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README.md

 # Indian Classical Dance Classification from Dance Poses
 ### Authors:
-Aarushi Aiyyar : 203050045
-Bhavesh Yadav : 193050052
-Khyati Oswal : 203050058
-Raj Gite : 203050092
-Smit Gangurde : 203050108
+Aarushi Aiyyar : 203050045\
+Bhavesh Yadav : 193050052\
+Khyati Oswal : 203050058\
+Raj Gite : 203050092\
+Smit Gangurde : 203050108\
 Yavnika Bhagat : 203050041
 ### Problem Statement:
-Identify the type of Indian dance form from a dance pose image. Use multiple techniques to classify the images and compare the various techniques.
+Identify the type of Indian dance form from a dance pose image. Use multiple techniques to classify the images and compare the various techniques.\
 ### Dataset:
- https://www.kaggle.com/somnath796/indian-dance-form-recognition
- Train Images: 364 | Test Images: 156
+ https://www.kaggle.com/somnath796/indian-dance-form-recognition\
+ Train Images: 364 | Test Images: 156\
  Number of classes: 8
 ### Techniques used and their test accuracies:
 |Implementation |Test Accuracy  |
@@ -23,14 +23,15 @@ Implemented Cross Validation.
 ### Running the code:
 Python Notebooks along with the necessary code are provided in the repository, in the folder 'Notebooks/'.
 
- 1. Custom CNN notebook:
+ 1. Custom CNN notebook:\
 Open the notebook, import the 'helpers' directory and run the cells.
- 2. VGG16: 
+ 2. VGG16:\
 Open the notebook, and run the cells.
- 3. ResNet152 using Monk:
-i. You can directly download the ipynb file and run it on kaggle
-ii. Upload dataset with appropriate data structure
-iii. Download the uploaded .py file, according to the numbers given in the file, execute commands on Kaggle notebook.
+ 3. ResNet152 using Monk:\
+i. You can directly download the ipynb file and run it on kaggle\
+ii. Upload dataset with appropriate data structure\
+iii. Download the uploaded .py file, according to the numbers given in the file, execute commands on Kaggle notebook.\
+
 ### References:
 
  1. https://www.kaggle.com/singhuday/identifythedanceform/version/1