CLASS_NAMES = np.array(['owl','galaxy', 'lightning','wine-bottle','t-shirt','waterfall', 'sword', 'school-bus',
'calculator','sheet-music','airplanes', 'lightbulb', 'skyscraper','mountain-bike','fireworks',
'computer-monitor','bear','grand-piano','kangaroo','laptop',], dtype='<U10')
import matplotlib.pyplot as plt
def show_batch(image_batch, label_batch):
plt.figure(figsize=(25,20))
for n in range(8):
ax = plt.subplot(1,8,n+1)
plt.imshow(image_batch[n])
plt.title(CLASS_NAMES[label_batch[n]==1][0].title())
plt.axis('off')
image_batch, label_batch = next(train_gen)
show_batch(image_batch, label_batch)
TypeError Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_21468/164695082.py in
13 plt.axis('off')
14
---> 15 image_batch, label_batch = next(train_gen)
16 show_batch(image_batch, label_batch)
c:\users\hp\anaconda3\envs\myenv\lib\site-packages\keras_preprocessing\image\iterator.py in next(self, *args, **kwargs)
102
103 def next(self, *args, **kwargs):
--> 104 return self.next(*args, **kwargs)
105
106 def next(self):
c:\users\hp\anaconda3\envs\myenv\lib\site-packages\keras_preprocessing\image\iterator.py in next(self)
114 # The transformation of images is not under thread lock
115 # so it can be done in parallel
--> 116 return self._get_batches_of_transformed_samples(index_array)
117
118 def _get_batches_of_transformed_samples(self, index_array):
c:\users\hp\anaconda3\envs\myenv\lib\site-packages\keras_preprocessing\image\iterator.py in _get_batches_of_transformed_samples(self, index_array)
229 target_size=self.target_size,
230 interpolation=self.interpolation)
--> 231 x = img_to_array(img, data_format=self.data_format)
232 # Pillow images should be closed after load_img,
233 # but not PIL images.
c:\users\hp\anaconda3\envs\myenv\lib\site-packages\keras_preprocessing\image\utils.py in img_to_array(img, data_format, dtype)
307 # or (channel, height, width)
308 # but original PIL image has format (width, height, channel)
--> 309 x = np.asarray(img, dtype=dtype)
310 if len(x.shape) == 3:
311 if data_format == 'channels_first':
c:\users\hp\anaconda3\envs\myenv\lib\site-packages\numpy\core_asarray.py in asarray(a, dtype, order)
81
82 """
---> 83 return array(a, dtype, copy=False, order=order)
84
85
TypeError: array() takes 1 positional argument but 2 were given
ResNet152V2 Model
CLASS_NAMES = np.array(['owl','galaxy', 'lightning','wine-bottle','t-shirt','waterfall', 'sword', 'school-bus',
'calculator','sheet-music','airplanes', 'lightbulb', 'skyscraper','mountain-bike','fireworks',
'computer-monitor','bear','grand-piano','kangaroo','laptop',], dtype='<U10')
import matplotlib.pyplot as plt
def show_batch(image_batch, label_batch):
plt.figure(figsize=(25,20))
for n in range(8):
ax = plt.subplot(1,8,n+1)
plt.imshow(image_batch[n])
plt.title(CLASS_NAMES[label_batch[n]==1][0].title())
plt.axis('off')
image_batch, label_batch = next(train_gen)
show_batch(image_batch, label_batch)
TypeError Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_21468/164695082.py in
13 plt.axis('off')
14
---> 15 image_batch, label_batch = next(train_gen)
16 show_batch(image_batch, label_batch)
c:\users\hp\anaconda3\envs\myenv\lib\site-packages\keras_preprocessing\image\iterator.py in next(self, *args, **kwargs)
102
103 def next(self, *args, **kwargs):
--> 104 return self.next(*args, **kwargs)
105
106 def next(self):
c:\users\hp\anaconda3\envs\myenv\lib\site-packages\keras_preprocessing\image\iterator.py in next(self)
114 # The transformation of images is not under thread lock
115 # so it can be done in parallel
--> 116 return self._get_batches_of_transformed_samples(index_array)
117
118 def _get_batches_of_transformed_samples(self, index_array):
c:\users\hp\anaconda3\envs\myenv\lib\site-packages\keras_preprocessing\image\iterator.py in _get_batches_of_transformed_samples(self, index_array)
229 target_size=self.target_size,
230 interpolation=self.interpolation)
--> 231 x = img_to_array(img, data_format=self.data_format)
232 # Pillow images should be closed after
load_img,233 # but not PIL images.
c:\users\hp\anaconda3\envs\myenv\lib\site-packages\keras_preprocessing\image\utils.py in img_to_array(img, data_format, dtype)
307 # or (channel, height, width)
308 # but original PIL image has format (width, height, channel)
--> 309 x = np.asarray(img, dtype=dtype)
310 if len(x.shape) == 3:
311 if data_format == 'channels_first':
c:\users\hp\anaconda3\envs\myenv\lib\site-packages\numpy\core_asarray.py in asarray(a, dtype, order)
81
82 """
---> 83 return array(a, dtype, copy=False, order=order)
84
85
TypeError: array() takes 1 positional argument but 2 were given
ResNet152V2 Model