--- license: cc-by-4.0 task_categories: - video-classification - other language: - en tags: - egocentric - first-person-video - action-recognition - textile - textile-manufacturing - mill - fabric - weaving - industrial - computer-vision - video pretty_name: Textile Manufacturing Egocentric Video Dataset Sample size_categories: - n<1K configs: - config_name: default data_files: - split: train path: metadata.csv --- # ๐Ÿงต Textile Manufacturing โ€” 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:** - ๐Ÿ“ž **Phone:** [+91 7672 000 500](tel:+917672000500) - ๐Ÿ’ฌ **WhatsApp:** [+91 7672 000 500](https://wa.me/917672000500) - ๐Ÿ“ง **Email:** [Hello@VerboseTechLabs.com](mailto:Hello@VerboseTechLabs.com) - ๐ŸŒ **Website:** [VerboseTechLabs.com](https://VerboseTechLabs.com) - ๐Ÿ”— **More datasets:** [kaggle.com/verbosetechlabsllp](https://www.kaggle.com/verbosetechlabsllp) --- ## Dataset Summary First-person point-of-view (POV) video recordings from textile manufacturing operations, captured on real factory floors. This is a **sample release** showcasing the format and quality of our larger textile industry dataset collection. ## Dataset Statistics | Metric | Value | |---|---| | Total clips | 11 | | Total duration | ~30.5 minutes | | Total size | ~1.04 GB | | Activity class | textile_manufacturing | | View type | Egocentric (first-person) | | Video format | MP4 | | Frame rate | 30 fps | | Resolution | 1080p | ## Supported Tasks - **Video classification** โ€” classify textile manufacturing activities - **Action recognition** โ€” recognize textile industry actions - **Fine-grained textile activity** classification - **Worker productivity** and time-motion analysis - **Machine operation** understanding (looms, knitting machines, dyeing units) - **Ergonomics research** in textile industry - **Assistive robotics** for textile factories - **Quality control** AI training - **Industrial AI** for textile automation ## Dataset Structure ### Folder Structure ``` textile-manufacturing-egocentric-sample/ โ”œโ”€โ”€ videos/ โ”‚ โ”œโ”€โ”€ textile_01.mp4 โ”‚ โ”œโ”€โ”€ textile_02.mp4 โ”‚ โ”œโ”€โ”€ textile_03.mp4 โ”‚ โ”œโ”€โ”€ textile_04.mp4 โ”‚ โ”œโ”€โ”€ textile_05.mp4 โ”‚ โ”œโ”€โ”€ textile_06.mp4 โ”‚ โ”œโ”€โ”€ textile_07.mp4 โ”‚ โ”œโ”€โ”€ textile_08.mp4 โ”‚ โ”œโ”€โ”€ textile_09.mp4 โ”‚ โ”œโ”€โ”€ textile_10.mp4 โ”‚ โ””โ”€โ”€ textile_11.mp4 โ”œโ”€โ”€ metadata.csv โ””โ”€โ”€ 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., `TXT_001`) | | `activity` | string | Main class: `textile_manufacturing` | | `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 | |---|---|---|---| | TXT_001 | textile_01.mp4 | 00:00:30 | 24 MB | | TXT_002 | textile_02.mp4 | 00:03:00 | 104 MB | | TXT_003 | textile_03.mp4 | 00:03:00 | 104 MB | | TXT_004 | textile_04.mp4 | 00:03:00 | 104 MB | | TXT_005 | textile_05.mp4 | 00:03:00 | 104 MB | | TXT_006 | textile_06.mp4 | 00:03:00 | 104 MB | | TXT_007 | textile_07.mp4 | 00:03:00 | 104 MB | | TXT_008 | textile_08.mp4 | 00:03:00 | 104 MB | | TXT_009 | textile_09.mp4 | 00:03:00 | 104 MB | | TXT_010 | textile_10.mp4 | 00:03:00 | 104 MB | | TXT_011 | textile_11.mp4 | 00:03:00 | 104 MB | ### Activity Coverage The dataset captures diverse textile manufacturing activities from real mill floors, spanning operations across the textile production pipeline โ€” spinning, weaving, knitting, dyeing, printing, finishing, and quality control. ## Usage ### Load with ๐Ÿค— datasets library ```python from datasets import load_dataset dataset = load_dataset("verbosetechlabsllp/textile-manufacturing-egocentric-sample") print(dataset) ``` ### Load metadata directly with Pandas ```python import pandas as pd df = pd.read_csv("hf://datasets/verbosetechlabsllp/textile-manufacturing-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/textile-manufacturing-egocentric-sample", filename="videos/textile_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=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 textile mill / factory floor - **Lighting**: Industrial factory lighting - **Audio**: Included in MP4 (ambient loom, machine, and worker sounds โ€” usable for multimodal research) - **Recording period**: February 2025 โ€“ May 2026 ## Licensing Information **CC BY 4.0** โ€” Free for research and commercial use with attribution. ## Citation ```bibtex @dataset{textile_manufacturing_egocentric_2026, title = {Textile Manufacturing โ€” Egocentric Video Dataset (Sample)}, author = {Verbose Tech Labs LLP}, year = {2026}, url = {https://huggingface.co/datasets/verbosetechlabsllp/textile-manufacturing-egocentric-sample} } ``` ## More Datasets from Verbose Tech Labs This dataset is part of a larger collection of egocentric activity datasets covering: - ๐Ÿ‘• Clothing industry manufacturing - ๐Ÿณ Cooking & food preparation - ๐Ÿงน Household cleaning tasks - ๐Ÿญ Manufacturing unit workflows (sample) - ๐Ÿ› ๏ธ Skilled commercial work (sample) - ๐Ÿงต Textile manufacturing (this โ€” sample) - ...and more categories in development ๐Ÿ”— Browse all our datasets: [kaggle.com/verbosetechlabsllp](https://www.kaggle.com/verbosetechlabsllp) | [huggingface.co/verbosetechlabsllp](https://huggingface.co/verbosetechlabsllp)