吴裕雄--天生自然 PYTHON数据分析：糖尿病视网膜病变数据分析(续六)

from albumentations import *
import time

IMG_SIZE = (224,224)

'''Use case from https://www.kaggle.com/alexanderliao/image-augmentation-demo-with-albumentation/'''
def albaugment(aug0, img):
    return aug0(image=img)['image']
idx=8
image1=x_test[idx]

'''1. Rotate or Flip'''
aug1 = OneOf([Rotate(p=0.99, limit=160, border_mode=0,value=0), Flip(p=0.5)],p=1)

'''2. Adjust Brightness or Contrast'''
aug2 = RandomBrightnessContrast(brightness_limit=0.45, contrast_limit=0.45,p=1)
h_min=np.round(IMG_SIZE[1]*0.72).astype(int)
h_max= np.round(IMG_SIZE[1]*0.9).astype(int)
print(h_min,h_max)

'''3. Random Crop and then Resize'''
#w2h_ratio = aspect ratio of cropping
aug3 = RandomSizedCrop((h_min, h_max),IMG_SIZE[1],IMG_SIZE[0], w2h_ratio=IMG_SIZE[0]/IMG_SIZE[1],p=1)

'''4. CutOut Augmentation'''
max_hole_size = int(IMG_SIZE[1]/10)
aug4 = Cutout(p=1,max_h_size=max_hole_size,max_w_size=max_hole_size,num_holes=8 )#default num_holes=8

'''5. SunFlare Augmentation'''
aug5 = RandomSunFlare(src_radius=max_hole_size,num_flare_circles_lower=10,num_flare_circles_upper=20,p=1)

'''6. Ultimate Augmentation -- combine everything'''
final_aug = Compose([aug1,aug2,aug3,aug4,aug5],p=1)

img1 = albaugment(aug1,image1)
img2 = albaugment(aug1,image1)
print('Rotate or Flip')
show_Nimages([image1,img1,img2],scale=2)
# time.sleep(1)

img1 = albaugment(aug2,image1)
img2 = albaugment(aug2,image1)
img3 = albaugment(aug2,image1)
print('Brightness or Contrast')
show_Nimages([img3,img1,img2],scale=2)
# time.sleep(1)

img1 = albaugment(aug3,image1)
img2 = albaugment(aug3,image1)
img3 = albaugment(aug3,image1)
print('Rotate and Resize')
show_Nimages([img3,img1,img2],scale=2)
print(img1.shape,img2.shape)
# time.sleep(1)

img1 = albaugment(aug4,image1)
img2 = albaugment(aug4,image1)
img3 = albaugment(aug4,image1)
print('CutOut')
show_Nimages([img3,img1,img2],scale=2)
# time.sleep(1)

img1 = albaugment(aug5,image1)
img2 = albaugment(aug5,image1)
img3 = albaugment(aug5,image1)
print('Sun Flare')
show_Nimages([img3,img1,img2],scale=2)
# time.sleep(1)

img1 = albaugment(final_aug,image1)
img2 = albaugment(final_aug,image1)
img3 = albaugment(final_aug,image1)
print('All above combined')
show_Nimages([img3,img1,img2],scale=2)
print(img1.shape,img2.shape)

aug_list = [aug5, aug2, aug3, aug4, aug1, final_aug]
aug_name = ['SunFlare', 'brightness or contrast', 'crop and resized', 'CutOut', 'rotate or flip', 'Everything Combined']

idx=8
layer_name = 'relu' 
for i in range(len(aug_list)):
    path=f"F:\kaggleDataSet\diabeticRetinopathy\resized test 19\"+str(row["id_code"])+".jpg"
    input_img = np.empty((1,224, 224, 3), dtype=np.uint8)
    input_img[0,:,:,:] = preprocess_image(path)
    aug_img = albaugment(aug_list[i],input_img[0,:,:,:])
    ben_img = transform_image_ben(aug_img)
    print('test pic no.%d -- augmentation: %s' % (i+1, aug_name[i]))
    _ = gen_heatmap_img(aug_img,model, layer_name=layer_name,viz_img=ben_img,orig_img=input_img[0])