数据集获取

git clone https://github.com/ibrahimethemhamamci/DENTEX.git

curl -L -o repo.zip https://github.com/ibrahimethemhamamci/DENTEX/archive/refs/heads/main.zip
unzip repo.zip

源站 README 摘录（使用方式）

DENTEX CHALLENGE 2023

Dental Enumeration and Diagnosis on Panoramic X-rays Challenge
<details><summary>Table of Contents</summary><p>

• What is DENTEX?
• Desired Output of the Challenge
• Data
• Citing Us
• License
• Contact
  Now, all the data related to DENTEX (including test and validation sets) are available on the Hugging Face page.

What is DENTEX?

We present the Dental Enumeration and Diagnosis on Panoramic X-rays Challenge (DENTEX), organized in conjunction with the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) in 2023. The primary objective of this challenge is to develop algorithms that can accurately detect abnormal teeth with dental enumeration and associated diagnosis. This not only aids in accurate treatment planning but also helps practitioners carry out procedures with a low margin of error.
The challenge provides three types of hierarchically annotated data and additional unlabeled X-rays for optional pre-training. The annotation of the data is structured using the Fédération Dentaire Internationale (FDI) system. The first set of data is partially labeled because it only includes quadrant information. The second set of data is also partially labeled but contains additional enumeration information along with the quadrant. The third data is fully labeled because it includes all quadrant-enumeration-diagnosis information for each abnormal tooth, and all participant algorithms will be benchmarked on the third data.
DENTEX aims to provide insights into the effectiveness of AI in dental radiology analysis and its potential to improve dental practice by comparing frameworks that simultaneously point out abnormal teeth with dental enumeration and associated diagnosis on panoramic dental X-rays.
Please visit the webpage of DENTEX (Dental Enumeration and Diagnosis on Panoramic X- rays Challenge) which is held at MICCAI2023.

Desired Output of the Challenge

*Fig. 1. A desi

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

完整仓库：github.com/ibrahimethemhamamci/DENTEX