【PYTHON OPENCV】Introduction to thresholding types.py

"""
Introduction to thresholding types
"""

# Import required packages:
import numpy as np
import cv2
from matplotlib import pyplot as plt


def build_sample_image():
    """Builds a sample image with 50x50 regions of different tones of gray"""

    # Define the different tones.
    # The end of interval is not included
    tones = np.arange(start=50, stop=300, step=50)
    # print(tones)

    # Initialize result with the first 50x50 region with 0-intensity level
    result = np.zeros((50, 50, 3), dtype="uint8")

    # Build the image concatenating horizontally the regions:
    for tone in tones:
        img = np.ones((50, 50, 3), dtype="uint8") * tone
        result = np.concatenate((result, img), axis=1)

    return result

def show_img_with_matplotlib(color_img, title, pos):
    """Shows an image using matplotlib capabilities"""

    # Convert BGR image to RGB
    img_RGB = color_img[:, :, ::-1]

    ax = plt.subplot(8, 1, pos)
    plt.imshow(img_RGB)
    plt.title(title)
    plt.axis('off')


# Create the dimensions of the figure and set title and color:
fig = plt.figure(figsize=(5, 9))
plt.suptitle("Simple thresholding types", fontsize=14, fontweight='bold')
fig.patch.set_facecolor('silver')

# Load the image and convert it to grayscale:
image = build_sample_image()
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# Plot the grayscale images and the histograms:
show_img_with_matplotlib(cv2.cvtColor(gray_image, cv2.COLOR_GRAY2BGR),
"img tones of gray - left to right: (0,50,100,150,200,250)", 1)

# Apply cv2.threshold() with different thresholding values:
ret1, thresh1 = cv2.threshold(gray_image, 100, 255, cv2.THRESH_BINARY)
ret2, thresh2 = cv2.threshold(gray_image, 100, 220, cv2.THRESH_BINARY)
ret3, thresh3 = cv2.threshold(gray_image, 100, 255, cv2.THRESH_BINARY_INV)
ret4, thresh4 = cv2.threshold(gray_image, 100, 220, cv2.THRESH_BINARY_INV)
ret5, thresh5 = cv2.threshold(gray_image, 100, 255, cv2.THRESH_TRUNC)
ret6, thresh6 = cv2.threshold(gray_image, 100, 255, cv2.THRESH_TOZERO)
ret7, thresh7 = cv2.threshold(gray_image, 100, 255, cv2.THRESH_TOZERO_INV)

# Plot the images:
show_img_with_matplotlib(cv2.cvtColor(thresh1, cv2.COLOR_GRAY2BGR), "THRESH_BINARY - thresh = 100 & maxValue = 255", 2)
show_img_with_matplotlib(cv2.cvtColor(thresh2, cv2.COLOR_GRAY2BGR), "THRESH_BINARY - thresh = 100 & maxValue = 220", 3)
show_img_with_matplotlib(cv2.cvtColor(thresh3, cv2.COLOR_GRAY2BGR), "THRESH_BINARY_INV - thresh = 100", 4)
show_img_with_matplotlib(cv2.cvtColor(thresh4, cv2.COLOR_GRAY2BGR), "THRESH_BINARY_INV - thresh = 100 & maxValue = 220", 5)
show_img_with_matplotlib(cv2.cvtColor(thresh5, cv2.COLOR_GRAY2BGR), "THRESH_TRUNC - thresh = 100", 6)
show_img_with_matplotlib(cv2.cvtColor(thresh6, cv2.COLOR_GRAY2BGR), "THRESH_TOZERO - thresh = 100", 7)
show_img_with_matplotlib(cv2.cvtColor(thresh7, cv2.COLOR_GRAY2BGR), "THRESH_TOZERO_INV - thresh = 100", 8)

# Show the Figure:
plt.show()