# samshap

**Repository Path**: wang_yang123/samshap

## Basic Information

- **Project Name**: samshap
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2023-11-04
- **Last Updated**: 2023-11-04

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Explain Any Concept: Segment Anything Meets Concept-Based Explanation (EAC) Poster @ NeurIPS 2023
Code for the paper "Explain Any Concept: Segment Anything Meets Concept-Based Explanation".


Here is an overview of our work, and you can find more in our [Preprint](https://arxiv.org/abs/2305.10289).
![Overview](./demo.png)

Our EAC approach generates high accurate and human-understandable post-hoc explanations.
![demo](./all_demo.png)

## Downloading the SAM backbone
We use ViT-H as our default SAM model. For downloading the pre-train model and installation dependencies, please refer [SAM repo](https://github.com/facebookresearch/segment-anything#model-checkpoints).

## Explain a hummingbird on your local pre-trained ResNet-50!
Simply run the following command:
```
python demo_samshap.py
```