In-context
X2I-in-context-learning
X2I Dataset
Project Page: https://vectorspacelab.github.io/OmniGen/
Github: https://github.com/VectorSpaceLab/OmniGen
Paper: https://arxiv.org/abs/2409.11340
Model: https://huggingface.co/Shitao/OmniGen-v1
To achieve robust multi-task processing capabilities, it is essential to train the OmniGen on large-scale and diverse datasets. However, in the field of unified image generation, a readily available dataset has yet to emerge. For this reason, we have curated a large-scale… See the full description on the dataset page: https://huggingface.co/datasets/yzwang/X2I-in-context-learning.aloha_incontext
aloha_incontext
A Mobile ALOHA robot manipulation dataset for in-context imitation learning. It contains
human-teleoperated demonstrations of pick-and-place, pen uncapping, placing eggs in a
box and closing it, and additional bimanual tasks.
1,328 episodes / 31 task configurations / 587,000 frames, recorded at 50 Hz.
The task configurations are divided into 25 seen configurations (1,318 episodes)
and 6 unseen configurations (10 episodes).
Observations and actions… See the full description on the dataset page: https://huggingface.co/datasets/vo2yager/aloha_incontext.word_in_contextDataset homepage:
https://wic-ita.github.io/index.html
gpcv_incontext_benchrecycling-in-common-contextpen_incontextThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.0",
"robot_type": "aloha",
"total_episodes": 100,
"total_frames": 50000,
"total_tasks": 4,
"total_videos": 0,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 50,
"splits": {
"train": "0:100"
},
"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/vo2yager/pen_incontext.