how to generate results using trained model?

[youkaichao]

Is there a function where I can pass a sentence and get an image?

[wulinsanity]

wechat Wu129196 ,communication

[yuxiaojian01]

The trained models are saved as 'xxxx.npz' in the folder of "checkpoints". If you use tl.file.load_and_assign_npz() to load the trained model, and restore the trained network net_g_res and net_rnn_res, and run the code: sess.run([net_g_res.outputs, net_rnn_res.outputs], feed_dict={ t_real_caption : sample_sentence, t_z : sample_seed})

img_gen, rnn_out = sess.run([net_g_res.outputs, net_rnn_res.outputs], feed_dict={ t_real_caption : sample_sentence, t_z : sample_seed})

save_images(img_gen, [ni, ni], 'samples/gen_samples/gen.png') you will get the generated image.

I have tried it and it works.

################sample code ############### import tensorflow as tf import tensorlayer as tl from tensorlayer.layers import from tensorlayer.prepro import from tensorlayer.cost import * import numpy as np import scipy from scipy.io import loadmat import time, os, re, nltk

from utils import from model import import model import pickle

ni = int(np.ceil(np.sqrt(batch_size))) save_dir = "checkpoint" with open("_vocab.pickle", 'rb') as f: vocab = pickle.load(f)

t_real_image = tf.placeholder('float32', [batch_size, image_size, image_size, 3], name = 'real_image')

t_real_caption = tf.placeholder(dtype=tf.int64, shape=[batch_size, None], name='real_caption_input')

t_z = tf.placeholder(tf.float32, [batch_size, z_dim], name='z_noise') generator_txt2img = model.generator_txt2img_resnet

net_rnn = rnn_embed(t_real_caption, is_train=False, reuse=False) netg, = generator_txt2img(t_z, net_rnn.outputs, is_train=False, reuse=False, batch_size=batch_size)

sess = tf.Session(config=tf.ConfigProto(allow_soft_placement=True)) tl.layers.initialize_global_variables(sess)

net_rnn_name = os.path.join(save_dir, 'net_rnn.npz') net_cnn_name = os.path.join(save_dir, 'net_cnn.npz') net_g_name = os.path.join(save_dir, 'net_g.npz') net_d_name = os.path.join(save_dir, 'net_d.npz')

net_rnn_res = tl.files.load_and_assign_npz(sess=sess, name=net_rnn_name, network=net_rnn)

net_g_res = tl.files.load_and_assign_npz(sess=sess, name=net_g_name, network=net_g)

sample_size = batch_size sample_seed = np.random.normal(loc=0.0, scale=1.0, size=(sample_size, z_dim)).astype(np.float32)

sample_sentence = ["the flower shown has yellow anther red pistil and bright red petals."] int(sample_size/ni) + \ ["this flower has petals that are yellow, white and purple and has dark lines"] int(sample_size/ni) + \ ["the petals on this flower are white with a yellow center"] int(sample_size/ni) + \ ["this flower has a lot of small round pink petals."] int(sample_size/ni) + \ ["this flower is orange in color, and has petals that are ruffled and rounded."] int(sample_size/ni) + \ ["the flower has yellow petals and the center of it is brown."] int(sample_size/ni) + \ ["this flower has petals that are blue and white."] int(sample_size/ni) +\ ["these white flowers have petals that start off white in color and end in a white towards the tips."] int(sample_size/ni)

for i, sentence in enumerate(sample_sentence): print("seed: %s" % sentence) sentence = preprocess_caption(sentence) sample_sentence[i] = [vocab.word_to_id(word) for word in nltk.tokenize.word_tokenize(sentence)] + [vocab.end_id] # add END_ID

sample_sentence = tl.prepro.pad_sequences(sample_sentence, padding='post')

img_gen, rnn_out = sess.run([net_g_res.outputs, net_rnn_res.outputs], feed_dict={ t_real_caption : sample_sentence, t_z : sample_seed})

save_images(img_gen, [ni, ni], 'samples/gen_samples/gen.png')

[monday342]

Can someone share a trained model? I trained this on my own computer and it is too slow. Even the python stop working after epoch 21.

[akm190]

Hi, I tried generating results using the .npz files. The generated results look drastically different from the ones that are produced when training the model. I have used the .npz file corresponding to the same epoch with which I am comparing the auto-generated result during training. Is there a possibility that the when the model is loaded back, the ordering of loading is not proper?

[Siddanth-pai]

@monday342 do you have a pre-trained model ?

[Naitik1Rajyaguru]

What is batch_size ??