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--- |
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license: cc-by-nc-4.0 |
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datasets: |
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- TLAIM/TAIX-Ray |
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language: |
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- en |
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tags: |
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- medical |
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- x-ray |
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- radiograph |
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- thorax |
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--- |
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# TAIX-Ray Models |
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This repository provides two trained deep learning models for classifying X-ray images from the TAIX-Ray dataset: |
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1. Binary Classification Model - Classifies X-ray images into two categories (normal vs. abnormal). |
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2. Ordinal Classification Model - Predicts severity levels based on ordinal categories. |
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Please see our paper for a detailed description: [Not yet available](https://arxiv.org/abs/your-paper-link) |
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<br> |
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## How to Use |
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### Prerequisites |
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Ensure you have the following dependencies installed: |
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```bash |
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pip install huggingface_hub |
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``` |
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### Download |
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```python |
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from huggingface_hub import hf_hub_download |
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# Download the checkpoint file from Hugging Face Hub |
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file_path = hf_hub_download( |
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repo_id="TLAIM/TAIX-Ray", |
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filename="binary.ckpt", # binary.ckpt or ordinal.ckpt |
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) |
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# Check if the file has been correctly downloaded |
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print(f"Checkpoint downloaded to: {file_path}") |
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``` |
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