[英]how to load multiple images through keras.load_img and data augment each images for CNN model
我想創建一個 CNN model 來對 10 種不同的汽車進行分類。 首先,我下載了一些圖像,現在我想通過數據增強來增加圖像的數量。 由於一次做一張圖像很忙,我為它編寫了一個 for 循環,它顯示了一個錯誤。
TypeError Traceback (most recent call last)
<ipython-input-14-9ced4a120c2d> in <module>
10
11 for i in images:
---> 12 x = img_to_array(images[i])
13 x = x.reshape((1,) + x.shape)
14 j=0
~\anaconda3\envs\DSEnv\lib\site-packages\keras_preprocessing\image\iterator.py in __getitem__(self, idx)
51
52 def __getitem__(self, idx):
---> 53 if idx >= len(self):
54 raise ValueError('Asked to retrieve element {idx}, '
55 'but the Sequence '
TypeError: '>=' not supported between instances of 'tuple' and 'int'
代碼:
images = ImageDataGenerator().flow_from_directory(r'\Users\Mohda\OneDrive\Desktop\ferrari sf90 stradale')
datagen = ImageDataGenerator(
rotation_range=30,
width_shift_range=0.3,
height_shift_range=0.3,
shear_range=0.2,
zoom_range=0.2,
horizontal_flip=True,
vertical_flip=True,
fill_mode='nearest')
for i in images:
x = img_to_array(images[i])
x = x.reshape((1,) + x.shape)
j=0
for batch in datagen.flow(x,batch_size=1,save_to_dir='preview',save_prefix='ferrari sf90 stradale',save_format='jpeg'):
i+=1
if i>20:
break
您不需要遍歷圖像並應用ImageDataGenerator
而是只需在圖像路徑上使用創建的ImageDataGenerator
,它會為您即時執行。 為了獲取圖像,您可以在生成器上調用next()
。
PATH_TO_IMAGES = r'\Users\Mohda\OneDrive\Desktop\ferrari sf90 stradale'
# Specify whatever augmentation methods you want to use here
train_datagen = ImageDataGenerator(
rotation_range=30,
width_shift_range=0.3,
height_shift_range=0.3,
shear_range=0.2,
zoom_range=0.2,
horizontal_flip=True,
vertical_flip=True,
fill_mode='nearest')
train_generator = train_datagen.flow_from_directory(
PATH_TO_IMAGES,
target_size=(150, 150),
batch_size=32,
save_to_dir=/tmp/img-data-gen-outputs
class_mode='binary')
# Use the generator by calling .next()
train_generator.next()
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