metadata
license: apache-2.0
task_categories:
- video-classification
- robotics
tags:
- egocentric
- manufacturing
- jewelry
- diamond-setting
pretty_name: Egocentric Specialties
size_categories:
- 10M<n<100M
Egocentric Specialties Dataset
A dataset of egocentric (first-person) and top-down video footage of skilled jewelry manufacturing workers.
If you would are a robotics company looking to source this kind of data across any industry reach out to:
Jay Grieve (jpgrieve551@gmail.com)
Aarjav Jain (aarjav02@gmail.com)
Dataset Description
This dataset contains synchronized ego and top-down video pairs capturing skilled workers performing diamond jewelry manufacturing tasks.
Job Types
| Job Type | Description | Workers |
|---|---|---|
| setting | Diamond setting work | worker-001, worker-002, worker-003, worker-004, worker-005 |
| wax_pulling | Wax pulling process | worker-006, worker-007 |
| wax_setting | Wax setting process | worker-008 |
Data Structure
diamond_factory/
├── setting/
│ ├── worker-001/
│ │ ├── ego_001.mp4
│ │ ├── top_001.mp4
│ │ ├── ego_002.mp4
│ │ └── top_002.mp4
│ └── ...
├── wax_pulling/
│ └── ...
└── wax_setting/
└── ...
Statistics
- Total videos: 83
- Total size: 883.01 GB
- Video pairs: 41
- Job types: 3 (setting, wax_pulling, wax_setting)
- Workers: 8
Video Types
- ego: Egocentric (first-person) view from worker's perspective
- top: Top-down overhead view of the workspace
Usage
from datasets import load_dataset
# Load the dataset (streams from S3)
ds = load_dataset('ThisIsPepper/EgocentricSpecialties', streaming=True)
for sample in ds['train']:
print(sample['video_path'])
print(sample['job_type'])
print(sample['worker'])
print(sample['video_type'])
License
Apache 2.0