Resolve "Create a parsing for the training and test input sets."

README.md

-# HVM Image Clf
+# Introduction
 
+# Prerequisites for Use
+1. Download the training data [Here](https://isic-challenge-data.s3.amazonaws.com/2018/ISIC2018_Task3_Training_Input.zip)
+2. Download the training ground truth [Here](https://isic-challenge-data.s3.amazonaws.com/2018/ISIC2018_Task3_Training_GroundTruth.zip)
+3. Download the test data images [Here](https://isic-challenge-data.s3.amazonaws.com/2018/ISIC2018_Task3_Validation_Input.zip)
+4. Download the test data ground truth [Here](https://isic-challenge-data.s3.amazonaws.com/2018/ISIC2018_Task3_Validation_GroundTruth.zip)
+5. Unzip the files into the data folder in this repository.
\ No newline at end of file

data_processing.py

+import os
+import cv2 #vision task package opencv-python
+import pandas as pd
+import glob
+import numpy as np
+
+def load_transform_images(folder):
+    """[summary]
+
+    Args:
+        filename ([type]): [description]
+    """
+    images = [cv2.imread(file, flags=cv2.IMREAD_GRAYSCALE) for file in glob.glob("./data/"+ folder+"/*.jpg")]
+    return images
+
+def transform(data):
+    flat = []
+    df = pd.DataFrame()
+    
+    for i,img in enumerate(data):
+        scale = (img.astype(np.float32) - 127.5)/127.5
+        scale = scale.reshape(1,-1)
+        df = df.append(pd.Series(scale[0]), ignore_index=True)
+        
+    return df
+
+# def batch_data(data):
+