将 ResNeXt 导入 Keras
Import ResNeXt into Keras
这个问题看起来很难,但我需要知道如何将 ResNeXt 模型导入 Keras Tensor-flow,我试过但没有用
from keras.applications.resnext import ResNeXt50
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
<ipython-input-1-ca380748170a> in <module>
----> 1 from keras.applications.resnext import ResNeXt50
~/opt/anaconda3/lib/python3.8/site-packages/keras/__init__.py in <module>
1 from __future__ import absolute_import
----> 2 from . import backend
3 from . import datasets
4 from . import engine
5 from . import layers
~/opt/anaconda3/lib/python3.8/site-packages/keras/backend/__init__.py in <module>
65 elif _BACKEND == 'tensorflow':
66 sys.stderr.write('Using TensorFlow backend.\n')
---> 67 from .tensorflow_backend import *
68 else:
69 raise ValueError('Unknown backend: ' + str(_BACKEND))
~/opt/anaconda3/lib/python3.8/site-packages/keras/backend/tensorflow_backend.py in <module>
----> 1 import tensorflow as tf
2
3 from tensorflow.python.training import moving_averages
4 from tensorflow.python.ops import tensor_array_ops
5 from tensorflow.python.ops import control_flow_ops
No module named 'keras.applications.resnext'
我一直不明白为什么一些常用的模型架构不是 keras
应用程序的一部分,例如 SE-Net
、ResNeXt
。但是,有一个著名的 keras
模型动物园存储库,您可以从中获取所需内容。 Classification models Zoo - Keras (and TensorFlow Keras)..
正在安装
!pip install git+https://github.com/qubvel/classification_models.git
正在导入
# for keras
from classification_models.keras import Classifiers
# for tensorflow keras
from classification_models.tfkeras import Classifiers
Classifiers.models_names()
['resnet18',
'resnet34',
'resnet50',
'resnet101',
'resnet152',
'seresnet18',
'seresnet34',
'seresnet50',
'seresnet101',
'seresnet152',
'seresnext50',
'seresnext101',
'senet154',
'resnet50v2',
'resnet101v2',
'resnet152v2',
'resnext50',
'resnext101',
'vgg16',
'vgg19',
'densenet121',
'densenet169',
'densenet201',
'inceptionresnetv2',
'inceptionv3',
'xception',
'nasnetlarge',
'nasnetmobile',
'mobilenet',
'mobilenetv2']
如何使用
SeResNeXT, preprocess_input = Classifiers.get('seresnext50')
model = SeResNeXT(include_top = False, input_shape=(224, 224, 3), weights='imagenet')
ResNeXt50, preprocess_input = Classifiers.get('resnext50')
model = ResNeXt50(include_top = False, input_shape=(224, 224, 3), weights='imagenet')
这个问题看起来很难,但我需要知道如何将 ResNeXt 模型导入 Keras Tensor-flow,我试过但没有用
from keras.applications.resnext import ResNeXt50
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
<ipython-input-1-ca380748170a> in <module>
----> 1 from keras.applications.resnext import ResNeXt50
~/opt/anaconda3/lib/python3.8/site-packages/keras/__init__.py in <module>
1 from __future__ import absolute_import
----> 2 from . import backend
3 from . import datasets
4 from . import engine
5 from . import layers
~/opt/anaconda3/lib/python3.8/site-packages/keras/backend/__init__.py in <module>
65 elif _BACKEND == 'tensorflow':
66 sys.stderr.write('Using TensorFlow backend.\n')
---> 67 from .tensorflow_backend import *
68 else:
69 raise ValueError('Unknown backend: ' + str(_BACKEND))
~/opt/anaconda3/lib/python3.8/site-packages/keras/backend/tensorflow_backend.py in <module>
----> 1 import tensorflow as tf
2
3 from tensorflow.python.training import moving_averages
4 from tensorflow.python.ops import tensor_array_ops
5 from tensorflow.python.ops import control_flow_ops
No module named 'keras.applications.resnext'
我一直不明白为什么一些常用的模型架构不是 keras
应用程序的一部分,例如 SE-Net
、ResNeXt
。但是,有一个著名的 keras
模型动物园存储库,您可以从中获取所需内容。 Classification models Zoo - Keras (and TensorFlow Keras)..
正在安装
!pip install git+https://github.com/qubvel/classification_models.git
正在导入
# for keras
from classification_models.keras import Classifiers
# for tensorflow keras
from classification_models.tfkeras import Classifiers
Classifiers.models_names()
['resnet18',
'resnet34',
'resnet50',
'resnet101',
'resnet152',
'seresnet18',
'seresnet34',
'seresnet50',
'seresnet101',
'seresnet152',
'seresnext50',
'seresnext101',
'senet154',
'resnet50v2',
'resnet101v2',
'resnet152v2',
'resnext50',
'resnext101',
'vgg16',
'vgg19',
'densenet121',
'densenet169',
'densenet201',
'inceptionresnetv2',
'inceptionv3',
'xception',
'nasnetlarge',
'nasnetmobile',
'mobilenet',
'mobilenetv2']
如何使用
SeResNeXT, preprocess_input = Classifiers.get('seresnext50')
model = SeResNeXT(include_top = False, input_shape=(224, 224, 3), weights='imagenet')
ResNeXt50, preprocess_input = Classifiers.get('resnext50')
model = ResNeXt50(include_top = False, input_shape=(224, 224, 3), weights='imagenet')