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license: cc-by-4.0
task_categories:
- video-classification
- other
language:
- en
tags:
- egocentric
- first-person-video
- action-recognition
- manufacturing
- industrial
- assembly
- motor
- factory
- computer-vision
- video
pretty_name: Manufacturing Unit Egocentric Video Dataset Sample
size_categories:
- n<1K
configs:
- config_name: default
data_files:
- split: train
path: metadata.csv
---
# π Manufacturing Unit Egocentric Video Dataset (Sample)
**This dataset is part of a larger collection of egocentric activity datasets by Verbose Tech Labs LLP. If you want the full dataset, or want access to more categories? Get in touch with us:**
- π **Phone:** [+91 7672 000 500](tel:+917672000500)
- π¬ **WhatsApp:** [+91 7672 000 500](https://wa.me/917672000500)
- π§ **Email:** [Hello@VerboseTechLabs.com](mailto:Hello@VerboseTechLabs.com)
- π **Website:** [VerboseTechLabs.com](https://VerboseTechLabs.com)
- π **More datasets:** [kaggle.com/verbosetechlabsllp](https://www.kaggle.com/verbosetechlabsllp)
---
## Dataset Summary
First-person point-of-view (POV) video recordings from a manufacturing unit, capturing key production activities including **assembling, coiling, motor assembly, and machine operation**. This is a **sample release** showcasing the quality and format of our larger manufacturing dataset collection.
## Dataset Statistics
| Metric | Value |
|---|---|
| Total clips | 5 |
| Total duration | ~12.5 minutes |
| Total size | ~380 MB |
| Activity classes | 5 |
| View type | Egocentric (first-person) |
| Video format | MP4 |
| Frame rate | 30 fps |
| Resolution | 1080p |
## Supported Tasks
- **Video classification** β classify manufacturing activities
- **Action recognition** β recognize industrial worker actions
- **Fine-grained assembly step** detection
- **Worker productivity** and time-motion analysis
- **Ergonomics research** β repetitive motion, posture analysis
- **Assistive robotics** for manufacturing floors
- **Quality control** and defect detection training
- **Human-robot collaboration** in industrial settings
## Dataset Structure
### Folder Structure
```
manufacturing-unit-egocentric-sample/
βββ videos/
β βββ Assembling MBC 1.mp4
β βββ Assembling.mp4
β βββ Coiling.mp4
β βββ Moter assembling.mp4
β βββ Working on machine.mp4
βββ metadata.csv
βββ README.md
```
### Data Fields
The `metadata.csv` file contains the following columns:
| Column | Type | Description |
|---|---|---|
| `file_name` | string | Relative path to the video file |
| `clip_id` | string | Unique identifier (e.g., `MFG_001`) |
| `activity` | string | Main manufacturing activity class |
| `sub_activity` | string | Fine-grained label |
| `duration` | string | Human-readable duration (HH:MM:SS) |
| `duration_seconds` | integer | Duration in seconds |
| `file_size_mb` | float | File size in megabytes |
| `recording_date` | date | Recording date (YYYY-MM-DD) |
| `resolution` | string | Video resolution |
| `fps` | integer | Frames per second |
| `view_type` | string | Camera view type (`egocentric`) |
| `notes` | string | Additional context |
### Activity Breakdown
| Clip ID | File | Activity | Sub-activity | Duration |
|---|---|---|---|---|
| MFG_001 | Assembling MBC 1.mp4 | assembling | mbc_assembly | 00:03:00 |
| MFG_002 | Assembling.mp4 | assembling | general_assembly | 00:00:30 |
| MFG_003 | Coiling.mp4 | coiling | wire_coiling | 00:03:00 |
| MFG_004 | Moter assembling.mp4 | motor_assembling | motor_assembly | 00:03:00 |
| MFG_005 | Working on machine.mp4 | machine_operation | general_operation | 00:03:00 |
### Activity Categories
- π§ **Assembling** β General and MBC (Motor Base Component) assembly
- π§΅ **Coiling** β Copper wire coiling for motor windings
- βοΈ **Motor Assembling** β Complete motor assembly workflow
- π οΈ **Machine Operation** β Workers operating manufacturing machinery
## Usage
### Load with π€ datasets library
```python
from datasets import load_dataset
dataset = load_dataset("verbosetechlabsllp/manufacturing-unit-egocentric-sample")
print(dataset)
```
### Load metadata directly with Pandas
```python
import pandas as pd
df = pd.read_csv("hf://datasets/verbosetechlabsllp/manufacturing-unit-egocentric-sample/metadata.csv")
print(df.head())
print(df['activity'].value_counts())
```
### Download a specific video
```python
from huggingface_hub import hf_hub_download
video_path = hf_hub_download(
repo_id="verbosetechlabsllp/manufacturing-unit-egocentric-sample",
filename="videos/Coiling.mp4",
repo_type="dataset"
)
print(f"Video downloaded to: {video_path}")
```
## Data Collection
- **Camera view**: First-person / egocentric (head-mounted or chest-mounted)
- **Environment**: Real manufacturing unit / factory floor
- **Lighting**: Industrial factory lighting
- **Audio**: Included in MP4 (includes ambient machine sounds β usable for multimodal research)
- **Recording date**: May 2026
## Licensing Information
**CC BY 4.0** β Free for research and commercial use with attribution.
## Citation
```bibtex
@dataset{manufacturing_unit_egocentric_2026,
title = {Manufacturing Unit Egocentric Video Dataset (Sample)},
author = {Verbose Tech Labs LLP},
year = {2026},
url = {https://huggingface.co/datasets/verbosetechlabsllp/manufacturing-unit-egocentric-sample}
}
```
## More Datasets from Verbose Tech Labs
This dataset is part of a larger collection of egocentric activity datasets covering:
- π Clothing industry manufacturing
- π³ Cooking & food preparation
- π§Ή Household cleaning tasks
- π Manufacturing unit workflows (this β sample)
- ...and more categories in development
π Browse all our datasets: [kaggle.com/verbosetechlabsllp](https://www.kaggle.com/verbosetechlabsllp) | [huggingface.co/verbosetechlabsllp](https://huggingface.co/verbosetechlabsllp)
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