1 files changed, 58 insertions, 0 deletions
diff --git a/cli/app/commands/biggan/random.py b/cli/app/commands/biggan/random.py
new file mode 100644
index 0000000..42db0b8
--- /dev/null
+++ b/cli/app/commands/biggan/random.py
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+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):
+  """
+  Generate a random BigGAN image
+  """
+  import tensorflow as tf
+  import tensorflow_hub as hub
+
+  print("Loading module...")
+  module = hub.Module('https://tfhub.dev/deepmind/biggan-128/2')
+  # module = hub.Module('https://tfhub.dev/deepmind/biggan-256/2')
+  # module = hub.Module('https://tfhub.dev/deepmind/biggan-512/2')
+
+  batch_size = 8
+  truncation = 0.5  # scalar truncation value in [0.02, 1.0]
+
+  z = truncation * tf.random.truncated_normal([batch_size, 120])  # noise sample
+
+  y_index = tf.random.uniform([batch_size], maxval=1000, dtype=tf.int32)
+  y = tf.one_hot(y_index, 1000)
+
+  outputs = module(dict(y=y, z=z, truncation=truncation))
+
+  with tf.Session() as sess:
+    sess.run(tf.compat.v1.global_variables_initializer())
+    sess.run(tf.compat.v1.tables_initializer())
+    results = sess.run(outputs)
+
+  print(results)
+
+  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))