning/radimagenet-vqa-500-test.fall2025_deeplearningdataset3vqa-rad
Dataset Card for VQA-RAD
Dataset Description
VQA-RAD is a dataset of question-answer pairs on radiology images. The dataset is intended to be used for training and testing
Medical Visual Question Answering (VQA) systems. The dataset includes both open-ended questions and binary "yes/no" questions.
The dataset is built from MedPix, which is a free open-access online database of medical images.
The question-answer pairs were manually generated by a team of… See the full description on the dataset page: https://huggingface.co/datasets/VQA-DeepLearning/vqa-rad.deeplearning-catdogdeeplearning_lmmdataset2deep-image-learningdataset1dataset5Mahidol_Deeplearning_Project_Classify_Friend_From_PopStartest_set_deeplearningDrug-Protein-Interaction-Prediction-Using-CLIP-and-Deep-LearningDelamination-detection-in-composite-laminates-using-deep-learningBIT_Deep_Learning_Fundamentalsfall2025-deeplearning-noisy-pairs-newdataset4fall2025-deeplearning-noisy-pairs-new-2fall2025-deeplearning-noisy-100kSSE-DeepLearning-26fall2025-deeplearning-noisy-test-10