This code is for OCR using ANN ,it contains one hidden layer, the input is an image of size 28x28.the code runs without any error but the output is not at all accurate even after giving 5000+ images for training.I am using the mnist dataset which is of the form of jpg images. Please tell me what is wrong with my logic.
import numpy as np
from PIL import Image
import random
from random import randint
y = [[0,0,0,0,0,0,0,0,0,0]]
W1 = [[ random.uniform(-1, 1) for q in range(40)] for p in range(784)]
W2 = [[ random.uniform(-1, 1) for q in range(10)] for p in range(40)]
def sigmoid(x):
global b
return (1.0 / (1.0 + np.exp(-x)))
#run the neural net forward
def run(X, W):
return sigmoid(np.matmul(X,W)) #1x2 * 2x2 = 1x1 matrix
#cost function
def cost(X, y, W):
nn_output = run(X, W)
return ((nn_output - y))
def gradient_Descent(X,y,W1,W2):
alpha = 0.12 #learning rate
epochs = 15000 #num iterations
for i in range(epochs):
Z2=sigmoid(np.matmul(run(X,W1),W2)) #final activation function(1X10))
Z1=run(X,W1) #first activation function(1X40)
phi1=Z1*(1-Z1) #differentiation of Z1
phi2=Z2*(1-Z2) #differentiation of Z2
delta2 = phi2*cost(Z1,y,W2) #delta for outer layer(1X10)
delta1 = np.transpose(np.transpose(phi1)*np.matmul(W2,np.transpose(delta2)))
deltaW2 = alpha*(np.matmul(np.transpose(Z1),delta2))
deltaW1 = alpha*(np.matmul(np.transpose(X),delta1))
W1=W1+deltaW1
W2=W2+deltaW2
def Training():
for j in range(8):
y[0][j]=1
k=1
while k<=15: #5421
print(k)
q=0
img = Image.open('mnist_jpgfiles/train/mnist_'+str(j)+'_'+str(k)+'.jpg')
iar = np.array(img) #image array
ar=np.reshape(iar,(1,np.product(iar.shape)))
ar=np.array(ar,dtype=float)
X = ar
'''
for p in range(784):
if X[0][p]>0:
X[0][p]=1
else:
X[0][p]=0
'''
k+=1
gradient_Descent(X,y,W1,W2)
print(np.argmin(cost(run(X,W1),y,W2)))
#print(W1)
y[0][j]=0
Training()
def test():
global W1,W2
for j in range(3):
k=1
while k<=5: #890
img = Image.open('mnist_jpgfiles/test/mnist_'+str(j)+'_'+str(k)+'.jpg')
iar = np.array(img) #image array
ar=np.reshape(iar,(1,np.product(iar.shape)))
ar=np.array(ar,dtype=float)
X = ar/256
'''
for p in range(784):
if X[0][p]>0:
X[0][p]=1
else:
X[0][p]=0
'''
k+=1
print("Should be "+str(j))
print((run(run(X,W1),W2)))
print((np.argmax(run(run(X,W1),W2))))
print("Testing.....")
test()