/skin-cancer-classification-machine-learning

This repository contains code to train the model, trained model and code to use the model. Interestingly, the code I used to remove hair from images and smooth them. This method increased the accuracy of the model from 71% to 86%.

Primary LanguagePython

skin-cancer-classification-machine-learning

This repository contains code to train the model for Skin Lesions Classification for benign and malignant classes, trained model and code to use the model. Sample Output: alt text

Important Note

We created a new dataset using the hair removal algorithm(uploaded). Interestingly, this method increased the accuracy of the model from 71% to 86%. You can run for more epochs and increase the accuracy significantly. I didnt upload the complete dataset, just few imagse to test the model. You can download and create one using the script I shared.

Origianl Dataset link: https://drive.google.com/file/d/134IIAM_GHQ3Dd6zI15HdBTD2ZTM5ATEs/

Model Details:

alt text

Using Model

  • Open the ModelLoading.py file
  • Chagne the image path and run the code
  • It'll load the model and predict on the given image

Results

A few images I used from test set to test the model:

Class: Malignant

alt text

Class: Benign

alt text

Class: Malignant

alt text

Let me know in case of any issues or queries.
Thanks & Regards
TalhaPythoneer