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Alyssonmach

#!pip install visualkeras
import visualkeras
import tensorflow as tf

conv_base = tf.keras.applications.VGG16(input_shape = (128, 128, 3), include_top = False, weights = 'imagenet')

layers_name = list()
for layer in conv_base.layers:
  layers_name.append(layer.name)

Alyssonmach

from PIL import Image
from matplotlib.pyplot as plt
import urllib.request as url 

# baixando os códigos para geração das imagens em braille
path_1 = 'https://raw.githubusercontent.com/code-coffee-ufcg/braillingo-image-generator/main/caractere_generator.py'
path_2 = 'https://raw.githubusercontent.com/code-coffee-ufcg/braillingo-image-generator/main/image_generator.py'
url.urlretrieve(path_1, 'caractere_generator.py')
url.urlretrieve(path_2, 'image_generator.py')

Alyssonmach

import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf

class_names = ['animal', 'fundo', 'contorno']

def display_with_metrics(display_list, iou_list, dice_score_list):
  '''displays a list of images/masks and overlays a list of IOU and Dice Scores'''
  
  metrics_by_id = [(idx, iou, dice_score) for idx, (iou, dice_score) in enumerate(zip(iou_list, dice_score_list)) if iou > 0.0]

Alyssonmach

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ZbK0CUBCI4nI",
   "metadata": {
    "id": "ZbK0CUBCI4nI"
   },
   "source": [
    "<img src=\"https://www.anped.org.br/sites/default/files/images/ufcg-lateral.png\" width=\"780\" height=\"240\" align=\"center\"/>"

Alyssonmach

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

class MergedGeneratorsSerie(Sequence):
    
    def __init__(self, *args):
        self.args = args

    def __len__(self):
        return len(self.args[0])

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