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license: cc-by-nc-4.0
datasets:
- TLAIM/TAIX-Ray
language:
- en
tags:
- medical
- x-ray
- radiograph
- thorax
---
# TAIX-Ray Models
This repository provides two trained deep learning models for classifying X-ray images from the TAIX-Ray dataset:
1. Binary Classification Model - Classifies X-ray images into two categories (normal vs. abnormal).
2. Ordinal Classification Model - Predicts severity levels based on ordinal categories.
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## Code & Details:
Model definitions, training, and evaluation code are available at https://github.com/mueller-franzes/TAIX-Ray
## How to Use
### Prerequisites
Ensure you have the following dependencies installed:
```bash
pip install huggingface_hub
```
### Download
```python
from huggingface_hub import hf_hub_download
# Download the checkpoint file from Hugging Face Hub
file_path = hf_hub_download(
repo_id="TLAIM/TAIX-Ray",
filename="binary.ckpt", # binary.ckpt or ordinal.ckpt
)
# Check if the file has been correctly downloaded
print(f"Checkpoint downloaded to: {file_path}")
```
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