Lab_plt.py

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

def Lab_plt(IMG_DIR, p_title):
    files = os.listdir(IMG_DIR)
    files = sorted(files)
    fps = 24
    Lt=[];Ll=[];La=[];Lb=[];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)
        Lt.append(i/fps/60)
        Ll.append(mean_l)
        La.append(mean_a)
        Lb.append(mean_b)
        Lc.append(mean_c)

    num = fps
    b = np.ones(num)/num
    Ll2 = np.convolve(Ll, b, mode='same')
    La2 = np.convolve(La, b, mode='same')
    Lb2 = np.convolve(Lb, b, mode='same')
    Lc2 = np.convolve(Lc, b, mode='same')
    l_mean = np.mean(Ll)
    a_mean = np.mean(La)
    b_mean = np.mean(Lb)
    c_mean = np.mean(Lc)

    l_med = np.median(Ll)
    a_med = np.median(La)
    b_med = np.median(Lb)
    c_med = np.median(Lc)

    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=False)
    ax = fig.add_subplot(111, fc='w', xlabel='分(min)', ylabel='L*(明度)')
    ax.set_title(p_title +" L*a*b* L*(明度)推移")
    ax.plot(Lt, Ll, label='L*')
    ax.plot(Lt, Ll2 , 'r', label='L*:Moving average')
    ax.axhline(y=l_mean , color='g',linestyle='dashed', linewidth=1)
    ax.text(-4, l_mean, "average:" + str(round(l_mean,1)) , size=10)
    ax.set_ylim(-5,255)
    ax.grid()
    ax.legend()
    fig.savefig(p_fname +'-Lab-l.png', facecolor=fig.get_facecolor())
    plt.show()

    fig1 = plt.figure(figsize=(16, 8), dpi=100, facecolor='lightgray', tight_layout=False)
    ax1 = fig1.add_subplot(111, fc='w', xlabel='分(min)', ylabel='a*(色相)')
    ax1.set_title(p_title +" L*a*b* a*(色相)推移")
    ax1.plot(Lt, La, label='a*')
    ax1.plot(Lt, La2 , 'r', label='a*:Moving average')
    ax1.axhline(y=a_mean , color='g',linestyle='dashed', linewidth=1)
    ax1.text(-4, a_mean, "average:" + str(round(a_mean,1)) , size=10)
    ax1.set_ylim(-5,255)
    ax1.grid()
    ax1.legend()
    fig1.savefig(p_fname +'-Lab-a.png', facecolor=fig.get_facecolor())
    plt.show()

    fig2 = plt.figure(figsize=(16, 8), dpi=100, facecolor='lightgray', tight_layout=False)
    ax2 = fig2.add_subplot(111, fc='w', xlabel='分(min)', ylabel='b*(彩度)')
    ax2.set_title(p_title +" L*a*b* b*(彩度)推移")
    ax2.plot(Lt, Lb, label='b*')
    ax2.plot(Lt, Lb2 , 'r', label='b*:Moving average')
    ax2.axhline(y=b_mean , color='g',linestyle='dashed', linewidth=1)
    ax2.text(-4, b_mean, "average:" + str(round(b_mean,1)) , size=10)
    ax2.set_ylim(-5,255)    
    ax2.grid()
    ax2.legend()
    fig2.savefig(p_fname +'-Lab-b.png', facecolor=fig.get_facecolor())
    plt.show()

    fig3 = plt.figure(figsize=(16, 8), dpi=100, facecolor='lightgray', tight_layout=False)
    ax3 = fig3.add_subplot(111, fc='w', xlabel='分(min)', ylabel='c*(彩度)')
    ax3.set_title(p_title +" L*a*b* c*(彩度)推移")
    ax3.plot(Lt, Lc, label='c*')
    ax3.plot(Lt, Lc2 , 'r', label='c*:Moving average')
    ax3.axhline(y=b_mean , color='g',linestyle='dashed', linewidth=1)
    ax3.text(-4, c_mean, "average:" + str(round(b_mean,1)) , size=10)
    ax3.set_ylim(-5,255)    
    ax3.grid()
    ax3.legend()
    fig3.savefig(p_fname +'-Lab-c.png', facecolor=fig.get_facecolor())
    plt.show()


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