Colab test

[vinhqngo5]

Phần 1: So sánh 2 ảnh Lena

# Import libraries
from matplotlib import pyplot as plt
from scipy import spatial
import numpy as np
import cv2 as cv
import os
!pip install gdown

# Tải 2 bức ảnh cần so sánh
!gdown --id 1NChSjvlcEnWwYUZAXHEDbqaDXWEU0IaB
!gdown --id 1dA_XAXmUO4qC5ESgu8DCjTJmaHxqAzsj

# Hàm tính His 
def calculate_histogram (image_path, create_plot=False):
    img = cv.imread(image_path, 0)
    hist,bins = np.histogram(img.flatten(),256,[0,256])
    cdf = hist.cumsum()
    cdf_normalized = cdf*float(hist.max())/cdf.max()

    if (create_plot == True):
        fig, axes = plt.subplots(1, 2)
        axes[1].plot(cdf_normalized, color = 'b')
        axes[1].hist(img.flatten(),256,[0,256,],color = 'r')
        axes[1].set_xlim([0,256])
        axes[1].legend(('cdf','histogram'), loc = 'upper left')
        axes[0].imshow(img)
        axes[0].axis("off")
        fig.tight_layout()
        return plt, hist, bins
    else:
        return hist, bins

# Tính size của ảnh
def size(img):
    return img.shape[0] * img.shape[1]

# Tính độ giống nhau giữa 2 ảnh
def compare_2_images (image_path_1, image_path_2): # Return percentage of similarity
    img_1 = cv.imread(image_path_1, 0)
    img_2 = cv.imread(image_path_2, 0)
    hist_1, bins_1 = calculate_histogram(image_path_1)
    hist_2, bins_2 = calculate_histogram(image_path_2)
    size_1 = size(img_1)
    size_2 = size(img_2)
    result = 1 - spatial.distance.cosine(hist_1 / size_1, hist_2 / size_2)
    return result

# Tạo đường dẫn tới 2 ảnh
folder_path = os.getcwd()
image_path_1 = os.path.join(folder_path, "lena.jpg")
image_path_2 = os.path.join(folder_path, "lena256.jpg")

# Tạo histogram cho 2 hình
plt_1, hist_1, bins_1 = calculate_histogram(image_path_1, True)
plt_2, hist_2, bins_2 = calculate_histogram(image_path_2, True)

[vinhqngo5]

# test code
function fancyAlert(arg) {
  if(arg) {
    $.facebox({div:'#foo'})
  }
}

# test code
function fancyAlert(arg) {
  if(arg) {
    $.facebox({div:'#foo'})
  }
}

[vinhqngo5]

[dotrann1412]

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