update

OAIZIB-CM.py

@@ -15,46 +15,16 @@ from datasets import (
 logger = datasets.logging.get_logger(__name__)
 
 _CITATION = """\
-@article{YAO2024103035,
-  title = {CartiMorph: A framework for automated knee articular cartilage morphometrics},
-  journal = {Medical Image Analysis},
-  author = {Yongcheng Yao and Junru Zhong and Liping Zhang and Sheheryar Khan and Weitian Chen},
-  volume = {91},
-  pages = {103035},
-  year = {2024},
-  issn = {1361-8415},
-  doi = {https://doi.org/10.1016/j.media.2023.103035}
-}
-
-@InProceedings{10.1007/978-3-031-82007-6_16,
-  author = {Yao, Yongcheng and Chen, Weitian},
-  editor = {Wu, Shandong and Shabestari, Behrouz and Xing, Lei},
-  title = {Quantifying Knee Cartilage Shape and Lesion: From Image to Metrics},
-  booktitle = {Applications of Medical Artificial Intelligence},
-  year = {2025},
-  publisher = {Springer Nature Switzerland},
-  address = {Cham},
-  pages = {162--172}
-}
+Please cite these papers when using this dataset:
+- CartiMorph: A framework for automated knee articular cartilage morphometrics
+- Quantifying Knee Cartilage Shape and Lesion: From Image to Metrics
 """
 
 _DESCRIPTION = """\
 This is the official release of the OAIZIB-CM dataset.
-
-OAIZIB-CM is based on the OAIZIB dataset.
-OAIZIB paper: Automated Segmentation of Knee Bone and Cartilage combining Statistical Shape Knowledge 
-and Convolutional Neural Networks: Data from the Osteoarthritis Initiative.
-In OAIZIB-CM, tibial cartilage is split into medial and lateral tibial cartilages.
-OAIZIB-CM includes CLAIR-Knee-103R, consisting of:
-  - a template image learned from 103 MR images of subjects without radiographic OA,
-  - a corresponding 5-ROI segmentation mask for cartilages and bones, and
-  - a corresponding 20-ROI atlas for articular cartilages.
-
-This dataset is released under the CC BY-NC 4.0 license.
+(https://huggingface.co/datasets/YongchengYAO/OAIZIB-CM/blob/load_dataset-support/README.md)
 """
 
-_HOMEPAGE_URL = "https://github.com/YongchengYAO/CartiMorph"
-
 
 class OAIZIBCMDataset(GeneratorBasedBuilder):
     VERSION = datasets.Version("1.0.0")
@@ -80,21 +50,25 @@ class OAIZIBCMDataset(GeneratorBasedBuilder):
                     "mask_path": Value("string"),
                 }
             ),
-            homepage=_HOMEPAGE_URL,
             citation=_CITATION,
         )
 
     def _split_generators(self, dl_manager):
         # Download dataset metadata and data files
         base_url = "https://huggingface.co/datasets/YongchengYAO/OAIZIB-CM/resolve/load_dataset-support"
-        train_csv_url = f"{base_url}/train.csv"
-        test_csv_url = f"{base_url}/test.csv"
+        # train_csv_url = f"{base_url}/train.csv"
+        # test_csv_url = f"{base_url}/test.csv"
+        train_csv_url = f"train.csv"
+        test_csv_url = f"test.csv"
         csv_paths = dl_manager.download({"train": train_csv_url, "test": test_csv_url})
         logger.info(f"Downloaded CSV paths: {csv_paths}")
 
         # Extract main dataset archive
+        # data_root_dir = dl_manager.download_and_extract(
+        #     "https://huggingface.co/datasets/YongchengYAO/OAIZIB-CM/resolve/load_dataset-support/data/OAIZIB-CM.zip"
+        # )
         data_root_dir = dl_manager.download_and_extract(
-            "https://huggingface.co/datasets/YongchengYAO/OAIZIB-CM/resolve/load_dataset-support/data/OAIZIB-CM.zip"
+            "data/OAIZIB-CM.zip"
         )
         data_dir = os.path.join(data_root_dir, "OAIZIB-CM")
         logger.info(f"Data directory set to {data_dir}")