def save_snapshots(self, generated_images, snapshot_dir_path, epoch,
batch_index):
image = combine_normalized_images(generated_images)
img_from_normalized_img(image).save(
os.path.join(
snapshot_dir_path, DCGanV3.model_name + '-' + str(epoch) +
"-" + str(batch_index) + ".png"))
def main():
seed = 42
np.random.seed(seed)
current_dir = os.path.dirname(__file__)
sys.path.append(os.path.join(current_dir, '..'))
current_dir = current_dir if current_dir is not '' else '.'
img_dir_path = current_dir + '/data/pokemon/img'
txt_dir_path = current_dir + '/data/pokemon/txt'
model_dir_path = current_dir + '/models'
img_width = 32
img_height = 32
from keras_text_to_image.library.dcgan_v3 import DCGanV3
from keras_text_to_image.library.utility.image_utils import img_from_normalized_img
from keras_text_to_image.library.utility.img_cap_loader import load_normalized_img_and_its_text
image_label_pairs = load_normalized_img_and_its_text(img_dir_path,
txt_dir_path,
img_width=img_width,
img_height=img_height)
shuffle(image_label_pairs)
gan = DCGanV3()
gan.load_model(model_dir_path)
for i in range(10):
image_label_pair = image_label_pairs[i]
normalized_image = image_label_pair[0]
text = image_label_pair[1]
image = img_from_normalized_img(normalized_image)
image.save(current_dir + '/data/outputs/' + DCGanV3.model_name +
'-generated-' + str(i) + '-0.png')
for j in range(3):
generated_image = gan.generate_image_from_text(text)
generated_image.save(current_dir + '/data/outputs/' +
DCGanV3.model_name + '-generated-' + str(i) +
'-' + str(j) + '.png')