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/')