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Hi @jalFaizy,
Can you please post solution with highest accuracy so that we all could learn from it.
I tried many architectures but was not able to get as much accuracy.
Thanks,
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here we have used the Stochastic gradient descent optimizer (i.e optimizer =‘sgd’). did any one tried using (optimizer =‘adam’) i believe Adam is also a Stochastic Optimization algorithm. I have seen people using ‘adam’ algorithm which is yielding better results
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# Python 3 code to randomly load an image into jupyter notebook and print it and open it
import os, random
image_folder=r'C:\Users\User\Documents\ImagesFolder'
a=random.choice(os.listdir(image_folder))
print(a)
from PIL import Image
file = image_folder+'\\'+a
Image.open(file).show()
This is the simplest way I can use matplotlib to solve the problem:
import matplotlib.pyplot as plt
from random import randint
img_name = randint(0, 26542)
img = plt.imread("C:\\Users\\User\\Age Detection\\Dataset\\Train\\Train\\" + str(img_name) + ".JPG")
plt.imshow(img)