datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
EgoVid_framesSimScale
Haochen Tian,
Tianyu Li,
Haochen Liu,
Jiazhi Yang,
Yihang Qiu,
Guang Li,
Junli Wang,
Yinfeng Gao,
Zhang Zhang,
Liang Wang,
Hangjun Ye,
Tieniu Tan,
Long Chen,
Hongyang Li
📧 Primary Contact: Haochen Tian (tianhaochen2023@ia.ac.cn)
📜 Materials: 🌐 𝕏 | 📰 Media| 🗂️ Slides | 🎬 Talk (in Chinese)
🖊️ Joint effort by CASIA, OpenDriveLab at HKU, and Xiaomi EV.
🔥 Highlights
🏗️ A scalable simulation pipeline that synthesizes diverse and… See the full description on the dataset page: https://huggingface.co/datasets/OpenDriveLab-org/SimScale.character_similarity
character_similarity
This is a dataset used for training models to determine whether two anime images (containing only one person) depict the same character. The dataset includes the following versions:
Version
Filename
Characters
Images
Information
v0
images_v0.tar.xz
2059
162116
Crawled from zerochan.net, includes images of Arknights, Fate/Grand Order, Genshin Impact, Girls' Frontline, and Azur Lane, as well as over 1500 other game or anime characters. The images are… See the full description on the dataset page: https://huggingface.co/datasets/deepghs/character_similarity.Stable-Sim2Realscotus-sonia_sotomayor-audio
SCOTUS-sim audio: sonia_sotomayor
Per-utterance audio clips from Oyez oral-argument mp3s, sliced at
the start_time / stop_time timestamps stored in the companion
scotus-sim/scotus-sonia_sotomayor-training dataset.
Alignment
clip_NNNNN.wav in the tarball corresponds exactly to
audio_segments.jsonl[NNNNN] in the training companion dataset.
In metadata.jsonl each row carries the same 0-padded index in idx.
This supersedes the v1 tarball, which had systematic audio↔segment… See the full description on the dataset page: https://huggingface.co/datasets/scotus-sim/scotus-sonia_sotomayor-audio.Koala_36M_1scotus-elizabeth_b_prelogar-audio
SCOTUS-sim audio: elizabeth_b_prelogar
Per-utterance audio clips from Oyez oral-argument mp3s, sliced at
the start_time / stop_time timestamps stored in the companion
scotus-sim/scotus-elizabeth_b_prelogar-training dataset.
Alignment
clip_NNNNN.wav in the tarball corresponds exactly to
audio_segments.jsonl[NNNNN] in the training companion dataset.
In metadata.jsonl each row carries the same 0-padded index in idx.
This supersedes the v1 tarball, which had systematic… See the full description on the dataset page: https://huggingface.co/datasets/scotus-sim/scotus-elizabeth_b_prelogar-audio.spatialvid_framesscotus-paul_d_clement-audio
SCOTUS-sim audio: paul_d_clement
Per-utterance audio clips from Oyez oral-argument mp3s, sliced at
the start_time / stop_time timestamps stored in the companion
scotus-sim/scotus-paul_d_clement-training dataset.
Alignment
clip_NNNNN.wav in the tarball corresponds exactly to
audio_segments.jsonl[NNNNN] in the training companion dataset.
In metadata.jsonl each row carries the same 0-padded index in idx.
This supersedes the v1 tarball, which had systematic audio↔segment… See the full description on the dataset page: https://huggingface.co/datasets/scotus-sim/scotus-paul_d_clement-audio.scotus-elena_kagan-audio
SCOTUS-sim audio: elena_kagan
Per-utterance audio clips from Oyez oral-argument mp3s, sliced at
the start_time / stop_time timestamps stored in the companion
scotus-sim/scotus-elena_kagan-training dataset.
Alignment
clip_NNNNN.wav in the tarball corresponds exactly to
audio_segments.jsonl[NNNNN] in the training companion dataset.
In metadata.jsonl each row carries the same 0-padded index in idx.
This supersedes the v1 tarball, which had systematic audio↔segment
index… See the full description on the dataset page: https://huggingface.co/datasets/scotus-sim/scotus-elena_kagan-audio.scotus-neal_kumar_katyal-audio
SCOTUS-sim audio: neal_kumar_katyal
Per-utterance audio clips from Oyez oral-argument mp3s, sliced at
the start_time / stop_time timestamps stored in the companion
scotus-sim/scotus-neal_kumar_katyal-training dataset.
Alignment
clip_NNNNN.wav in the tarball corresponds exactly to
audio_segments.jsonl[NNNNN] in the training companion dataset.
In metadata.jsonl each row carries the same 0-padded index in idx.
This supersedes the v1 tarball, which had systematic… See the full description on the dataset page: https://huggingface.co/datasets/scotus-sim/scotus-neal_kumar_katyal-audio.vlsi-simple-bufferingsim2real-6dof
sim2real-6dof Dataset
Code Commit Hash (used for data generation): ae30b7e16f1d7eefc00383fcfaed09cbfb22f1a9
Shards: 80
Shard Size: 1000
E31_decoder_gen_fsqscotus-lisa_s_blatt-audio
SCOTUS-sim audio: lisa_s_blatt
Per-utterance audio clips from Oyez oral-argument mp3s, sliced at
the start_time / stop_time timestamps stored in the companion
scotus-sim/scotus-lisa_s_blatt-training dataset.
