ディレクトリ内にある画像をすべて合成して三種類の方式でHDR画像を作成するスクリプト

MakeHDR.py

# coding: utf-8

# In[1]:

import os
from pathlib import Path
from tqdm import tqdm
import pandas as pd
import numpy as np
import cv2

# In[2]:

# Create HDR Image Function
def MakeHDR(imagePathList, expTime, savePath, name):    
    # 画像ファイルを読み込む
    img_list = [cv2.imread(str(fn)) for fn in imagePathList]

    # 露出時間をセット
    exposure_times = np.array(expTime, dtype=np.float32)

    # Debevec法によるHDR合成
    merge_debvec = cv2.createMergeDebevec()
    hdr_debvec = merge_debvec.process(img_list, times=exposure_times.copy())
    tonemap1 = cv2.createTonemapDurand(gamma=2.2)
    res_debvec = tonemap1.process(hdr_debvec.copy())

    # Robertson法によるHDR合成
    merge_robertson = cv2.createMergeRobertson()
    hdr_robertson = merge_robertson.process(img_list, times=exposure_times.copy())
    tonemap2 = cv2.createTonemapDurand(gamma=2.2)
    res_robertson = tonemap2.process(hdr_robertson.copy())

    # Mertens法によるHDR合成
    merge_mertens = cv2.createMergeMertens()
    res_mertens = merge_mertens.process(img_list)

    # 8ビットデータに変換
    res_debvec_8bit = np.clip(res_debvec*255, 0, 255).astype('uint8')
    res_robertson_8bit = np.clip(res_robertson*255, 0, 255).astype('uint8')
    res_mertens_8bit = np.clip(res_mertens*255, 0, 255).astype('uint8')

    # 画像をファイルに保存
    cv2.imwrite(savePath + "/ldr_debvec/" + name + "_ldr_debvec.jpg", res_debvec_8bit)
    cv2.imwrite(savePath + "/ldr_robertson/" + name + "_ldr_robertson.jpg", res_robertson_8bit)
    cv2.imwrite(savePath + "/fusion_mertens/" + name + "_fusion_mertens.jpg", res_mertens_8bit)

# In[3]:

#Setup pathlib
currentPath = Path()

#Set target path
currentPath = currentPath / '2018-10-26-17-24-17-544/'

#Declare dataset list
grupPath = []

#Searth image paths
pathList = list(currentPath.glob('**/*.png'))
parentList = []
for i in range(len(pathList)):
    parentList.append(pathList[i].parent)

#Remove duplication
parentList = list(set(parentList))

#Make dataset list
for i in range(len(parentList)):
    parentPath = parentList[i]
    if(str(parentPath).find('test') == -1 and str(parentPath).find('result') == -1):
        imagePathList = [p.resolve() for p in parentPath.iterdir()]
        expTimeList = []        
        for t in range(len(imagePathList)):
            filename = str(imagePathList[t].stem)
            nameStruct = filename.split('_')
            expTimeList.append(float(nameStruct[1]))

        data=[parentPath.absolute(), imagePathList, expTimeList]

        grupPath.append(data)

#Output path
for i in range(len(grupPath)):
    print(" + " + grupPath[i][0].name)
    for t in range(len(grupPath[i][1])):
         print(" |-- " + grupPath[i][1][t].name + ", " + str(grupPath[i][2][t]))

# In[4]:

# For convert to csv 
# data = dict()
# data['path'] = grupPath[i][1]
# data['time'] = grupPath[i][2]
# d = pd.DataFrame.from_dict(data)
# d.to_csv('./time.csv')

#Main processing
for i in tqdm(range(len(grupPath))):
    MakeHDR(grupPath[i][1],grupPath[i][2],str(grupPath[i][0].parent), grupPath[i][0].name)
    saveDirPath = str(grupPath[i][0].parent) + "/" + "result"
#Make save directory
    try:
        os.mkdir(saveDirPath)
        os.mkdir(saveDirPath+"/ldr_robertson")
        os.mkdir(saveDirPath+"/ldr_debvec")
        os.mkdir(saveDirPath+"/fusion_mertens")
    except FileExistsError:
        print("Exists")
    MakeHDR(grupPath[i][1],grupPath[i][2],saveDirPath,grupPath[i][0].name)