Update README.md

README.md

@@ -1,7 +1,3 @@
-configs:
- - config_name: data
-  data_files: main_normal.7z
-  sep: "\t"
 ---
 license: mit
 task_categories:
@@ -30,7 +26,7 @@ size_categories:
 The dataset containes invasive coronary angiograms for the coronary dominance classification task, an essential aspect in assessing the severity of coronary artery disease.
 The dataset holds 1,574 studies, including X-ray multi-view videos from two different interventional angiography systems.
 Each study has the following tags: bad quality, artifact, high uncertainty, and occlusion. Those tags help to classify dominance classification more accurately and allow to utilize the dataset for uncertainty estimation and outlier detection.
-![Dataset scheme](https://huggingface.co/datasets/BearSubj13/CoronaryDominance/blob/main/dataset_scheme.png "Dataset scheme")
+![Dataset scheme](dataset_scheme.png "Dataset scheme")
 
 More information about coronary dominance classification using neural networks in https://doi.org/10.48550/arXiv.2309.06958.
 
@@ -39,6 +35,7 @@ Some angiographic studies from the dataset are from CardioSYNTAX dataset of coro
 
 CITATION
 Please cite:
+```
 @misc{ponomarchuk2024endtoendsyntaxscoreprediction,
       title={End-to-end SYNTAX score prediction: benchmark and methods}, 
       author={Alexander Ponomarchuk and Ivan Kruzhilov and Galina Zubkova and Artem Shadrin and Ruslan Utegenov and Ivan Bessonov and Pavel Blinov},
@@ -48,3 +45,4 @@ Please cite:
       primaryClass={cs.CV},
       url={https://arxiv.org/abs/2407.19894}, 
 }
+```