Eye_caputure_Rakhi

import skimage
from skimage import io, transform
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib as mt
import math

import warnings
warnings.simplefilter("ignore")

def NCC(patch, template):
    row, column = template.shape[0], template.shape[1]        
    NCC_r = np.sum(((patch[:,:,0] - np.mean(patch[:,:,0])) * (template[:,:,0]- temp_mean[:,:,0]))/(np.std(patch[:,:,0], ddof=1) * temp_std[0]))
    NCC_g = np.sum(((patch[:,:,1] - np.mean(patch[:,:,1])) * (template[:,:,1]- temp_mean[:,:,1]))/(np.std(patch[:,:,1], ddof=1) * temp_std[1]))
    NCC_b = np.sum(((patch[:,:,2] - np.mean(patch[:,:,2])) * (template[:,:,2]- temp_mean[:,:,2]))/(np.std(patch[:,:,2], ddof=1) * temp_std[2]))
    NCC   = NCC_r + NCC_g + NCC_b
    NCC  = NCC / ((s_row * s_col)- 1)
    
    return NCC

def plot_match(index, position):
    match = search[int(sorted_patch_ncc[index, 1]):int(sorted_patch_ncc[index, 1]) + temp_row, int(sorted_patch_ncc[index, 0]):int(sorted_patch_ncc[index, 0]) + temp_col]
    ax = fig.add_subplot(2, 3, position)
    ax.imshow(match)
    plt.title(f"k = {index + 1} \n Location = ({int(sorted_patch_ncc[index, 1] + temp_row/2)}, {int(sorted_patch_ncc[index, 0] + temp_col/2)})")
    plt.axis("off")
    
    
s = io.imread('no2.jpg')
t = io.imread('template_eye.png')

scale_factor = 0.3

# Downscale the image using the rescale function
search = transform.rescale(s, scale_factor, anti_aliasing=True, multichannel=True)
template= transform.rescale(t, scale_factor, anti_aliasing=True, multichannel=True)


print(search.shape)
print(template.shape)

temp_row, temp_col = template.shape[0], template.shape[1]
s_row, s_col = search.shape[0], search.shape[1]

temp_mean = np.mean(template, axis=(0, 1), keepdims=True)
temp_std = np.std(template, axis=(0, 1), ddof=1)


patch_ncc = []

for i in range(s_row - temp_row):
    for j in range(s_col - temp_col):
        patch = search[i:i+temp_row, j:j+temp_col]
        ncc_ = NCC(patch, template)
        patch_ncc.append([j, i, ncc_])


patch_ncc.sort(reverse=True, key=lambda x: x[2])
sorted_patch_ncc = np.array(patch_ncc)


ncc_plot = pd.Series(sorted_patch_ncc[:, 2])
ncc_plot.plot.line(xlabel='k', ylabel='NCC')




fig = plt.figure(figsize=(30, 10))
plot_match(0, 1)
plot_match(1, 2)
plot_match(4, 3)
plot_match(9, 4)
plot_match(99, 5)
plot_match(499, 6)

plt.show()