Breast Cancer is a serious ailment that affects a large fraction of women and the early detection of breast cancer is needed for treatment to begin early enough for them to possibly complete freedom from cancer.
The aim for this project is to tell if an image provided by the user has breast cancer or it does not.
One of the most important aims is to improve model accuracy so as to obtain a correct diagnosis of the ailment.This project uses a large database of images and uses several python libraries so as to create a model which in turn is used to obtain a result from the inputted result.
What things you need to install the software and how to install them.
- Install numpy
- Install Python 3.8-3.9
- Install pandas
- Install seaborn
- Install matplotlib
- Download the relevant libraries or if you are using google colab you only need to import them.
- Note the different graphs that have been generated with the code.
- Build the heatmap so as to understand how the model compares values.
- Create log,tree and forest during model training.
- Remember to train the models.
- Python - Language
- Pandas -Data visualisation library
- Numpy -Data visualisation library
- Matplotlib -Data visualisation library
- Re-construct image by extracting x-y coordinates from filenames.
- Detect in each 50x50 swatch
- Highlight +ve cases by localization.
- Report severity and output image of detected swatches.