Alignment
clip_NNNNN.wav in the tarball corresponds exactly to
audio_segments.jsonl[NNNNN] in the training companion dataset.
In metadata.jsonl each row carries the same 0-padded index in idx.
This supersedes the v1 tarball, which had systematic audio↔segment
index… See the full description on the dataset page: https://huggingface.co/datasets/scotus-sim/scotus-lisa_s_blatt-audio.scotus-john_g_roberts_jr-audio
SCOTUS-sim audio: john_g_roberts_jr
Per-utterance audio clips from Oyez oral-argument mp3s, sliced at
the start_time / stop_time timestamps stored in the companion
scotus-sim/scotus-john_g_roberts_jr-training dataset.
Alignment
clip_NNNNN.wav in the tarball corresponds exactly to
audio_segments.jsonl[NNNNN] in the training companion dataset.
In metadata.jsonl each row carries the same 0-padded index in idx.
This supersedes the v1 tarball, which had systematic… See the full description on the dataset page: https://huggingface.co/datasets/scotus-sim/scotus-john_g_roberts_jr-audio.scotus-samuel_a_alito_jr-audio
SCOTUS-sim audio: samuel_a_alito_jr
Per-utterance audio clips from Oyez oral-argument mp3s, sliced at
the start_time / stop_time timestamps stored in the companion
scotus-sim/scotus-samuel_a_alito_jr-training dataset.
Alignment
clip_NNNNN.wav in the tarball corresponds exactly to
audio_segments.jsonl[NNNNN] in the training companion dataset.
In metadata.jsonl each row carries the same 0-padded index in idx.
This supersedes the v1 tarball, which had systematic… See the full description on the dataset page: https://huggingface.co/datasets/scotus-sim/scotus-samuel_a_alito_jr-audio.Koala_36M_1_filtered_imgsscotus-brett_m_kavanaugh-audio
SCOTUS-sim audio: brett_m_kavanaugh
Per-utterance audio clips from Oyez oral-argument mp3s, sliced at
the start_time / stop_time timestamps stored in the companion
scotus-sim/scotus-brett_m_kavanaugh-training dataset.
Alignment
clip_NNNNN.wav in the tarball corresponds exactly to
audio_segments.jsonl[NNNNN] in the training companion dataset.
In metadata.jsonl each row carries the same 0-padded index in idx.
This supersedes the v1 tarball, which had systematic… See the full description on the dataset page: https://huggingface.co/datasets/scotus-sim/scotus-brett_m_kavanaugh-audio.scotus-jeffrey_l_fisher-audio
SCOTUS-sim audio: jeffrey_l_fisher
Per-utterance audio clips from Oyez oral-argument mp3s, sliced at
the start_time / stop_time timestamps stored in the companion
scotus-sim/scotus-jeffrey_l_fisher-training dataset.
Alignment
clip_NNNNN.wav in the tarball corresponds exactly to
audio_segments.jsonl[NNNNN] in the training companion dataset.
In metadata.jsonl each row carries the same 0-padded index in idx.
This supersedes the v1 tarball, which had systematic audio↔segment… See the full description on the dataset page: https://huggingface.co/datasets/scotus-sim/scotus-jeffrey_l_fisher-audio.scotus-neil_gorsuch-audio
SCOTUS-sim audio: neil_gorsuch
Per-utterance audio clips from Oyez oral-argument mp3s, sliced at
the start_time / stop_time timestamps stored in the companion
scotus-sim/scotus-neil_gorsuch-training dataset.
Alignment
clip_NNNNN.wav in the tarball corresponds exactly to
audio_segments.jsonl[NNNNN] in the training companion dataset.
In metadata.jsonl each row carries the same 0-padded index in idx.
This supersedes the v1 tarball, which had systematic audio↔segment
index… See the full description on the dataset page: https://huggingface.co/datasets/scotus-sim/scotus-neil_gorsuch-audio.Koala_36M_1_filtered_imgs_3w-5wcrawl_facepartcraft3d-data-shard04LAPAscotus-amy_coney_barrett-audio
SCOTUS-sim audio: amy_coney_barrett
Per-utterance audio clips from Oyez oral-argument mp3s, sliced at
the start_time / stop_time timestamps stored in the companion
scotus-sim/scotus-amy_coney_barrett-training dataset.
Alignment
clip_NNNNN.wav in the tarball corresponds exactly to
audio_segments.jsonl[NNNNN] in the training companion dataset.
In metadata.jsonl each row carries the same 0-padded index in idx.
This supersedes the v1 tarball, which had systematic… See the full description on the dataset page: https://huggingface.co/datasets/scotus-sim/scotus-amy_coney_barrett-audio.imagenet_val_caption1scotus-ketanji_brown_jackson-audio
SCOTUS-sim audio: ketanji_brown_jackson
Per-utterance audio clips from Oyez oral-argument mp3s, sliced at
the start_time / stop_time timestamps stored in the companion
scotus-sim/scotus-ketanji_brown_jackson-training dataset.
Alignment
clip_NNNNN.wav in the tarball corresponds exactly to
audio_segments.jsonl[NNNNN] in the training companion dataset.
In metadata.jsonl each row carries the same 0-padded index in idx.
This supersedes the v1 tarball, which had systematic… See the full description on the dataset page: https://huggingface.co/datasets/scotus-sim/scotus-ketanji_brown_jackson-audio.testframesE31_render_gen_vq