| --- |
| license: cc-by-4.0 |
| task_categories: |
| - video-classification |
| - other |
| language: |
| - en |
| tags: |
| - egocentric |
| - first-person-video |
| - action-recognition |
| - electronics |
| - electronics-assembly |
| - pcb |
| - soldering |
| - manufacturing |
| - industrial |
| - computer-vision |
| - video |
| pretty_name: Electronics Assembly Egocentric Video Dataset Sample |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: metadata.csv |
| --- |
| |
| # π Electronics Assembly β 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 of electronics assembly work, captured on real electronics manufacturing floors. Videos showcase PCB assembly, component placement, soldering, and related electronics production tasks. This is a **sample release** showcasing the format and quality of our larger electronics manufacturing dataset collection. |
|
|
| ## Dataset Statistics |
|
|
| | Metric | Value | |
| |---|---| |
| | Total clips | 7 | |
| | Total duration | ~83 minutes (~1 hour 23 minutes) | |
| | Total size | ~7.6 GB | |
| | Activity class | electronics_assembly | |
| | View type | Egocentric (first-person) | |
| | Video format | MP4 | |
| | Frame rate | 30 fps | |
| | Resolution | 1080p | |
| |
| ## Supported Tasks |
| |
| - **Video classification** β classify electronics assembly activities |
| - **Action recognition** β recognize electronics manufacturing actions |
| - **Fine-grained assembly step** detection (component placement, soldering, testing) |
| - **Hand-object interaction** β tweezers, soldering irons, PCBs, components |
| - **Worker productivity** and time-motion analysis |
| - **Ergonomics research** for electronics assembly workers |
| - **Assistive robotics** for electronics manufacturing lines |
| - **Quality control** and defect detection AI training |
| - **Human-robot collaboration** in electronics assembly |
| - **Industrial AI** for smart electronics factories |
| |
| ## Dataset Structure |
| |
| ### Folder Structure |
| |
| ``` |
| electronics-assembly-egocentric-sample/ |
| βββ videos/ |
| β βββ electronics_assembly_01.mp4 |
| β βββ electronics_assembly_02.mp4 |
| β βββ electronics_assembly_03.mp4 |
| β βββ electronics_assembly_04.mp4 |
| β βββ electronics_assembly_05.mp4 |
| β βββ electronics_assembly_06.mp4 |
| β βββ electronics_assembly_07.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., `ELE_001`) | |
| | `activity` | string | Main class: `electronics_assembly` | |
| | `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 | |
| |---|---|---|---| |
| | ELE_001 | electronics_assembly_01.mp4 | 00:01:52 | 171 MB | |
| | ELE_002 | electronics_assembly_02.mp4 | 00:16:10 | 1.77 GB | |
| | ELE_003 | electronics_assembly_03.mp4 | 00:11:10 | 859 MB | |
| | ELE_004 | electronics_assembly_04.mp4 | 00:16:30 | 1.37 GB | |
| | ELE_005 | electronics_assembly_05.mp4 | 00:15:35 | 1.50 GB | |
| | ELE_006 | electronics_assembly_06.mp4 | 00:21:52 | 1.87 GB | |
| | ELE_007 | electronics_assembly_07.mp4 | 00:00:10 | 99 MB | |
| |
| ### Activity Coverage |
| |
| The dataset captures electronics assembly workflows including: |
| - π PCB (Printed Circuit Board) assembly |
| - π§² Component placement and soldering |
| - π§ Manual assembly operations |
| - π Quality inspection during assembly |
| - π οΈ Tool usage β tweezers, soldering irons, testers |
| |
| ## Usage |
| |
| ### Load with π€ datasets library |
| |
| ```python |
| from datasets import load_dataset |
|
|
| dataset = load_dataset("verbosetechlabsllp/electronics-assembly-egocentric-sample") |
| print(dataset) |
| ``` |
| |
| ### Load metadata directly with Pandas |
| |
| ```python |
| import pandas as pd |
| |
| df = pd.read_csv("hf://datasets/verbosetechlabsllp/electronics-assembly-egocentric-sample/metadata.csv") |
| print(df.head()) |
| print(f"Total duration: {df['duration_seconds'].sum() / 60:.1f} minutes") |
| ``` |
| |
| ### Download a specific video |
| |
| ```python |
| from huggingface_hub import hf_hub_download |
|
|
| video_path = hf_hub_download( |
| repo_id="verbosetechlabsllp/electronics-assembly-egocentric-sample", |
| filename="videos/electronics_assembly_02.mp4", |
| repo_type="dataset" |
| ) |
| print(f"Video downloaded to: {video_path}") |
| ``` |
| |
| ### Extract sample frames |
|
|
| ```python |
| import cv2, os |
| |
| def extract_frames(video_path, out_dir, every_n_seconds=10): |
| 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 electronics manufacturing / assembly floor |
| - **Lighting**: Industrial workshop lighting with task illumination |
| - **Audio**: Included in MP4 (ambient soldering, tool, and machine sounds β usable for multimodal research) |
| - **Recording date**: July 2026 |
|
|
| ## Licensing Information |
|
|
| **CC BY 4.0** β Free for research and commercial use with attribution. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @dataset{electronics_assembly_egocentric_2026, |
| title = {Electronics Assembly β Egocentric Video Dataset (Sample)}, |
| author = {Verbose Tech Labs LLP}, |
| year = {2026}, |
| url = {https://huggingface.co/datasets/verbosetechlabsllp/electronics-assembly-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 (sample) |
| - π οΈ Skilled commercial work (sample) |
| - π§΅ Textile manufacturing (sample) |
| - π Electronics assembly (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) |
|
|