BanglaFace: A Curated In-the-Wild Bangladeshi Facial Image Dataset for Face Inpainting and Computer Vision

Description

DATASET OVERVIEW This dataset consists of 1,625 unique high-quality facial images of Bangladeshi demographics extracted from 45 YouTube videos across 9 content categories. All of these images were collected from publicly available videos which has been enlisted in video_metadat.csv. No additional personal or confidential information is included. These images are curated for face inpainting, facial recognition, and generative modeling. The dataset features both raw in-the-wild and geometrically aligned face representations with comprehensive metadata. SUMMARY STATISTICS OF DATASET - Total Images: 1,625 unique individuals (deduplicated from 80,137 raw detections) - Source Videos: 45 across 9 categories - Total Duration: 22 hours 22 minutes 24 seconds - Demographics: Bangladeshi population RAW VS. ALIGNED IMAGES - Raw Faces: Original crops from video frames via MTCNN detection, retaining natural pose and scale variations for authentic in-the-wild facial data. - Aligned Faces: Standardized 112x112 pixel images with facial landmarks normalized to consistent positions, facilitating model training on facial identity features. PROCESSING PARAMETERS - Face Detector: MTCNN with 0.85 confidence threshold - Minimum Face Resolution: 100x100 pixels - Deduplication: ResNet-34 embeddings (128-dim) with 0.54 similarity threshold - Blur Filtering: Laplacian Variance metric, threshold 80.0 - Frame Sampling: 1 frame per 10 frames - Video Resolution: Minimum 720p CATEGORY DISTRIBUTION - Festival (9 videos): 247 images, 15.20% - University (9): 319 images, 19.63% - Travel (15): 642 images, 39.51% - Market (4): 207 images, 12.74% - Public Events (3): 162 images, 9.97% - Lifestyle (1): 14 images, 0.86% - Education (1): 23 images, 1.42% - Historical Place (1): 8 images, 0.49% - Documentaries (2): 3 images, 0.18% ORGANIZATION Sequential IDs (000001-001625) are organized by category, video, and then by frame order. The image_metadata.csv and video_metadata provide complete traceability, linking each image to the source video, category, and frame ID. The directory structure is shown as follows: BanglaFace_Dataset/ ├── images/ # 1,625 raw face images (000001.jpg - 001625.jpg) ├── aligned_images/ # 1,625 aligned face images (000001.jpg - 001625.jpg) └── metadata/ └── image_metadata.csv # Complete image metadata └── video_metadata.csv # Complete video metadata USE CASES This dataset is suitable for: - Face inpainting and completion tasks - Facial recognition and verification systems - Face alignment and landmark detection - Generative model training (GANs, VAEs) - Face attribute analysis - Demographic studies on facial characteristics

Institutions

• University of Dhaka

  Dhaka Division, Dhaka

Categories

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