MWEV2019.12.RC1
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This is release 2019.12.RC1 of the Synopsys-caffe-models, a set of Caffe Deep Learning Models adapted for use with DesignWare EV6x Processors.
These models must be used together with Synopsys-Caffe v2019.12.RC1 and the MetaWare EV Development Toolkit v2019.12.RC1 from Synopsys.
Supported Models
- alexnet
- DAN
- DeepTesla
- denoiser
- densenet
- deeplab
- facedetect_v1
- facedetect_v2
- faster_rcnn_resnet101
- fcn
- googlenet
- icnet
- inception_resnet_v1
- inception_resnet_v2
- inception_v1
- inception_v2
- inception_v3
- inception_v4
- lenet
- mobilenet
- mobilenet_ssd
- mtcnn_v1
- openpose
- pspnet
- resnet_101
- resnet_152
- resnet_50
- resnet50_ssd
- resnext_101
- resnext_152
- resnext_50
- segnet
- shufflenet_v1
- shufflenet_v2
- srgan
- squeezenet
- srcnn
- ssd
- pspnet
- unet
- vdcr
- vgg16
- yolo_tiny
- yolo_v1
- yolo_v2_coco
- yolo_v2_voc
- yolo_v3 (yolo_v3_tiny included)
Images
- imagenet_mean - mean images for different image sizes
- imagenet_test_images - simple set of test images
- images - different image data sub-sets
Changes vs v2019.09
New models
- fcn
- shufflenet_v1
- shufflenet_v2
- resnext_101
- resnext_152
- resnext_50
Updated models
- deeplabv3- added test images
- DeepTesla- added models and test images
- MobileNet- updated models
Other changes
Helper tools
git_sparse_download.sh(bat) - helps to download only part of models.