How to plot the colors of each pixel in the image?

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I'm working on image color recognition, so I'm converting the RGB image to Lab because it's the closest color space to human vision. After that, I get each one of the Lab's 3 channels and I want to plot in the 3D graphic the color variations that I identified in the converted image. How do I plot the graphic with the colors of the image? 

import cv2
import numpy as np
import urllib
import mpl_toolkits.mplot3d.axes3d as p3
import matplotlib.pyplot as plt

# Load an image that contains all possible colors.
request = urllib.urlopen('IMD015.bmp')
image_array = np.asarray(bytearray(request.read()), dtype=np.uint8)
image = cv2.imdecode(image_array, cv2.CV_LOAD_IMAGE_COLOR)

lab_image = cv2.cvtColor(image, cv2.COLOR_BGR2LAB)
l_channel,a_channel,b_channel = cv2.split(lab_image)

# Print the minimum and maximum of lightness.
print np.min(l_channel) # 0
print np.max(l_channel) # 255

# Print the minimum and maximum of a.
print np.min(a_channel) # 42
print np.max(a_channel) # 226

# Print the minimum and maximum of b.
print np.min(b_channel) # 20
print np.max(b_channel) # 223

#colours.append([l_channel, a_channel, b_channel])

fig = plt.figure()
ax = p3.Axes3D(fig)
ax.scatter(l_channel, a_channel, b_channel, c='b', marker='o')

ax.set_xlabel('L')
ax.set_ylabel('A')
ax.set_zlabel('B')
fig.add_axes(ax)
#plt.savefig('plot-15.png')
plt.show()

The output is:

    
asked by anonymous 13.10.2018 / 01:59

1 answer

3

Solution

  • Converts to CIELAB using OpenCV.
  • First illustrates the 2D chart, with each color channel.
  • Then the 3D chart for each Channel.

    • Code 

    import numpy as np
import cv2
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D


def mostrar_imagem_Lab(nome, img):
    plt.figure(nome)
    plt.subplot(2, 2, 1)
    plt.imshow(img)

    plt.subplot(2, 2, 2)
    plt.imshow(img[:, :, 0], cmap='Greys')

    plt.subplot(2, 2, 3)
    plt.imshow(img[:, :, 1], cmap='PuBuGn_r')

    plt.subplot(2, 2, 4)
    plt.imshow(img[:, :, 2], cmap='YlGnBu_r')


img = cv2.imread("C:\Users\usuario\Desktop\teste\4-cube_horribly_scrambled.png")
lab_image = cv2.cvtColor(img, cv2.COLOR_BGR2LAB)
h, w, c = img.shape
y = range(h)
x = range(w)
X, Y = np.meshgrid(x, y)

mostrar_imagem_Lab('Gráfico Lab', lab_image)

plt.figure('Canal L')
ax = plt.axes(projection='3d')

ax.plot_surface(X, Y, lab_image[:, :, 0], cmap='Greys')

plt.figure('Canal a')
ax = plt.axes(projection='3d')

ax.plot_surface(X, Y, lab_image[:, :, 1], cmap='PuBuGn_r')

plt.figure('Canal b')
ax = plt.axes(projection='3d')

ax.plot_surface(X, Y, lab_image[:, :, 2], cmap='YlGnBu_r')

plt.show()

    Result

    With the following test image:

    Thefollowing2Dresultwasobtained:

    3DresultforLchannel:

    3Dresultforchannela:

    3Dresultforchannelb:

    Note

    Ifthecolormapisdifferent(RGB,BGR,HSV,etc.),checkthefollowinglinks:

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