def test_that_internal_imports_are_not_overriden():
# Test that changing the keras module after importing
# Keras does not override keras.preprocessing's keras module
import keras_applications
reload(keras_applications)
assert keras_applications._KERAS_BACKEND is None
import keras
if not hasattr(keras.applications, 'keras_applications'):
return # Old Keras, don't run.
import tensorflow as tf
keras_applications.set_keras_submodules(backend=tf.keras.backend,
engine=tf.keras.engine,
layers=tf.keras.layers,
models=tf.keras.models,
utils=tf.keras.utils)
assert keras.applications.vgg16.backend is keras.backend
# Now test the reverse order
del keras
reload(keras_applications)
assert keras_applications._KERAS_BACKEND is None
keras_applications.set_keras_submodules(backend=tf.keras.backend,
engine=tf.keras.engine,
layers=tf.keras.layers,
models=tf.keras.models,
utils=tf.keras.utils)
import keras
assert keras.applications.vgg16.backend is keras.backend
import sys, os.path
sys.path.append(os.path.join(os.path.dirname(__file__), 'models', 'DenseNet'))
import numpy as np
import keras
from keras import backend as K
try:
import keras_applications
keras_applications.set_keras_submodules(backend=keras.backend,
layers=keras.layers,
models=keras.models,
utils=keras.utils)
except ImportError:
pass
import warnings
from models import cifar_resnet, cifar_pyramidnet, plainnet, wide_residual_network as wrn
import densenet # pylint: disable=import-error
from clr_callback import CyclicLR
from sgdr_callback import SGDR
ARCHITECTURES = [
'simple', 'resnet-32', 'resnet-110', 'resnet-110-fc', 'resnet-110-wfc',
'wrn-28-10', 'densenet-100-12', 'densenet-100-24', 'densenet-bc-190-40',
'pyramidnet-272-200', 'pyramidnet-110-270', 'resnet-50', 'resnet-101',
'resnet-152', 'rn18', 'rn34', 'rn50', 'rn101', 'rn152', 'rn200', 'nasnet-a'
]
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from .. import backend
from .. import engine
from .. import layers
from .. import models
from .. import utils
import keras_applications
keras_applications.set_keras_submodules(backend=backend,
layers=layers,
models=models,
utils=utils)
from .vgg16 import VGG16
from .vgg19 import VGG19
from .resnet50 import ResNet50
from .inception_v3 import InceptionV3
from .inception_resnet_v2 import InceptionResNetV2
from .xception import Xception
from .mobilenet import MobileNet
from .mobilenetv2 import MobileNetV2
from .densenet import DenseNet121, DenseNet169, DenseNet201
from .nasnet import NASNetMobile, NASNetLarge
import cv2
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
import matplotlib.patches as mpatches
import constants
import time
import keras
from keras_applications import set_keras_submodules
set_keras_submodules(
backend=keras.backend,
layers=keras.layers,
models=keras.models,
engine=keras.engine,
utils=keras.utils,
)
BACKBONE_NAME = "resnext101"
CHECKPOINT_PATH = "data/{}-fpn-modanet.hdf5".format(BACKBONE_NAME)
def invert_image_preprocessing(x):
x_ = np.zeros(x.shape)
x_[:,:,:] = x
x_[...,0] *= 0.229
x_[...,1] *= 0.224
x_[...,2] *= 0.225
x_[...,0] += 0.485
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from .. import backend
from .. import engine
from .. import layers
from .. import models
from .. import utils
import keras_applications
keras_applications.set_keras_submodules(
backend=backend,
layers=layers,
models=models,
utils=utils)
from .vgg16 import VGG16
from .vgg19 import VGG19
from .resnet50 import ResNet50
from .inception_v3 import InceptionV3
from .inception_resnet_v2 import InceptionResNetV2
from .xception import Xception
from .mobilenet import MobileNet
from .mobilenetv2 import MobileNetV2
from .densenet import DenseNet121, DenseNet169, DenseNet201
from .nasnet import NASNetMobile, NASNetLarge
import tensorflow as tf
import keras_applications
from tensorflow.python.keras import engine as keras_engine
keras_applications.set_keras_submodules(backend=tf.keras.backend,
layers=tf.keras.layers,
models=tf.keras.models,
utils=tf.keras.utils,
engine=keras_engine)
found at [mobilenet_v2_keras]
(https://github.com/JonathanCMitchell/mobilenet_v2_keras)
"""
from __future__ import print_function
from __future__ import absolute_import
from __future__ import division
import os
import warnings
import numpy as np
import keras
from keras_applications import get_keras_submodule, set_keras_submodules
set_keras_submodules(backend="tensorflow")
backend = get_keras_submodule('backend')
# engine = get_keras_submodule('engine')
layers = get_keras_submodule('layers')
models = get_keras_submodule('models')
keras_utils = get_keras_submodule('utils')
from keras_applications import imagenet_utils
from keras_applications.imagenet_utils import decode_predictions
from keras_applications.imagenet_utils import _obtain_input_shape
# TODO Change path to v1.1
BASE_WEIGHT_PATH = ('https://github.com/JonathanCMitchell/mobilenet_v2_keras/'
'releases/download/v1.1/')
