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pjm363 (Philip Monaco)'s avatar
Merge branch '11-installation-instructions' into 'main'
pjm363 (Philip Monaco) authored 
Fix EDA Errors

Closes #11

See merge request !8
c9f75671
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pjm363 (Philip Monaco)'s avatar c9f75671
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data
EDA.py
Project_Notebook.ipynb
README.md
data_processing.py
image_preprocessing.ipynb
requirements.txt
README.md

Introduction

Training of neural networks for automated diagnosis of pigmented skin lesions is hampered by the small size and lack of diversity of available dataset of dermatoscopic images. We collected dermatoscopic images from different populations, acquired and stored by different modalities. The final dataset consists of 10015 dermatoscopic images which can serve as a training set for academic machine learning purposes. Cases include a representative collection of all important diagnostic categories in the realm of pigmented lesions: Actinic keratoses and intraepithelial carcinoma / Bowen's disease (akiec), basal cell carcinoma (bcc), benign keratosis-like lesions (solar lentigines / seborrheic keratoses and lichen-planus like keratoses, bkl), dermatofibroma (df), melanoma (mel), melanocytic nevi (nv) and vascular lesions (angiomas, angiokeratomas, pyogenic granulomas and hemorrhage, vasc).

Prerequisites for Use

  1. Download the training data Here
  2. Download the training ground truth Here
  3. Download the test data images Here
  4. Download the test data ground truth Here
  5. Unzip the files into the data folder in this repository.
  6. Download required packages from requirements.txt, "pip install -r requirements.txt"