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hist_compare_many.py
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import time
from matplotlib import pyplot as plt
import os
import cv2
import numpy as np
import glob
from natsort import natsorted
import xlwt
def rgb2hsi(img_rgb):
rows = int(img_rgb.shape[0])
cols = int(img_rgb.shape[1])
B, G, R = cv2.split(img_rgb)
# Normalize to [0,1]
B = B / 255.0
G = G / 255.0
R = R / 255.0
img_hsi = img_rgb.copy()
H, S, I = cv2.split(img_hsi)
for i in range(rows):
for j in range(cols):
num = 0.5 * ((R[i, j] - G[i, j]) + (R[i, j] - B[i, j]))
den = np.sqrt((R[i, j] - G[i, j]) ** 2 + (R[i, j] - B[i, j]) * (G[i, j] - B[i, j]))
theta = float(np.arccos(num / den))
if den == 0:
H = 0
elif B[i, j] <= G[i, j]:
H = theta
else:
H = 2 * np.pi - theta
min_RGB = min(min(B[i, j], G[i, j]), R[i, j])
sum = B[i, j] + G[i, j] + R[i, j]
if sum == 0:
S = 0
else:
S = 1 - 3 * min_RGB / sum
H = H / (2 * np.pi)
I = sum / 3.0
# H = H * 360
# For ease of understanding, the results are often extended, that is, [0°, 360°], [0,100], [0,255]
img_hsi[i, j, 0] = H * 360
img_hsi[i, j, 1] = S * 100
img_hsi[i, j, 2] = I * 255
# Or in order to facilitate the calculation of the histogram, expanded to 0~255 (same as RGB)
# img_hsi[i, j, 0] = H * 255
# img_hsi[i, j, 1] = S * 255
# img_hsi[i, j, 2] = I * 255
return img_hsi
class Hisogram(object):
# def create_rgb_hist(self, image, color_type=1):
# """
# Get color space histogram
# """
# h, w, c = image.shape
# rgHist = np.zeros([16 * 16 * 16, 1], np.float32)
# print(rgHist)
# hsize = 256 / 16
# for row in range(0, h, 1):
# for col in range(0, w, 1):
# b = image[row, col, 0]
# g = image[row, col, 1]
# r = image[row, col, 2]
# index = np.int(b / hsize) * 16 * 16 + np.int(g / hsize) * 16 + np.int(r / hsize)
# rgHist[np.int(index), 0] = rgHist[np.int(index), 0] + 1
# return rgHist
def hist_compare(self, hist1, hist2):
"""
compare two histograms
"""
# hist1 = self.create_rgb_hist(image1)
# hist2 = self.create_rgb_hist(image2)
match1 = cv2.compareHist(hist1, hist2, cv2.HISTCMP_BHATTACHARYYA)
# match2 = cv2.compareHist(hist1, hist2, cv2.HISTCMP_CORREL)
# match3 = cv2.compareHist(hist1, hist2, cv2.HISTCMP_CHISQR)
# match4 = cv2.compareHist(hist1, hist2, cv2.HISTCMP_INTERSECT)
# print("Bhattacharyya distance：%20s, Correlation：%20s, Chi-square：%s, HISTCMP_INTERSECT：%s " % (match1, match2, match3, match4))
# return match1, match2, match3, match4
return match1
# def hist_image(self, image):
# color = ("Hue", "Saturity", "Intensity")
# for i, color in enumerate(color):
# hist = cv2.calcHist([image], [i], None, [256], [0, 256]) # Calculate the histogram of RGB
# # hist = cv.calcHist([image], [0,1], None, [180,256], [0,180,0,256]) # Calculate the histogram of H-S
# print(hist)
if __name__ == '__main__':
base_dir = '../data/key_data/key_global_3'
# save_path = '../data/keyframe_data/'
game_list = os.listdir(base_dir)
for game in game_list:
event_list = os.listdir(os.path.join(base_dir, game))
for event in event_list:
print(event)
workbook = xlwt.Workbook(encoding='utf-8')
pic_list = natsorted(os.listdir(os.path.join(base_dir, game, event)))
img_count = 0
for pic in pic_list:
time_start = time.time()
# print(pic)
img_list = natsorted(glob.glob(os.path.join(base_dir, game, event, pic) + '/*.png'))
img_num = len(img_list)
end = img_num - 1
firstfilename = os.path.basename(img_list[0])
first_filename = firstfilename.replace("global_", "")
save_count = 1
worksheet = workbook.add_sheet('{}'.format(pic))
worksheet.write(0, 0, label=u'pic')
worksheet.write(0, 1, label=u'Bhattacharyya distance')
# worksheet.write(0, 2, label=u'Correlation')
# worksheet.write(0, 3, label=u'Chi-square')
# worksheet.write(0, 4, label=u'HISTCMP_INTERSECT')
hist_list = []
for img in img_list:
img_rgb = cv2.imread(img)
# img_hsi = rgb2hsi(img_rgb)
hsv1 = cv2.cvtColor(img_rgb, cv2.COLOR_RGB2HSV)
hist_hi = cv2.calcHist([hsv1], [0], None, [360], [0, 359])
# hist_hi = cv2.calcHist([img_hsi], [0, 2], None, [25, 25], [0, 359, 0, 255])
hist_list.append(hist_hi)
time_end = time.time()
print('Time cost = %fs' % (time_end - time_start))
for index in range(0, end, 1):
hist_hi1 = hist_list[index]
hist_hi2 = hist_list[index + 1]
myHist = Hisogram()
# match1, match2, match3, match4 = myHist.hist_compare(hist_h1, hist_h2)
match1 = myHist.hist_compare(hist_hi1, hist_hi2)
img_name = os.path.basename(img_list[index + 1]).replace(".png", "")
flo_count = img_name.replace("global_", "")
worksheet.write(save_count, 0, flo_count)
worksheet.write(save_count, 1, match1)
# worksheet.write(save_count, 2, match2)
# worksheet.write(save_count, 3, match3)
# worksheet.write(save_count, 4, match4)
save_count += 1
img_count += 1
time_end = time.time()
print('Time cost = %fs' % (time_end - time_start))
# print(img_count)
xls_save_path = os.path.join('../data/excel', game)
isExists_2 = os.path.exists(xls_save_path)
if not isExists_2:
os.makedirs(xls_save_path)
workbook.save(xls_save_path + '/{}_hist.xls'.format(event))