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@akehoyayoi
Last active June 17, 2022 05:50
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簡易画像データ水増しツール
import glob
import cv2
import numpy as np
import os
import tqdm
from PIL import Image, ImageChops
def effect_gamma(image):
gamma = 1.5
gamma_cvt = np.zeros((256,1),dtype = 'uint8')
for i in range(256):
gamma_cvt[i][0] = 255 * (float(i)/255) ** (1.0/gamma)
return cv2.LUT(image,gamma_cvt)
def extract_filename(path):
basename = os.path.basename(path)
return os.path.splitext(basename)[0]
def copy_image(image):
image = cv2.imread(file)
file_name = extract_filename(file)
cv2.imwrite('./output/' + file_name + '_original.png', image)
def save_gamma_image(file):
image = cv2.imread(file)
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
image = effect_gamma(image)
file_name = extract_filename(file)
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
cv2.imwrite('./output/' + file_name + '_gamma.png', image)
def save_gaussian_image(file):
illust_im = Image.open(file).convert('RGB')
noise_im = Image.effect_noise((illust_im.width, illust_im.height), 50).convert('RGB')
result_im = ImageChops.multiply(illust_im, noise_im)
file_name = extract_filename(file)
result_im.save('./output/' + file_name + '_gaussian.png')
def save_salt_and_papper_image(file):
image = cv2.imread(file)
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
row,col,ch = image.shape
# 白
pts_x = np.random.randint(0, col-1 , 10000) #0から(col-1)までの乱数を千個作る
pts_y = np.random.randint(0, row-1 , 10000)
image[(pts_y,pts_x)] = (255,255,255) #y,xの順番になることに注意
# 黒
pts_x = np.random.randint(0, col-1 , 10000)
pts_y = np.random.randint(0, row-1 , 10000)
image[(pts_y,pts_x)] = (0,0,0)
file_name = extract_filename(file)
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
cv2.imwrite('./output/' + file_name + '_salt.png', image)
files = glob.glob("./input/*")
for file in tqdm.tqdm(files):
print(file)
copy_image(file)
save_gamma_image(file)
save_gaussian_image(file)
save_salt_and_papper_image(file)
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