Publishing 2019 R1 content

[platform/upstream/dldt.git] / inference-engine / ie_bridges / python / sample / style_transfer_sample / style_transfer_sample.py

diff --git a/inference-engine/ie_bridges/python/sample/style_transfer_sample.py b/inference-engine/ie_bridges/python/sample/style_transfer_sample/style_transfer_sample.py
similarity index 68%
rename from inference-engine/ie_bridges/python/sample/style_transfer_sample.py
rename to inference-engine/ie_bridges/python/sample/style_transfer_sample/style_transfer_sample.py
index 76fcada..fc08b17 100644 (file)
--- a/inference-engine/ie_bridges/python/sample/style_transfer_sample.py
+++ b/inference-engine/ie_bridges/python/sample/style_transfer_sample/style_transfer_sample.py
@@ -1,6 +1,6 @@
 #!/usr/bin/env python
 """
- Copyright (c) 2018 Intel Corporation
+ Copyright (C) 2018-2019 Intel Corporation
 
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
@@ -17,7 +17,7 @@
 from __future__ import print_function
 import sys
 import os
-from argparse import ArgumentParser
+from argparse import ArgumentParser, SUPPRESS
 import cv2
 import numpy as np
 import logging as log
@@ -26,30 +26,33 @@ from openvino.inference_engine import IENetwork, IEPlugin
 
 
 def build_argparser():
-    parser = ArgumentParser()
-    parser.add_argument("-m", "--model", help="Path to an .xml file with a trained model.", required=True, type=str)
-    parser.add_argument("-i", "--input", help="Path to a folder with images or path to an image files", required=True,
-                        type=str, nargs="+")
-    parser.add_argument("-l", "--cpu_extension",
-                        help="MKLDNN (CPU)-targeted custom layers.Absolute path to a shared library with the kernels "
-                             "impl.", type=str, default=None)
-    parser.add_argument("-pp", "--plugin_dir", help="Path to a plugin folder", type=str, default=None)
-    parser.add_argument("-d", "--device",
-                        help="Specify the target device to infer on; CPU, GPU, FPGA or MYRIAD is acceptable. Sample "
-                             "will look for a suitable plugin for device specified (CPU by default)", default="CPU",
-                        type=str)
-    parser.add_argument("-nt", "--number_top", help="Number of top results", default=10, type=int)
-    parser.add_argument("-ni", "--number_iter", help="Number of inference iterations", default=1, type=int)
-    parser.add_argument("--mean_val_r", "-mean_val_r",
-                        help="Mean value of red chanel for mean value subtraction in postprocessing ", default=0,
-                        type=float)
-    parser.add_argument("--mean_val_g", "-mean_val_g",
-                        help="Mean value of green chanel for mean value subtraction in postprocessing ", default=0,
-                        type=float)
-    parser.add_argument("--mean_val_b", "-mean_val_b",
-                        help="Mean value of blue chanel for mean value subtraction in postprocessing ", default=0,
-                        type=float)
-    parser.add_argument("-pc", "--perf_counts", help="Report performance counters", default=False, action="store_true")
+    parser = ArgumentParser(add_help=False)
+    args = parser.add_argument_group('Options')
+    args.add_argument('-h', '--help', action='help', default=SUPPRESS, help='Show this help message and exit.')
+    args.add_argument("-m", "--model", help="Path to an .xml file with a trained model.", required=True, type=str)
+    args.add_argument("-i", "--input", help="Path to a folder with images or path to an image files", required=True,
+                      type=str, nargs="+")
+    args.add_argument("-l", "--cpu_extension",
+                      help="Optional. Required for CPU custom layers. "
+                           "Absolute MKLDNN (CPU)-targeted custom layers. Absolute path to a shared library with the "
+                           "kernels implementations", type=str, default=None)
+    args.add_argument("-pp", "--plugin_dir", help="Path to a plugin folder", type=str, default=None)
+    args.add_argument("-d", "--device",
+                      help="Specify the target device to infer on; CPU, GPU, FPGA, HDDL or MYRIAD is acceptable. Sample "
+                           "will look for a suitable plugin for device specified. Default value is CPU", default="CPU",
+                      type=str)
+    args.add_argument("-nt", "--number_top", help="Number of top results", default=10, type=int)
+    args.add_argument("-ni", "--number_iter", help="Number of inference iterations", default=1, type=int)
+    args.add_argument("--mean_val_r", "-mean_val_r",
+                      help="Mean value of red chanel for mean value subtraction in postprocessing ", default=0,
+                      type=float)
+    args.add_argument("--mean_val_g", "-mean_val_g",
+                      help="Mean value of green chanel for mean value subtraction in postprocessing ", default=0,
+                      type=float)
+    args.add_argument("--mean_val_b", "-mean_val_b",
+                      help="Mean value of blue chanel for mean value subtraction in postprocessing ", default=0,
+                      type=float)
+    args.add_argument("-pc", "--perf_counts", help="Report performance counters", default=False, action="store_true")
 
     return parser
 
@@ -101,7 +104,6 @@ def main():
     # Loading model to the plugin
     log.info("Loading model to the plugin")
     exec_net = plugin.load(network=net)
-    del net
 
     # Start sync inference
     log.info("Starting inference ({} iterations)".format(args.number_iter))
@@ -133,8 +135,6 @@ def main():
         out_img = os.path.join(os.path.dirname(__file__), "out_{}.bmp".format(batch))
         cv2.imwrite(out_img, data)
         log.info("Result image was saved to {}".format(out_img))
-    del exec_net
-    del plugin
 
 
 if __name__ == '__main__':