Lab_plt-comp.py

#!/usr/bin/env python
import os
import sys
import cv2
import numpy as np
import colorsys
import matplotlib.pyplot as plt
import math
from scipy import stats

def Lab_plt(IMG_DIR, IMG_DIR2, p_title):
    files = os.listdir(IMG_DIR)
    files = sorted(files)
    fps = 24
    Ll=[];Lc=[]
    for i, file in enumerate(files):
        if not i % (fps / 8) == 0:
                continue
        img_path = IMG_DIR + '/' + file
        img = cv2.imread(img_path)
        lab_img = cv2.cvtColor(img, cv2.COLOR_BGR2Lab)
        mean_l = int(np.mean(lab_img[:,:,0]))
        mean_a = int(np.mean(lab_img[:,:,1]))
        mean_b = int(np.mean(lab_img[:,:,2]))
        mean_c = math.sqrt(mean_a**2+mean_b**2)
        Ll.append(mean_l)
        Lc.append(mean_c)

    l_mean = np.mean(Ll)
    c_mean = np.mean(Lc)

    files = os.listdir(IMG_DIR2)
    files = sorted(files)
    fps = 24
    Ll2=[];Lc2=[]
    for i, file in enumerate(files):
        if not i % (fps / 8) == 0:
                continue
        img_path = IMG_DIR2 + '/' + file
        img = cv2.imread(img_path)
        lab_img = cv2.cvtColor(img, cv2.COLOR_BGR2Lab)
        mean_l = int(np.mean(lab_img[:,:,0]))
        mean_a = int(np.mean(lab_img[:,:,1]))
        mean_b = int(np.mean(lab_img[:,:,2]))
        mean_c = math.sqrt(mean_a**2+mean_b**2)
        Ll2.append(mean_l)
        Lc2.append(mean_c)

    l_mean2 = np.mean(Ll2)
    c_mean2 = np.mean(Lc2)

    p_fname =p_title

    plt.rcParams['font.family'] = 'sans-serif'
    plt.rcParams['font.sans-serif'] = ['IPAPGothic', 'VL PGothic']

    fig = plt.figure(figsize=(16, 8), dpi=100, facecolor='lightgray', tight_layout=True)
    ax4 = fig.add_subplot(111, fc='w', xlabel='c*(彩度)', ylabel='L*(明度)')
    ax4.set_title(p_title +" L*a*b* トーン:明度x彩度　比較")

    ax4.scatter(Lc,Ll,c="blue",s=1,label="TV1期")
    ax4.axhline(y=l_mean , color='aqua',linestyle='dashed', linewidth=1)
    ax4.text(145, l_mean, "mean:" + str(round(l_mean,1)), ha='right', size=10)
    ax4.axvline(x=c_mean , color='aqua',linestyle='dashed', linewidth=1)
    ax4.text(c_mean, -4, "mean:" + str(round(c_mean,1)), ha='right', size=10)

    ax4.scatter(Lc2,Ll2,c="red",s=1,label="アンコン編")
    ax4.axhline(y=l_mean2 , color='magenta',linestyle='dashed', linewidth=1)
    ax4.text(145, l_mean2, "mean:" + str(round(l_mean2,1)), ha='right', size=10)
    ax4.axvline(x=c_mean2 , color='magenta',linestyle='dashed', linewidth=1)
    ax4.text(c_mean2, -4, "mean:" + str(round(c_mean2,1)), ha='right', size=10)
    ax4.set_xlim([140, 240])
    ax4.set_ylim([-10, 255])

    ax4.grid()
    plt.legend(loc="upper left")
    fig.savefig(p_fname +'-lab-tone-comp.png', facecolor=fig.get_facecolor())
    plt.show()


if __name__ == '__main__':
    IMG_DIR = sys.argv[1]
    IMG_DIR2 = sys.argv[2]
    p_title = sys.argv[3]
    Lab_plt(IMG_DIR, IMG_DIR2, p_title)