The script is designed to download popular public deep learning topologies and prepare models for the Model Optimizer tool.
- Install python3 (version 3.5.2 or higher)
- Install yaml and requests modules with the command
sudo -E pip3 install pyyaml requests-
Run the script with
-hkey to see the help message:./downloader.py -h usage: downloader.py [-h] [-c CONFIG.YML] [--name PAT[,PAT...]] [--list FILE.LST] [--all] [--print_all] [-o DIR] [--cache_dir DIR] [--num_attempts N] optional arguments: -h, --help show this help message and exit -c CONFIG.YML, --config CONFIG.YML path to YML configuration file --name PAT[,PAT...] download only topologies whose names match at least one of the specified patterns --list FILE.LST download only topologies whose names match at least one of the patterns in the specified file --all download all topologies from the configuration file --print_all print all available topologies -o DIR, --output_dir DIR path where to save topologies --cache_dir DIR directory to use as a cache for downloaded files --num_attempts N attempt each download up to N times list_topologies.yml - default configuration file -
Run the script with the default configuration file:
./downloader.py --all
or with a custom configuration file:
./downloader.py --all -c <path_to_configuration_file>
-
Run the script with the
--print_alloption to see the available topologies:./downloader.py --print_all densenet-121 densenet-161 densenet-169 densenet-201 squeezenet1.0 squeezenet1.1 mtcnn-p mtcnn-r mtcnn-o mobilenet-ssd vgg19 vgg16 ssd512 ssd300 inception-resnet-v2 dilation googlenet-v1 googlenet-v2 googlenet-v4 alexnet ssd_mobilenet_v2_coco resnet-50 resnet-101 resnet-152 googlenet-v3 se-inception se-resnet-101 se-resnet-152 se-resnet-50 se-resnext-50 se-resnext-101 Sphereface license-plate-recognition-barrier-0007 mobilenet-v1-1.0-224 mobilenet-v2 faster_rcnn_inception_v2_coco deeplabv3 ctpn ssd_mobilenet_v1_coco faster_rcnn_resnet101_coco mobilenet-v2-1.4-224 age-gender-recognition-retail-0013 age-gender-recognition-retail-0013-fp16 emotions-recognition-retail-0003 emotions-recognition-retail-0003-fp16 face-detection-adas-0001 face-detection-adas-0001-fp16 face-detection-retail-0004 face-detection-retail-0004-fp16 face-person-detection-retail-0002 face-person-detection-retail-0002-fp16 face-reidentification-retail-0095 face-reidentification-retail-0095-fp16 facial-landmarks-35-adas-0002 facial-landmarks-35-adas-0002-fp16 head-pose-estimation-adas-0001 head-pose-estimation-adas-0001-fp16 human-pose-estimation-0001 human-pose-estimation-0001-fp16 landmarks-regression-retail-0009 landmarks-regression-retail-0009-fp16 license-plate-recognition-barrier-0001 license-plate-recognition-barrier-0001-fp16 pedestrian-and-vehicle-detector-adas-0001 pedestrian-and-vehicle-detector-adas-0001-fp16 pedestrian-detection-adas-0002 pedestrian-detection-adas-0002-fp16 person-attributes-recognition-crossroad-0230 person-attributes-recognition-crossroad-0230-fp16 person-detection-action-recognition-0005 person-detection-action-recognition-0005-fp16 person-detection-retail-0002 person-detection-retail-0002-fp16 person-detection-retail-0013 person-detection-retail-0013-fp16 person-reidentification-retail-0031 person-reidentification-retail-0031-fp16 person-reidentification-retail-0076 person-reidentification-retail-0076-fp16 person-reidentification-retail-0079 person-reidentification-retail-0079-fp16 person-vehicle-bike-detection-crossroad-0078 person-vehicle-bike-detection-crossroad-0078-fp16 road-segmentation-adas-0001 road-segmentation-adas-0001-fp16 semantic-segmentation-adas-0001 semantic-segmentation-adas-0001-fp16 single-image-super-resolution-1033 single-image-super-resolution-1033-fp16 text-detection-0002 text-detection-0002-fp16 vehicle-attributes-recognition-barrier-0039 vehicle-attributes-recognition-barrier-0039-fp16 vehicle-detection-adas-0002 vehicle-detection-adas-0002-fp16 vehicle-license-plate-detection-barrier-0106 vehicle-license-plate-detection-barrier-0106-fp16 face-detection-adas-binary-0001 single-image-super-resolution-1032 single-image-super-resolution-1032-fp16 action-recognition-0001-encoder action-recognition-0001-encoder-fp16 instance-segmentation-security-0049 instance-segmentation-security-0049-fp16 vehicle-detection-adas-binary-0001 driver-action-recognition-adas-0002-decoder driver-action-recognition-adas-0002-decoder-fp16 pedestrian-detection-adas-binary-0001 person-detection-action-recognition-teacher-0002 person-detection-action-recognition-teacher-0002-fp16 instance-segmentation-security-0033 instance-segmentation-security-0033-fp16 action-recognition-0001-decoder action-recognition-0001-decoder-fp16 text-recognition-0012 text-recognition-0012-fp16 driver-action-recognition-adas-0002-encoder driver-action-recognition-adas-0002-encoder-fp16 gaze-estimation-adas-0002 gaze-estimation-adas-0002-fp16
-
Download only some topologies (mtcnn-p and all topologies starting with "densenet-" in the following code example):
./downloader.py --name 'mtcnn-p,densenet-*'The argument to
--namemust be a comma-separated list of patterns, which may contain shell-style wildcards. See https://docs.python.org/3/library/fnmatch.html for a full description of the pattern syntax.Alternatively, you can get the list of patterns from a file:
./downloader.py --list my.lst
The specified file must list one pattern per line. Blank lines and comments starting with
#will be ignored. For example:mtcnn-p densenet-* # get all DenseNet variants
Expected free space to download all the topologies with the default configuration file is around 7.5 GB.
Copyright © 2018 Intel Corporation
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.