import argparse import random from autowebcompat import network, utils parser = argparse.ArgumentParser() parser.add_argument('network', type=str, choices=network.SUPPORTED_NETWORKS, help='Select the network to use for training') parser.add_argument('optimizer', type=str, choices=network.SUPPORTED_OPTIMIZERS, help='Select the optimizer to use for training') args = parser.parse_args() labels = utils.read_labels() utils.prepare_images() all_image_names = [i for i in utils.get_images() if i in labels] all_images = sum([[i + '_firefox.png', i + '_chrome.png'] for i in all_image_names], []) image = utils.load_image(all_images[0]) input_shape = image.shape BATCH_SIZE = 32 EPOCHS = 50 def load_pair(fname): f = utils.load_image(fname + '_firefox.png') print(f.shape) c = utils.load_image(fname + '_chrome.png') print(c.shape) return [f, c] images_train = random.sample(all_image_names, int(len(all_image_names) * 0.9)) images_test = [i for i in all_image_names if i not in set(images_train)]
parser.add_argument('file_name', action='store', help='Filename to open and save your labels') parser.add_argument('--verify', dest='verify', default=False, action='store_true', help='To verify and edit previous labels') args = parser.parse_args() labels = utils.read_labels(labels_directory + args.file_name + '.csv') bounding_boxes = utils.read_bounding_boxes(labels_directory + args.file_name + '_bounding_box.json') if args.verify: images_to_show = [i for i in utils.get_images() if i in labels] else: all_labels = utils.read_labels() images_to_show = [i for i in utils.get_images() if i not in labels] images_in_all_labels = [i for i in images_to_show if i in all_labels] images_not_in_all_labels = [ i for i in images_to_show if i not in all_labels ] random.shuffle(images_not_in_all_labels) random.shuffle(images_in_all_labels) images_to_show = images_not_in_all_labels + images_in_all_labels image_index = 0 drawing = False shifting = False changing_shape = False
import random from autowebcompat import network from autowebcompat import utils labels = utils.read_labels() utils.prepare_images() all_images = utils.get_images() image = utils.load_image(all_images[0]) input_shape = image.shape BATCH_SIZE = 32 EPOCHS = 50 def load_pair(fname): f = utils.load_image(fname + '_firefox.png') print(f.shape) c = utils.load_image(fname + '_chrome.png') print(c.shape) return [f, c] images_train = random.sample(all_images, int(len(all_images) * 0.9)) images_test = [i for i in all_images if i not in set(images_train)] def couples_generator(images): for i in images: yield load_pair(i), labels[i]
import random from autowebcompat import network, utils labels = utils.read_labels() utils.prepare_images() all_image_names = utils.get_images() all_images = sum([[i + '_firefox.png', i + '_chrome.png'] for i in all_image_names], []) image = utils.load_image(all_images[0]) input_shape = image.shape BATCH_SIZE = 32 EPOCHS = 50 def load_pair(fname): f = utils.load_image(fname + '_firefox.png') print(f.shape) c = utils.load_image(fname + '_chrome.png') print(c.shape) return [f, c] images_train = random.sample(all_image_names, int(len(all_image_names) * 0.9)) images_test = [i for i in all_image_names if i not in set(images_train)] def couples_generator(images): for i in images: yield load_pair(i), labels[i]