README.md

metadata

title: Illumination-Invariant Fish Classification
emoji: 🐟
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 6.5.1
python_version: '3.10'
app_file: app.py
pinned: false

Illumination-Invariant Identification of Wild and Farmed Larimichthys crocea

via Cross-Modal 3D Shape Priors

Overview

This Space demonstrates an illumination-invariant fish classification system that identifies wild and farmed Larimichthys crocea (yellow croaker) using cross-modal 3D shape priors.

Features

• Multi-modal Fusion: Integrates RGB and depth information for enhanced feature representation
• Shape-Guided Attention: Leverages depth-estimated shape information to guide RGB feature learning
• Real-time Inference: Fast classification with pre-trained models
• Grad-CAM Visualization: Visualize model attention with heatmaps

Usage

Upload an image of a fish, and the system will:

1. Detect if it's a yellow croaker (confidence threshold: 0.5)
2. If detected, classify it as Wild or Farmed
3. Display detection mask and Grad-CAM heatmap for interpretability

Model Architecture

• Backbone: ResNet50
• Depth Decoder: UNet-style decoder with attention gates
• Classification Head: Fully connected layers with dropout

Citation

If you use this code in your research, please cite: