tonyreina

import cv2
import numpy as np
from scipy import ndimage 

""" Erosion with OpenCV """

def Erosion_Opencv(img, kernel):
        cv2.imshow("Input Image", img)
        cv2.waitKey(0) 
        erosion = cv2.erode(img,kernel,iterations = 1)

tonyreina

from tensorflow.keras.utils import Sequence
import numpy as np

class DatasetGenerator(Sequence):
    """
    TensorFlow Dataset from Python/NumPy Iterator
    """
    
    def __init__(self, filenames, batch_size=8, crop_dim=[240,240], augment=False, seed=816):
        

tonyreina

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tonyreina

# !/usr/bin/env python

import tensorflow as tf
from tensorflow.python.framework.convert_to_constants import convert_variables_to_constants_v2_as_graph
from tensorflow.lite.python.util import run_graph_optimizations, get_grappler_config

from pathlib import Path
import argparse

def frozen_keras_graph(model):

tonyreina

#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright (c) 2020 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0

tonyreina

import argparse
import tensorflow as tf
import os
import sys

os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'

unlikely_output_types = ['Const', 'Assign', 'NoOp', 'Placeholder', 'Assert']

def dump_for_tensorboard(graph_def: tf.GraphDef, logdir: str):

tonyreina

# !/usr/bin/env python
"""
 Copyright (c) 2018 Intel Corporation
​
 Licensed under the Apache License, Version 2.0 (the 'License');
 you may not use this file except in compliance with the License.
 You may obtain a copy of the License at
​
      http://www.apache.org/licenses/LICENSE-2.0
​

tonyreina

import tensorflow as tf
import argparse

parser = argparse.ArgumentParser(
    description="Loads TensorFlow protobuf and converts it to saved model",
    add_help=True, formatter_class=argparse.ArgumentDefaultsHelpFormatter)

parser.add_argument("--filename", required=True,
                    help="the name and path of the HDF5 dataset")
parser.add_argument("--input_layer_name", default="import/shuffled_queue:0",

tonyreina

#!/usr/bin/env python

# python openvino_inference.py -l /opt/intel/openvino/inference_engine/lib/libcpu_extension.so

import sys
import os
from argparse import ArgumentParser
import numpy as np
import logging as log
from timeit import default_timer as timer

tonyreina

import numpy as np
import tensorflow as tf

num_channels = 3

def create_model():
    """
     Generic fully-convolutional (FCN) model
     Model inputs can be defined with size "None" so that they can
      use different shapes each time. This works for FCN models