83 lines
2.7 KiB
Python
83 lines
2.7 KiB
Python
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import numpy as np
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import cv2
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from multiprocessing import Pool
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import multiprocessing
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import random
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def bruit(image_orig):
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h, w, c=image_orig.shape
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n=np.random.randn(h, w, c)*random.randint(5, 30)
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return np.clip(image_orig+n, 0, 255).astype(np.uint8)
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def change_gamma(image, alpha=1.0, beta=0.0):
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return np.clip(alpha*image+beta, 0, 255).astype(np.uint8)
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def modif_img(img):
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h, w, c=img.shape
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r_color=[np.random.randint(255), np.random.randint(255), np.random.randint(255)]
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img=np.where(img==[142, 142, 142], r_color, img).astype(np.uint8)
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if np.random.randint(3):
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k_max=3
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kernel_blur=np.random.randint(k_max)*2+1
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img=cv2.GaussianBlur(img, (kernel_blur, kernel_blur), 0)
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M=cv2.getRotationMatrix2D((int(w/2), int(h/2)), random.randint(-10, 10), 1)
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img=cv2.warpAffine(img, M, (w, h))
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if np.random.randint(2):
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a=int(max(w, h)/5)+1
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pts1=np.float32([[0, 0], [w, 0], [0, h], [w, h]])
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pts2=np.float32([[0+random.randint(-a, a), 0+random.randint(-a, a)], [w-random.randint(-a, a), 0+random.randint(-a, a)], [0+random.randint(-a, a), h-random.randint(-a, a)], [w-random.randint(-a, a), h-random.randint(-a, a)]])
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M=cv2.getPerspectiveTransform(pts1,pts2)
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img=cv2.warpPerspective(img, M, (w, h))
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if np.random.randint(2):
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r=random.randint(0, 5)
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h2=int(h*0.9)
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w2=int(w*0.9)
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if r==0:
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img=img[0:w2, 0:h2]
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elif r==1:
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img=img[w-w2:w, 0:h2]
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elif r==2:
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img=img[0:w2, h-h2:h]
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elif r==3:
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img=img[w-w2:w, h-h2:h]
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img=cv2.resize(img, (h, w))
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if np.random.randint(2):
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r=random.randint(1, int(max(w, h)*0.15))
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img=img[r:w-r, r:h-r]
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img=cv2.resize(img, (h, w))
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if not np.random.randint(4):
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t=np.empty((h, w, c) , dtype=np.float32)
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for i in range(h):
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for j in range(w):
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for k in range(c):
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t[i][j][k]=(i/h)
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M=cv2.getRotationMatrix2D((int(w/2), int(h/2)), np.random.randint(4)*90, 1)
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t=cv2.warpAffine(t, M, (w, h))
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img=(cv2.multiply((img/255).astype(np.float32), t)*255).astype(np.uint8)
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img=change_gamma(img, random.uniform(0.6, 1.0), -np.random.randint(50))
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if not np.random.randint(4):
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p=(15+np.random.randint(10))/100
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img=(img*p+50*(1-p)).astype(np.uint8)+np.random.randint(100)
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img=bruit(img)
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return img
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def create_lot_img(image, nbr, nbr_thread=None):
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if nbr_thread is None:
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nbr_thread=multiprocessing.cpu_count()
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lot_original=np.repeat([image], nbr, axis=0)
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with Pool(nbr_thread) as p:
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lot_result=p.map(modif_img, lot_original)
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p.close()
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return lot_result
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