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Hair Type Image Detection
An image classification model based on Google's Vision Transformer (ViT) architecture, specifically designed to identify five hairstyle types (curly, dreadlocks, twists, straight, wavy) from facial images with 93% accuracy.
Downloads 143
Release Time : 10/15/2024
Model Overview
This model is fine-tuned using the pre-trained ViT-base-patch16-224-in21k, enabling efficient and accurate classification of hairstyle types in facial images, suitable for applications in beauty, fashion, and identity recognition.
Model Features
High-precision Hairstyle Classification
Achieves an overall accuracy of 92.8% in five-class hairstyle recognition tasks, with an F1 score of 97.8% for dreadlocks classification.
ViT-based Architecture
Utilizes Google's pre-trained Vision Transformer base model, featuring powerful image feature extraction capabilities.
Lightweight Solution
Compared to traditional CNN models, it maintains high accuracy while offering more efficient inference performance.
Model Capabilities
Facial Image Analysis
Hairstyle Classification
Multi-class Image Recognition
Use Cases
Beauty & Fashion
Virtual Hairstyle Try-on
Real-time recognition of a user's current hairstyle in AR beauty applications to recommend matching hairstyle products.
Accurately identifies the user's base hairstyle type, enhancing product recommendation relevance.
Identity Recognition
Feature-assisted Identification
Serves as a supplementary feature for facial recognition systems, improving recognition accuracy through hairstyle features.
Achieves 99% recognition accuracy for dreadlocks on the test set.
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