datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
pascal-voc
Pascal VOC
Dataset Summary
The Pascal Visual Object Classes (VOC) dataset is a widely used benchmark in the field of computer vision. It is designed for object detection, image classification, semantic segmentation, and action classification tasks. The dataset provides a comprehensive set of annotated images covering 20 object classes, allowing researchers to evaluate and compare the performance of various algorithms.
Note: This dataset repository contains all editions of… See the full description on the dataset page: https://huggingface.co/datasets/merve/pascal-voc.pascal-voc-2012pascal_vocPASCAL_VOCPascal_VOCpedro-pascalpascal_digits_10class_remappascal-voc-2012
Dataset Card for "pascal-voc-2012"
More Information needed
pascal_voc2012_det_train_valPASCALRAWpascal_rawmarin-starcoderdata_pascalPascalpascal-voc-2012-segmentation-lance
Pascal VOC 2012 Segmentation (Lance Format)
A Lance-formatted version of the Pascal VOC 2012 semantic segmentation split, sourced from nateraw/pascal-voc-2012. Each row pairs an inline JPEG image with the per-pixel PNG segmentation mask and a cosine-normalized OpenCLIP ViT-B-32 image embedding, so a single columnar table carries both annotation modalities and the features needed to retrieve, curate, and train against them — all available directly from the Hub at… See the full description on the dataset page: https://huggingface.co/datasets/lance-format/pascal-voc-2012-segmentation-lance.pascal-features-dllabsdetails_runkai__PascalHermes-2.5-Mistral-7B
Dataset Card for Evaluation run of runkai/PascalHermes-2.5-Mistral-7B
Dataset automatically created during the evaluation run of model runkai/PascalHermes-2.5-Mistral-7B on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_runkai__PascalHermes-2.5-Mistral-7B.pascal_voc_seg_train_valPASCAL_VOC_backup_from_JimmyUnleashedpascal-voc
Pascal VOC
Dataset Summary
The Pascal Visual Object Classes (VOC) dataset is a widely used benchmark in the field of computer vision. It is designed for object detection, image classification, semantic segmentation, and action classification tasks. The dataset provides a comprehensive set of annotated images covering 20 object classes, allowing researchers to evaluate and compare the performance of various algorithms.
Note: This dataset repository contains all editions of… See the full description on the dataset page: https://huggingface.co/datasets/yizhangdev/pascal-voc.pedro-pascallrgb-pascalvoc-neuralwalkerimport torch
from datasets import load_dataset
from torch_geometric.data import Data, Batch
from tqdm import tqdm
# Load the HuggingFace dataset from hub
hf_dataset = load_dataset("samm393/lrgb-pascalvoc-neuralwalker")
# Load multiple graphs
num_graphs = 10
# Convert each to PyG Data object
pyg_graphs = []
for i in tqdm(range(num_graphs), desc="Loading graphs"):
hf_row = hf_dataset['train'][i]
pyg_dict = {k: torch.tensor(v) if isinstance(v, list) else v for k, v in hf_row.items()}… See the full description on the dataset page: https://huggingface.co/datasets/ReasonGNN/lrgb-pascalvoc-neuralwalker.raw_pascal_12classsc_Pascal
Dataset Card for "sc_Pascal"
More Information needed
pascal-parts-sam3PascalPartThis PACO dataset is designed to load coco-stuff only & coco stuff thing.pascal-contextmy-single-image-dataset
Dataset Card for "my-single-image-dataset"
More Information needed
nepali-slrclassification-ie-optimizationpascal-context-fixlrgb-pascalvoc-neuralwalker-walk-length-6import torch
from datasets import load_dataset
from torch_geometric.data import Data, Batch
from tqdm import tqdm
# Load the HuggingFace dataset from hub
hf_dataset = load_dataset("samm393/lrgb-pascalvoc-neuralwalker")
# Load multiple graphs
num_graphs = 10
# Convert each to PyG Data object
pyg_graphs = []
for i in tqdm(range(num_graphs), desc="Loading graphs"):
hf_row = hf_dataset['train'][i]
pyg_dict = {k: torch.tensor(v) if isinstance(v, list) else v for k, v in hf_row.items()}… See the full description on the dataset page: https://huggingface.co/datasets/ReasonGNN/lrgb-pascalvoc-neuralwalker-walk-length-6.