def export(sess, input_pl, output_tensor, input_file_pattern, output_dir):
"""Exports inference outputs to an output directory.
Args:
sess: tf.Session with variables already loaded.
input_pl: tf.Placeholder for input (HWC format).
output_tensor: Tensor for generated outut images.
input_file_pattern: Glob file pattern for input images.
output_dir: Output directory.
"""
if output_dir:
_make_dir_if_not_exists(output_dir)
if input_file_pattern:
for file_path in tf.gfile.Glob(input_file_pattern):
# Grab a single image and run it through inference
input_np = np.asarray(PIL.Image.open(file_path))
output_np = sess.run(output_tensor, feed_dict={input_pl: input_np})
image_np = data_provider.undo_normalize_image(output_np)
output_path = _file_output_path(output_dir, file_path)
PIL.Image.fromarray(image_np).save(output_path)
def export(sess, input_pl, output_tensor, input_file_pattern, output_dir):
"""Exports inference outputs to an output directory.
Args:
sess: tf.Session with variables already loaded.
input_pl: tf.Placeholder for input (HWC format).
output_tensor: Tensor for generated outut images.
input_file_pattern: Glob file pattern for input images.
output_dir: Output directory.
"""
if output_dir:
_make_dir_if_not_exists(output_dir)
if input_file_pattern:
for file_path in tf.gfile.Glob(input_file_pattern):
# Grab a single image and run it through inference
input_np = np.asarray(PIL.Image.open(file_path))
output_np = sess.run(output_tensor, feed_dict={input_pl: input_np})
image_np = data_provider.undo_normalize_image(output_np)
output_path = _file_output_path(output_dir, file_path)
PIL.Image.fromarray(image_np).save(output_path)
def export(sess, input_pl, output_tensor, input_file_pattern, output_dir):
"""Exports inference outputs to an output directory.
Args:
sess: tf.Session with variables already loaded.
input_pl: tf.Placeholder for input (HWC format).
output_tensor: Tensor for generated outut images.
input_file_pattern: Glob file pattern for input images.
output_dir: Output directory.
"""
#如果output_dir配置了，要判断其是否存在
if output_dir:
_make_dir_if_not_exists(output_dir)
"""
tf.gfile.Glob
tf.gfile.Glob(filename)
查找匹配pattern的文件并以列表的形式返回，filename可以是一个具体的文件名，也可以是包含通配符的正则表达式。
关于gfile的操作可以查看：https://blog.csdn.net/a373595475/article/details/79693430
PIL:是一个python进行图片处理的库，可以参考文档http://effbot.org/imagingbook/
PIL.Image.fromarray
"""
if input_file_pattern:
for file_path in tf.gfile.Glob(input_file_pattern):
# Grab a single image and run it through inference
input_np = np.asarray(PIL.Image.open(file_path))
output_np = sess.run(output_tensor, feed_dict={input_pl: input_np})
image_np = data_provider.undo_normalize_image(output_np)
output_path = _file_output_path(output_dir, file_path)
PIL.Image.fromarray(image_np).save(output_path)
return output_path