---
title: Dress Detection and Classification Pipeline
emoji: 👗
colorFrom: pink
colorTo: purple
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
pinned: false
license: mit
---

# Dress Detection and Classification Pipeline

This application performs end-to-end dress analysis using computer vision and deep learning:

## Features

1. **Human Detection**: Detects humans in uploaded images using Faster R-CNN
2. **Dress Segmentation**: Segments the dress area using a specialized U-Net model
3. **Classification**: Classifies the dress type using a ConvNeXt model
4. **Grad-CAM**: Shows attention areas for the classification decision with interpretability

## How to Use

1. Upload an image containing a person wearing a dress
2. The pipeline will automatically:
   - Detect the person in the image
   - Segment the dress area
   - Classify the dress type
   - Show what parts of the dress the model focused on for classification


## Technical Details

- **Detection Model**: Faster R-CNN with ResNet-50 backbone
- **Segmentation Model**: U-Net with ResNet-34 encoder
- **Classification Model**: ConvNeXt v2 Base
- **Interpretability**: Grad-CAM for attention visualization

## Note

This is an academic project demonstrating the integration of multiple computer vision models in a single pipeline. The models may require fine-tuning for optimal performance on specific datasets.