datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
mscoco_2014_5k_test_image_text_retrieval
MSCOCO (5K test set)
Original paper: Microsoft COCO: Common Objects in Context
Homepage: https://cocodataset.org/#home
5K test set split from: http://cs.stanford.edu/people/karpathy/deepimagesent/caption_datasets.zip
Bibtex:
@inproceedings{lin2014microsoft,
title={Microsoft coco: Common objects in context},
author={Lin, Tsung-Yi and Maire, Michael and Belongie, Serge and Hays, James and Perona, Pietro and Ramanan, Deva and Doll{\'a}r, Piotr and Zitnick, C Lawrence}… See the full description on the dataset page: https://huggingface.co/datasets/nlphuji/mscoco_2014_5k_test_image_text_retrieval.MS-COCOmscoco-controlnet-cannywds_mscoco_captionsmscoco_chairMS-COCO-CaptionsMS-COCO-uniquemscoco-1st-captionTo reproduce, run pip install -r requirements.txt and download.sh.
mscoco-controlnet-canny-less-colorsthai-mscoco-2014-captions
Usage
from datasets import load_dataset
dataset = load_dataset("patomp/thai-mscoco-2014-captions")
dataset
output
DatasetDict({
train: Dataset({
features: ['image', 'filepath', 'sentids', 'filename', 'imgid', 'split', 'sentences_tokens', 'sentences_raw', 'sentences_sentid', 'cocoid', 'th_sentences_raw'],
num_rows: 113287
})
validation: Dataset({
features: ['image', 'filepath', 'sentids', 'filename', 'imgid', 'split', 'sentences_tokens'… See the full description on the dataset page: https://huggingface.co/datasets/patomp/thai-mscoco-2014-captions.MS_COCO_2017_URL_TEXTwds_mscoco_captions2017mscoco
Common Objects in Context (COCO) Dataset
This dataset is English captions of COCO dataset.
The splits in this dataset is set according to Andrej Karpathy's split from dataset_coco.json file. The collection was created specifically for simplicity of use in training and evaluation pipeline by non-commercial and research purposes. The COCO images dataset is licensed under a Creative Commons Attribution 4.0 License.
Reference
@misc{lin2015microsoftcococommonobjects… See the full description on the dataset page: https://huggingface.co/datasets/romrawinjp/mscoco.mscocomscoco-colour_masksmscoco_train_2014_openai_clip-vit-base-patch32_image_caption_retrieval_pairs_2022-09-01mscoco_train_2014_openai_clip-vit-base-patch32_image_image_retrieval_pairs_2022-09-15mbeir_mscoco_task0mbeir_mscoco_task3mscoco-small
Dataset Card for "mscoco-small"
More Information needed
MSCOCO_PT-BRmscoco_omni
catalog.jsonl contains the captions and filenames for each image id. There are around 170 text-image-video-audio (omni) tuples in it.
How to run
Specify GOOGLE_API_KEY
run the following to get setup readybash setup.sh
then only need to run this file only in the futurepython geminiAPI.py
If runs successfully, a file called mscoco_cmret.jsonl will be generated, please provide this file to me.
mscoco_100k
Dataset Card for "mscoco_100k"
More Information needed
mscoco_train_2014_openai_clip-vit-base-patch32_image_image_retrieval_pairs_2022-09-13mscoco_contrastive
⚠️ Part of the BidirLM-Omni Collection > This dataset is a specific modality sub-sample of the corpus used to train the BidirLM-Omni models.
Looking for the full training mixture? > If you want to access the complete, balanced 1.8M sample omnimodal dataset (integrating text, image, audio), please visit the global integration hub here:👉 BidirLM/BidirLM-Omni-Contrastive
📜 Citation
If you use this processed dataset or the broader BidirLM mixture in your research, please cite… See the full description on the dataset page: https://huggingface.co/datasets/BidirLM/mscoco_contrastive.mscoco_20k_unique_imgs
Dataset Card for "mscoco_20k_unique_imgs"
More Information needed
mscoco_100k_30k_test
Dataset Card for "mscoco_100k_30k_test"
More Information needed
mscoco_2014_train_captions_openai_clip-vit-base-patch32mscoco_train_2014_openai_clip-vit-base-patch32_image_caption_retrieval_pairsmscoco_train_2014_openai_clip-vit-base-patch32_self_retrieval