ego-centric
Egocentric-100K
Egocentric-100K is the largest dataset of manual labor. You can visualize the dataset here.
Egocentric-100K is state-of-the-art in hand visibility and active manipulation density compared to previous in-the-wild egocentric datasets. The complete 30,000 frame evaluation set is available at Egocentric-100K-Evaluation.
Dataset Statistics
Attribute
Value
Total Hours
100,405
Total Frames
10.8 billion
Video Clips
2,010,759
Median Clip Length
180.0 seconds
Mean… See the full description on the dataset page: https://huggingface.co/datasets/builddotai/Egocentric-100K.Egocentric-10K
Egocentric-10K is the largest egocentric dataset. It is the first dataset collected exclusively in real factories.
Your browser does not support the video tag.
Egocentric-10K is state-of-the-art in hand visibility and active manipulation density compared to previous in-the-wild egocentric datasets. The complete 30,000 frame evaluation set is available at Egocentric-10K-Evaluation.
Dataset Statistics
Attribute
Value
Total Hours
10,000
Total Frames
1.08 billion… See the full description on the dataset page: https://huggingface.co/datasets/builddotai/Egocentric-10K.Egocentric_10K_Evaluation
Dataset Card for Egocentric_10K_Evaluation
This is a FiftyOne dataset with 30000 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("Voxel51/Egocentric_10K_Evaluation")
# Launch the App
session = fo.launch_app(dataset)
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/Egocentric_10K_Evaluation.awesome-egocentric-atlas
Use this dataset
from datasets import load_dataset
ds = load_dataset("cy0307/awesome-egocentric-atlas", split="train")
print(len(ds), "resources")
print(ds[0])
papers = load_dataset(
"csv",
data_files="https://huggingface.co/datasets/cy0307/awesome-egocentric-atlas/resolve/main/awesome-egocentric-papers.csv",
split="train",
)
print(len(papers), "paper-linked resources")
Each row is one catalogued resource. Columns:
Column
Description
name
Resource name… See the full description on the dataset page: https://huggingface.co/datasets/cy0307/awesome-egocentric-atlas.Egocentric_10K_subset
Dataset Card for Egocentric 10K (subset - Factory 51, first 51 videos)
This is a FiftyOne dataset with 416 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("Voxel51/Egocentric_10K_subset")
# Launch the App
session =… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/Egocentric_10K_subset.APAC-Egocentric-Stereo
APAC Egocentric Stereo → FiftyOne (Native Multimodal MCAP)
The labeled stereo release of
humyn-labs/APAC-Egocentric-Stereo-Labeled,
converted to native multimodal MCAP episodes.
Twelve people were filmed doing their jobs while wearing a head-mounted
stereo rig. Each sequence runs about a minute and carries the rectified
video from both eyes, a depth render, a hand and head tracking render, and a
caption describing what the wearer is doing at every moment. The work spans… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/APAC-Egocentric-Stereo.