inference-engine/ie_bridges/python/sample/benchmark_app/benchmark/utils/benchmark_utils.py

   1 """
   2  Copyright (C) 2018-2019 Intel Corporation
   3
   4  Licensed under the Apache License, Version 2.0 (the "License");
   5  you may not use this file except in compliance with the License.
   6  You may obtain a copy of the License at
   7
   8       http://www.apache.org/licenses/LICENSE-2.0
   9
  10  Unless required by applicable law or agreed to in writing, software
  11  distributed under the License is distributed on an "AS IS" BASIS,
  12  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  13  See the License for the specific language governing permissions and
  14  limitations under the License.
  15 """
  16
  17 import logging
  18 import argparse
  19 import os
  20 import cv2
  21 import numpy as np
  22 import sys
  23
  24 from glob import glob
  25 from random import choice
  26 from datetime import datetime
  27 from fnmatch import fnmatch
  28
  29 from .constants import *
  30
  31 logging.basicConfig(format="[ %(levelname)s ] %(message)s", level=logging.INFO, stream=sys.stdout)
  32 logger = logging.getLogger('BenchmarkApp')
  33
  34
  35 def validate_args(args):
  36     if args.number_iterations is not None and args.number_iterations < 0:
  37         raise Exception("Number of iterations should be positive (invalid -niter option value)")
  38     if args.number_infer_requests < 0:
  39         raise Exception("Number of inference requests should be positive (invalid -nireq option value)")
  40     if not fnmatch(args.path_to_model, XML_EXTENSION_PATTERN):
  41         raise Exception('Path {} is not xml file.')
  42
  43
  44 def parse_args():
  45     parser = argparse.ArgumentParser(add_help=False)
  46     args = parser.add_argument_group('Options')
  47     args.add_argument('-h', '--help', action='help', default=argparse.SUPPRESS, help=HELP_MESSAGES["HELP"])
  48     args.add_argument('-i', '--path_to_images', type=str, required=True, help=HELP_MESSAGES['IMAGE_MESSAGE'])
  49     args.add_argument('-m', '--path_to_model', type=str, required=True, help=HELP_MESSAGES['MODEL_MESSAGE'])
  50     args.add_argument('-c', '--path_to_cldnn_config', type=str, required=False,
  51                       help=HELP_MESSAGES['CUSTOM_GPU_LIBRARY_MESSAGE'])
  52     args.add_argument('-l', '--path_to_extension', type=str, required=False, default=None,
  53                       help=HELP_MESSAGES['CUSTOM_GPU_LIBRARY_MESSAGE'])
  54     args.add_argument('-api', '--api_type', type=str, required=False, default='async', choices=['sync', 'async'],
  55                       help=HELP_MESSAGES['API_MESSAGE'])
  56     args.add_argument('-d', '--target_device', type=str, required=False, default="CPU",
  57                       help=HELP_MESSAGES['TARGET_DEVICE_MESSAGE'])
  58     args.add_argument('-niter', '--number_iterations', type=int, required=False, default=None,
  59                       help=HELP_MESSAGES['ITERATIONS_COUNT_MESSAGE'])
  60     args.add_argument('-nireq', '--number_infer_requests', type=int, required=False, default=2,
  61                       help=HELP_MESSAGES['INFER_REQUESTS_COUNT_MESSAGE'])
  62     args.add_argument('-nthreads', '--number_threads', type=int, required=False, default=None,
  63                       help=HELP_MESSAGES['INFER_NUM_THREADS_MESSAGE'])
  64     args.add_argument('-b', '--batch_size', type=int, required=False, default=None,
  65                       help=HELP_MESSAGES['BATCH_SIZE_MESSAGE'])
  66     args.add_argument('-pin', '--infer_threads_pinning', type=str, required=False, default='YES',
  67                       choices=['YES', 'NO'], help=HELP_MESSAGES['INFER_THREADS_PINNING_MESSAGE'])
  68     return parser.parse_args()
  69
  70
  71 def get_images(path_to_images, batch_size):
  72     images = list()
  73     if os.path.isfile(path_to_images):
  74         while len(images) != batch_size:
  75             images.append(path_to_images)
  76     else:
  77         path = os.path.join(path_to_images, '*')
  78         files = glob(path, recursive=True)
  79         for file in files:
  80             file_extension = file.rsplit('.').pop().upper()
  81             if file_extension in IMAGE_EXTENSIONS:
  82                 images.append(file)
  83         if len(images) == 0:
  84             raise Exception("No images found in {}".format(path_to_images))
  85         if len(images) < batch_size:
  86             while len(images) != batch_size:
  87                 images.append(choice(images))
  88     return images
  89
  90
  91 def get_duration_in_secs(target_device):
  92     duration = 0
  93     for device in DEVICE_DURATION_IN_SECS:
  94         if device in target_device:
  95             duration = max(duration, DEVICE_DURATION_IN_SECS[device])
  96
  97     if duration == 0:
  98         duration = DEVICE_DURATION_IN_SECS[UNKNOWN_DEVICE_TYPE]
  99         logger.warn("Default duration {} seconds for unknown device {} is used".format(duration, target_device))
 100
 101     return duration
 102
 103
 104 def fill_blob_with_image(images_path, shape):
 105     images = np.ndarray(shape)
 106     for item in range(shape[0]):
 107         image = cv2.imread(images_path[item])
 108
 109         new_im_size = tuple(shape[2:])
 110         if image.shape[:-1] != new_im_size:
 111             logger.warn("Image {} is resize from ({}) to ({})".format(images_path[item], image.shape[:-1], new_im_size))
 112             image = cv2.resize(image, new_im_size)
 113
 114         image = image.transpose((2, 0, 1))
 115         images[item] = image
 116     return images
 117
 118
 119 def sync_infer_request(exe_network, times, images):
 120     iteration_start_time = datetime.now()
 121     exe_network.infer(images)
 122     current_time = datetime.now()
 123     times.append((current_time - iteration_start_time).total_seconds())
 124     return current_time