sbugallo

# -*- coding: utf-8 -*-

from keras.layers import Activation
from keras.layers import AveragePooling2D
from keras.layers import BatchNormalization
from keras.layers import Concatenate
from keras.layers import Conv2D
from keras.layers import Input
from keras.layers import Lambda
from keras.layers import MaxPooling2D

sbugallo

# -*- coding: utf-8 -*-

from keras import layers
from keras.layers import Activation
from keras.layers import BatchNormalization
from keras.layers import Conv2D
from keras.layers import MaxPooling2D
from keras.layers import AveragePooling2D
from keras import backend as K

sbugallo

from keras.layers import Conv2D
from keras.layers import Activation
from keras.layers import Add
from keras.layers import BatchNormalization
from keras.layers import ZeroPadding2D
from keras.layers import MaxPooling2D

def identity_block(input_tensor, kernel_size, filters, stage, block, use_bias=True):
    """
    This block is the one with no convolutional layer at its shortcut branch

sbugallo

from keras.layers import Conv2D
from keras.layers import MaxPooling2D


"""
VGG16 model
"""
def build_vgg_graph(input_image, stage5=False):

    """

sbugallo

cmake_minimum_required(VERSION 3.17.0)
project(onnx_test)

set(CMAKE_BUILD_TYPE "Release")
set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
set(CMAKE_MODULE_PATH "${CMAKE_CURRENT_LIST_DIR}/cmake/" ${CMAKE_MODULE_PATH})

set("OpenCV_DIR" "/usr/local/include/opencv4")
find_package(OpenCV REQUIRED)