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---
title: Dress Detection and Classification Pipeline
emoji: π
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.
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