file_name stringclasses 7
values | clip_id stringclasses 7
values | activity stringclasses 1
value | sub_activity stringclasses 1
value | duration stringclasses 1
value | duration_seconds int64 180 180 | file_size_mb float64 103 104 | recording_date stringdate 2026-07-20 00:00:00 2026-07-20 00:00:00 | resolution stringclasses 1
value | fps int64 30 30 | view_type stringclasses 1
value | notes stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|
videos/metal_industry_operation01.mp4 | MTL_001 | metal_industry | metalwork_operation | 00:03:00 | 180 | 103.66 | 2026-07-20 | 1080p | 30 | egocentric | Metal industry operations activity |
videos/metal_industry_operation02.mp4 | MTL_002 | metal_industry | metalwork_operation | 00:03:00 | 180 | 103.59 | 2026-07-20 | 1080p | 30 | egocentric | Metal industry operations activity |
videos/metal_industry_operation03.mp4 | MTL_003 | metal_industry | metalwork_operation | 00:03:00 | 180 | 103.47 | 2026-07-20 | 1080p | 30 | egocentric | Metal industry operations activity |
videos/metal_industry_operation04.mp4 | MTL_004 | metal_industry | metalwork_operation | 00:03:00 | 180 | 103.59 | 2026-07-20 | 1080p | 30 | egocentric | Metal industry operations activity |
videos/metal_industry_operation05.mp4 | MTL_005 | metal_industry | metalwork_operation | 00:03:00 | 180 | 103.62 | 2026-07-20 | 1080p | 30 | egocentric | Metal industry operations activity |
videos/metal_industry_operation06.mp4 | MTL_006 | metal_industry | metalwork_operation | 00:03:00 | 180 | 103.88 | 2026-07-20 | 1080p | 30 | egocentric | Metal industry operations activity |
videos/metal_industry_operation07.mp4 | MTL_007 | metal_industry | metalwork_operation | 00:03:00 | 180 | 103.66 | 2026-07-20 | 1080p | 30 | egocentric | Metal industry operations activity |
⚙️ Metal Industry Operations — 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:
- 📞 Phone: +91 7672 000 500
- 💬 WhatsApp: +91 7672 000 500
- 📧 Email: Hello@VerboseTechLabs.com
- 🌐 Website: VerboseTechLabs.com
- 🔗 More datasets: kaggle.com/verbosetechlabsllp
Dataset Summary
First-person point-of-view (POV) video recordings from metal industry operations, captured on real factory floors. Videos showcase metalworking activities including welding, grinding, cutting, machining, and finishing operations. This is a sample release showcasing the format and quality of our larger metal industry dataset collection.
Dataset Statistics
| Metric | Value |
|---|---|
| Total clips | 7 |
| Total duration | 21 minutes (7 × 3:00) |
| Total size | ~725 MB |
| Activity class | metal_industry |
| View type | Egocentric (first-person) |
| Video format | MP4 |
| Frame rate | 30 fps |
| Resolution | 1080p |
| Clip length | Uniform 3 minutes each |
Supported Tasks
- Video classification — classify metal industry activities
- Action recognition — recognize metalworking actions
- Fine-grained metalworking activity classification
- Hand-object interaction — welding torches, grinders, cutting tools
- Worker safety monitoring — detect risky actions & PPE compliance
- Ergonomics research for metal industry workers
- Assistive robotics for metal fabrication lines
- Quality control and defect detection AI training
- Human-robot collaboration in metal manufacturing
- Industrial AI for smart metal factories
Dataset Structure
Folder Structure
metal-industry-operations-egocentric-sample/
├── videos/
│ ├── metal_industry_operation01.mp4
│ ├── metal_industry_operation02.mp4
│ ├── metal_industry_operation03.mp4
│ ├── metal_industry_operation04.mp4
│ ├── metal_industry_operation05.mp4
│ ├── metal_industry_operation06.mp4
│ └── metal_industry_operation07.mp4
├── metadata.csv
