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| import cv2 | |
| import numpy as np | |
| import os | |
| import matplotlib.pyplot as plt | |
| import io | |
| from PIL import Image | |
| import numpy as np | |
| def process_bgr_image(img, lb, ub, channel): | |
| # Define the lower and upperbounds based on the image channel. | |
| if channel == 'Blue': | |
| lb = np.array([lb, 0, 0], np.uint8) | |
| ub = np.array([ub, 255, 255], np.uint8) | |
| elif channel == 'Green': | |
| lb = np.array([0, lb, 0], np.uint8) | |
| ub = np.array([255, ub, 255], np.uint8) | |
| elif channel == 'Red': | |
| lb = np.array([0, 0, lb], np.uint8) | |
| ub = np.array([255, 255, ub], np.uint8) | |
| # Calculate the histograms for the BGR color space and the Hue channel in the HSV image. | |
| hist_b, hist_g, hist_r = calculateHistogram(img, mode='BGR') | |
| # Plot the histograms | |
| hist_bgr = plotHistogram((hist_b, hist_g, hist_r), mode='BGR') | |
| # Calculate the mask for the given bounds from hsv image | |
| op = calculateMask(img, lb, ub, mode='BGR') | |
| return hist_bgr, op | |
| def process_hsv_image(img, lb, ub): | |
| # Conver the image to the HSV color space | |
| img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) | |
| # Define the lower and upperbounds for Hue | |
| lb = np.array([lb, 0, 0], np.uint8) | |
| ub = np.array([ub, 255, 255], np.uint8) | |
| # Calculate the histograms for the BGR color space and the Hue channel in the HSV image. | |
| hist_hue = calculateHistogram(img_hsv, mode='HSV') | |
| # Plot the histogram. | |
| hist_hsv = plotHistogram(hist_hue, mode='HSV') | |
| # Calculate the mask for the given bounds from hsv image | |
| op = calculateMask((img_hsv, img), lb, ub, mode='HSV') | |
| return hist_hsv, op | |
| def calculateHistogram(img, mode): | |
| if mode == 'BGR': | |
| hist_b = cv2.calcHist([img], [0], None, [256], [0,255]) | |
| hist_g = cv2.calcHist([img], [1], None, [256], [0,255]) | |
| hist_r = cv2.calcHist([img], [2], None, [256], [0,255]) | |
| return hist_b, hist_g, hist_r | |
| elif mode == 'HSV': | |
| hist_hue = cv2.calcHist([img], [0], None, [180], [0,180]) | |
| return hist_hue | |
| def plotHistogram(hists, mode): | |
| if mode == 'BGR': | |
| hist_b, hist_g, hist_r = hists | |
| plt.figure(figsize=(10,2)) | |
| plt.plot(hist_b, color='b', label='Blue') | |
| plt.plot(hist_g, color='g', label='Green') | |
| plt.plot(hist_r, color='r', label='Red') | |
| plt.xlim([0, 255]) | |
| plt.legend() | |
| buf_bgr= io.BytesIO() | |
| plt.savefig(buf_bgr, format='png') | |
| buf_bgr.seek(0) | |
| hist_bgr = Image.open(buf_bgr) | |
| plt.close() | |
| return hist_bgr | |
| if mode == 'HSV': | |
| hist_hue = hists | |
| plt.figure(figsize=(10,2)) | |
| plt.plot(hist_hue, color='black', label='Black') | |
| plt.xlim([0, 180]) | |
| buf_hsv = io.BytesIO() | |
| plt.savefig(buf_hsv, format='png') | |
| buf_hsv.seek(0) | |
| hist_hsv = Image.open(buf_hsv) | |
| plt.close() | |
| return hist_hsv | |
| def calculateMask(imgs, lb, ub, mode): | |
| op = None | |
| if mode == 'BGR': | |
| img = imgs | |
| mask_1d = cv2.inRange(img, lb, ub) | |
| mask_3d = cv2.merge([mask_1d, mask_1d, mask_1d]) | |
| op = cv2.bitwise_and(img, mask_3d) | |
| if mode == 'HSV': | |
| img_hsv, img = imgs | |
| mask_1d = cv2.inRange(img_hsv, lb, ub) | |
| mask_3d = cv2.merge([mask_1d, mask_1d, mask_1d]) | |
| op = cv2.bitwise_and(img, mask_3d) | |
| return op |