Datasets:

BWS-Data-Solutions
/

BWS-Privacy-Blurred-POC

language: en
license: other
pretty_name: Privacy-Native Blurred Environments (POC)
task_categories:
  - image-classification
  - image-segmentation
tags:
  - depth-estimation
  - bokeh
  - segmentation
  - background-removal
  - clear-act-compliant
  - privacy-safe
  - synthetic-like
size_categories:
  - 10K<n<100K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': 01_Studio__Fashion_60_JPEGs
            '1': 02_Photo_Booth__Series_60_JPEGs
  splits:
    - name: train
      num_bytes: 37718791.6
      num_examples: 96
    - name: validation
      num_bytes: 9185666.4
      num_examples: 24
  download_size: 45508376
  dataset_size: 46904458

Privacy-Native Blurred Environments (POC)

High-quality, heavily blurred environmental images designed specifically for computer vision and depth estimation training — built from the ground up to eliminate biometric, PII, and Right of Publicity risks.

This Proof of Concept dataset is 100% proprietary (shot and owned by Brett Williams Studios). No scraped, web-crawled, or third-party data.

Why This Dataset Exists

With the CLEAR Act 2026 disclosure requirements now active, many teams need training data that is verifiably clean. This collection removes facial geometries, identifiable features, and personal data while preserving rich environmental context perfect for:

Depth estimation & monocular depth models
Bokeh simulation & portrait effects
Background composition & segmentation
Scene understanding
Synthetic data augmentation

Dataset Properties

Total Images (POC): 120 high-fidelity samples (full 25k+ production set available)
Style: Multi-environment indoor/outdoor scenes with intentionally blurred human figures
Resolution: High-resolution originals (downsampled versions also available)
Format: JPG + metadata
IP Status: Fully cleared for commercial AI training use

Dataset Splits

Split	Images	Purpose
`train`	96	Main training / development
`validation`	24	Evaluation & quick preview

Legal & Compliance

Biometric/PII free by design
Delivered with SHA-256 cryptographic manifests for audit trails
Non-exclusive commercial licensing available
Full production dataset available via secure AWS S3 -https://www.kaggle.com/datasets/createphotos/rivacy-native-blurred-environments-poc

Getting Started

from datasets import load_dataset

dataset = load_dataset("BWS-Data-Solutions/BWS-Privacy-Blurred-POC")

# View an example
example = dataset["train"][0]
example["image"].show()