Load Imges for Keras Multi Class Classification

gistfile1.txt

from glob import glob
from PIL import Image
import numpy as np


def img_data(class_id,filename):
    '''
    Return an np array of
    CLASS_NUMBER 
    '''
    im=np.array(Image.open(filename))
    label = [class_id]
    r = im[:,:,0].flatten()
    g = im[:,:,1].flatten()
    b = im[:,:,2].flatten()
    return np.array(list(label) +list(r) + list(g) + list(b),np.uint8)

#
#Read our Test/Train data sets into to np
#So we then can use multi class learning on them
#
#


FILES=3
train=[]
for n in range(6):
    for f  in glob("./train/L{}/*".format(n))[:FILES]:
        train.append(img_data(n,f))
        print("train Shape is  {}".format(len(train)))
        train_data["files"].append(f)
        train_data["class"].append("L{}".format(n))
    
test=[]
for n in range(6):
    for f  in glob("./validation/L{}/*".format(n))[:FILES]:
        test.append(img_data(n,f))
        print("test Shape is  {}".format(len(test)))