Created
November 19, 2023 00:52
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extracting green plant columns from the field image
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| import cv2 | |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| img = cv2.imread("field.jpg") | |
| img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) | |
| lower_bound = np.array([35, 50, 50]) # lower bound green in HSV | |
| upper_bound = np.array([75, 255, 255]) # upper bound green in HSV | |
| mask = cv2.inRange(img_hsv, lower_bound, upper_bound) # this mask will filter out everything that is not green, green being defined by the lower and upper bounds in the HSV space | |
| segmented_image = cv2.bitwise_and(img_hsv, img_hsv, mask=mask) # extract the green things from the image using the mask | |
| segmented_image = cv2.cvtColor(segmented_image, cv2.COLOR_HSV2BGR) | |
| rotation_matrix = cv2.getRotationMatrix2D((img.shape[1]/2, img.shape[0]/2), -35, 1) | |
| rotated_image = cv2.warpAffine(segmented_image, rotation_matrix, (img.shape[1], img.shape[0])) | |
| # draw a histogram of the green values in the rotated_image along the x axis | |
| green_values = [] | |
| for i in range(rotated_image.shape[1]): | |
| for j in range(rotated_image.shape[0]): | |
| if rotated_image[j, i, 1] > 0: # we are back in the BGR format | |
| green_values.append(i) | |
| f, plots = plt.subplots(2,1) | |
| plots[0].hist(green_values, bins=range(0, rotated_image.shape[1], 1)) | |
| plots[1].imshow(rotated_image) | |
| plt.show() |
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