biggan

1 files changed, 46 insertions, 0 deletions

diff --git a/cli/app/commands/bigbigan/random.py b/cli/app/commands/bigbigan/random.py
new file mode 100644
index 0000000..a1fd65f
--- /dev/null
+++ b/cli/app/commands/bigbigan/random.py
@@ -0,0 +1,46 @@
+import click
+
+from app.utils import click_utils
+from app.settings import app_cfg
+
+from os.path import join
+import time
+import numpy as np
+
+from PIL import Image
+
+def image_to_uint8(x):
+  """Converts [-1, 1] float array to [0, 255] uint8."""
+  x = np.asarray(x)
+  x = (256. / 2.) * (x + 1.)
+  x = np.clip(x, 0, 255)
+  x = x.astype(np.uint8)
+  return x
+
+@click.command('')
+# @click.option('-i', '--input', 'opt_dir_in', required=True, 
+#   help='Path to input image glob directory')
+# @click.option('-r', '--recursive', 'opt_recursive', is_flag=True)
+@click.pass_context
+def cli(ctx):
+  """
+  """
+  import tensorflow as tf
+  import tensorflow_hub as hub
+
+  print("Loading module...")
+  module = hub.Module('https://tfhub.dev/deepmind/bigbigan-resnet50/1')
+  z = tf.random.normal([8, 120])  # latent samples
+  outputs = module(z, signature='generate', as_dict=True)
+
+  with tf.Session() as sess:
+    sess.run(tf.compat.v1.global_variables_initializer())
+    sess.run(tf.compat.v1.tables_initializer())
+    results = sess.run(outputs)
+
+  for sample in results['default']:
+    sample = image_to_uint8(sample)
+    img = Image.fromarray(sample, "RGB")
+    fp_img_out = "{}.png".format(int(time.time() * 1000))
+    img.save(join(app_cfg.DIR_OUTPUTS, fp_img_out))
+