└── 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., MTL_001) |
activity |
string | Main class: metal_industry |
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 |
Clip Overview
| Clip ID | File | Duration | Size |
|---|---|---|---|
| MTL_001 | metal_industry_operation01.mp4 | 00:03:00 | 104 MB |
| MTL_002 | metal_industry_operation02.mp4 | 00:03:00 | 104 MB |
| MTL_003 | metal_industry_operation03.mp4 | 00:03:00 | 104 MB |
| MTL_004 | metal_industry_operation04.mp4 | 00:03:00 | 104 MB |
| MTL_005 | metal_industry_operation05.mp4 | 00:03:00 | 104 MB |
| MTL_006 | metal_industry_operation06.mp4 | 00:03:00 | 104 MB |
| MTL_007 | metal_industry_operation07.mp4 | 00:03:00 | 104 MB |
Uniform Clip Length ✨
All 7 clips have identical 3-minute duration, making this dataset:
- ✅ Ideal for balanced batch training — no padding or trimming needed
- ✅ Perfect for temporal comparisons between clips
- ✅ Easy to work with for model benchmarking
Activity Coverage
The dataset captures metal industry operations including:
- 🔥 Welding and joining
- ⚙️ Grinding and finishing
- ✂️ Metal cutting operations
- 🔩 Machining and drilling
- 🔍 Quality inspection
- 🛠️ Manual metal fabrication
Usage
Load with 🤗 datasets library
from datasets import load_dataset
dataset = load_dataset("verbosetechlabsllp/metal-industry-operations-egocentric-sample")
print(dataset)
Load metadata directly with Pandas
import pandas as pd
df = pd.read_csv("hf://datasets/verbosetechlabsllp/metal-industry-operations-egocentric-sample/metadata.csv")
print(df.head())
print(f"Total duration: {df['duration_seconds'].sum() / 60:.1f} minutes")
Download a specific video
from huggingface_hub import hf_hub_download
video_path = hf_hub_download(
repo_id="verbosetechlabsllp/metal-industry-operations-egocentric-sample",
filename="videos/metal_industry_operation01.mp4",
repo_type="dataset"
)
print(f"Video downloaded to: {video_path}")
Extract sample frames
import cv2, os
def extract_frames(video_path, out_dir, every_n_seconds=5):
os.makedirs(out_dir, exist_ok=True)
cap = cv2.VideoCapture(video_path)
fps = cap.get(cv2.CAP_PROP_FPS)
frame_interval = int(fps * every_n_seconds)
count, saved = 0, 0
while True:
ret, frame = cap.read()
if not ret: break
if count % frame_interval == 0:
cv2.imwrite(f"{out_dir}/frame_{saved:04d}.jpg", frame)
saved += 1
count += 1
cap.release()
return saved
Data Collection
- Camera view: First-person / egocentric (head-mounted or chest-mounted)
- Environment: Real metal industry / factory floor
- Lighting: Industrial factory lighting with occasional bright welding/cutting arcs
- Audio: Included in MP4 (ambient machinery, grinding, and welding sounds — usable for multimodal research)
- Recording date: July 2026
Licensing Information
CC BY 4.0 — Free for research and commercial use with attribution.
Citation
@dataset{metal_industry_operations_egocentric_2026,
title = {Metal Industry Operations — Egocentric Video Dataset (Sample)},
author = {Verbose Tech Labs LLP},
year = {2026},
url = {https://huggingface.co/datasets/verbosetechlabsllp/metal-industry-operations-egocentric-sample}
}
More Datasets from Verbose Tech Labs
This dataset is part of a larger collection of egocentric activity datasets covering:
- 👕 Clothing industry manufacturing
- 🍳 Cooking & food preparation
- 🧹 Household cleaning tasks
- 🏭 Manufacturing unit workflows (sample)
- 🛠️ Skilled commercial work (sample)
- 🧵 Textile manufacturing (sample)
- 🔌 Electronics assembly (sample)
- ⚙️ Metal industry operations (this — sample)
- ...and more categories in development
🔗 Browse all our datasets: kaggle.com/verbosetechlabsllp | huggingface.co/verbosetechlabsllp
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