Update README.md

README.md

@@ -19,20 +19,57 @@ size_categories:
 The CholecSeg8k dataset, an extension of the Cholec80 collection, includes 8,080 carefully annotated images from laparoscopic cholecystectomy surgeries, selected from 17 video clips in Cholec80. Each image in CholecSeg8K is pixel-level annotated for thirteen different surgical elements. The dataset is efficiently organized in a directory structure, featuring 101 folders, each containing 80 frames at a resolution of 854x480, along with three types of masks for each frame: a color mask for visualization, an annotation tool mask, and a watershed mask for simplified processing. This comprehensive dataset, freely available under the CC BY-NC-SA 4.0 license, is a critical resource for advancing the field of computer-assisted surgical procedures.
 
 
-# Loading data
+# Loading the data
+
+First install the `datasets` library, then run the following code,
 ```python
 from datasets import load_dataset
 
 dataset = load_dataset("minwoosun/CholecSeg8k", trust_remote_code=True)
 ```
 
-# Tutorial
-A short tutorial on how to load and use the data can be found in `tutorial/`.
+# Simple demo: displaying image
+
+```python
+from datasets import load_dataset
+import matplotlib.pyplot as plt
+
+dataset = load_dataset("minwoosun/CholecSeg8k", trust_remote_code=True)
+
+def display_image(image_index):
+    '''Display the image and corresponding three masks.'''
+    
+    fig, axs = plt.subplots(2, 2, figsize=(10, 10))
+    
+    for ax in axs.flat:
+        ax.axis('off')
+    
+    # Display each image in its respective subplot
+    axs[0, 0].imshow(dataset['train'][image_index]['image'])
+    axs[0, 1].imshow(dataset['train'][image_index]['color_mask'])
+    axs[1, 0].imshow(dataset['train'][image_index]['watershed_mask'])
+    axs[1, 1].imshow(dataset['train'][image_index]['annotation_mask'])
+    
+    # Adjust spacing between images
+    plt.subplots_adjust(wspace=0.01, hspace=-0.6)
+    
+    plt.show()
+
+display_image(800) # video index from 0 to 8079
+```
+![alt text](http://url/to/example.png)
 
-Download `tutorial/environment.yaml` then run the following code to set up the conda environment,
+# Citation (BibTex):
 ```
-conda env create -f tutorial_environment.yaml
-conda activate cholecseg8k
+@misc{hong2020cholecseg8k,
+      title={CholecSeg8k: A Semantic Segmentation Dataset for Laparoscopic Cholecystectomy Based on Cholec80}, 
+      author={W. -Y. Hong and C. -L. Kao and Y. -H. Kuo and J. -R. Wang and W. -L. Chang and C. -S. Shih},
+      year={2020},
+      eprint={2012.12453},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV}
+}
 ```
 
-Open `tutorial/tutorial.ipynb` using jupyter notebook.
+# Data card contact
+Min Woo Sun (minwoos@stanford.edu)