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] [--name NAME] [--print_all] [-o OUTPUT_DIR] optional arguments: -h, --help show this help message and exit -c CONFIG, --config CONFIG path to YML configuration file --name NAME name of topology for downloading --print_all print all available topologies -o OUTPUT_DIR, --output_dir OUTPUT_DIR path where to save topologies list_topologies.yml - default configuration file -
Run the script with the default configuration file:
./downloader.py
or with a custom configuration file:
./downloader.py -c <path_to_configuration_file>
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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 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-0001 face-reidentification-retail-0001-fp16 head-pose-estimation-adas-0001 head-pose-estimation-adas-0001-fp16 landmarks-regression-retail-0001 landmarks-regression-retail-0001-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-0031 person-attributes-recognition-crossroad-0031-fp16 person-detection-action-recognition-0001 person-detection-action-recognition-0001-fp16 person-detection-retail-0001 person-detection-retail-0001-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 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
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Download only one topology (mtcnn-p in the following code example):
./downloader.py --name mtcnn-p
Expected free space to download all the topologies with the default configuration file is around 3.5 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.