MWEV2019.09.RC2

This is release 2019.09-RC2 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 v2019.09-RC2 and the MetaWare EV Development Toolkit v2019.09-RC2 from Synopsys.

Supported Models

• alexnet
• DAN
• DeepTesla
• denoiser
• densenet
• deeplab
• facedetect_v1
• facedetect_v2
• faster_rcnn_resnet101
• 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
• segnet
• 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 v2019.06

New models

• deeplab
• srcnn
• vdcr

Updated models

• denoiser - added test images
• srgan - added models and test images
• mobilnet - added a new new model v1_1.0_224
• resnet 50/101/152 - added optimized models

Other changes

• removed obsolete C headers with test image arrays

Helper tools

git_sparse_download.sh(bat) - helps to download only part of models.

MWEV2019.09

This is release 2019.09 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 v2019.09 and the MetaWare EV Development Toolkit v2019.09 from Synopsys.

Supported Models

• alexnet
• DAN
• DeepTesla
• denoiser
• densenet
• deeplab
• facedetect_v1
• facedetect_v2
• faster_rcnn_resnet101
• 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
• segnet
• 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 v2019.06

New models

• deeplab
• srcnn
• vdcr

Updated models

• denoiser - added test images
• srgan - added models and test images
• mobilnet - added a new new model v1_1.0_224
• resnet 50/101/152 - added optimized models

Other changes

• removed obsolete C headers with test image arrays

Helper tools

git_sparse_download.sh(bat) - helps to download only part of models.

MWEV2019.09.RC1

This is release 2019.09-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 v2019.09-RC1 and the MetaWare EV Development Toolkit v2019.09-RC1 from Synopsys.

Supported Models

• alexnet
• DAN
• DeepTesla
• denoiser
• densenet
• facedetect_v1
• facedetect_v2
• faster_rcnn_resnet101
• 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
• segnet
• srgan
• squeezenet
• ssd
• pspnet
• unet
• 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 v2019.06

Updated models

• denoiser - added test images
• srgan - added models and test images
• mobilnet - added a new new model v1_1.0_224
• resnet 50/101/152 - added optimized models

Other changes

• removed obsolete C headers with test image arrays

Helper tools

git_sparse_download.sh(bat) - helps to download only part of models.

MWEV2019.06.1

This is release 2019.06-1 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 v2019.06 and the MetaWare EV Development Toolkit v2019.06-1 from Synopsys.

Supported Models

• alexnet
• DAN
• DeepTesla
• denoiser
• densenet
• facedetect_v1
• facedetect_v2
• faster_rcnn_resnet101
• 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_cnn
• resnet_152_cnn
• resnet_50
• resnet50_ssd
• segnet
• srgan
• squeezenet
• ssd
• pspnet
• unet
• 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 v2019.06

Updated models

• srgan

Helper tools

git_sparse_download.sh(bat) - helps to download only part of models.

MWEV2019.06

This is release 2019.06 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 v2019.06 and the MetaWare EV Development Toolkit v2019.06 from Synopsys.

Supported Models

• alexnet
• DAN
• DeepTesla
• denoiser
• densenet
• facedetect_v1
• facedetect_v2
• faster_rcnn_resnet101
• 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_cnn
• resnet_152_cnn
• resnet_50
• resnet50_ssd
• segnet
• srgan
• squeezenet
• ssd
• pspnet
• unet
• 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 v2019.03

Updated models

• alexnet
• facedetect_v1
• googlenet
• inception_v1
• inception_v4
• mtcnn_v1

Helper tools

git_sparse_download.sh(bat) - helps to download only part of models.

MWEV_O_2019_06_RC1

This is release 2019.06.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 v2019.06.RC1 and the MetaWare EV Development Toolkit v2019.06.RC1 from Synopsys.

Supported Models

• alexnet
• DAN
• DeepTesla
• denoiser
• densenet
• facedetect_v1
• facedetect_v2
• faster_rcnn_resnet101
• 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_cnn
• resnet_152_cnn
• resnet_50
• resnet50_ssd
• segnet
• srgan
• squeezenet
• ssd
• pspnet
• unet
• 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 v2019.03

Updated models

• googlenet
• inception_v1
• inception_v4
• mtcnn_v1

Helper tools

git_sparse_download.sh(bat) - helps to download only part of models.

MWEV_O_2019_03_RC1

This is release 2019.03.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 v2019.03.RC1 and the MetaWare EV Development Toolkit v2019.03.RC1 from Synopsys.

Supported Models

• alexnet
• DAN
• DeepTesla
• denoiser
• densenet
• 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_cnn
• resnet_152_cnn
• resnet_50
• resnet50_ssd
• segnet
• srgan
• squeezenet
• ssd
• pspnet
• unet
• 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 v2018.12

New models

• DAN
• DeepTesla
• mtcnn_v1
• resnet50_ssd
• srgan

Updated models

• faster_rcnn_resnet101
• gogglenet
• icnet
• inception_resnet_v1
• inception_v3
• mobilenet_ssd. Update images
• openpose
• segnet
• unet
• yolo_v2
• yolo_v3

New image sets

• COCO2017
• VOC2007. Annotation
• detect_test

Helper tools

git_sparse_download.sh(bat) - helps to download only part of models.

MWEV_O_2019_03

This is release 2019.03 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 v2019.03 and the MetaWare EV Development Toolkit v2019.03 from Synopsys.

Supported Models

• alexnet
• DAN
• DeepTesla
• denoiser
• densenet
• 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_cnn
• resnet_152_cnn
• resnet_50
• resnet50_ssd
• segnet
• srgan
• squeezenet
• ssd
• pspnet
• unet
• 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 v2018.12

New models

• DAN
• DeepTesla
• mtcnn_v1
• resnet50_ssd
• srgan

Updated models

• faster_rcnn_resnet101
• gogglenet
• icnet
• inception_resnet_v1
• inception_v3
• mobilenet_ssd. Update images
• openpose
• segnet
• unet
• yolo_v2
• yolo_v3

New image sets

• COCO2017
• VOC2007. Annotation
• detect_test

Helper tools

git_sparse_download.sh(bat) - helps to download only part of models.

MWEV_O_2018_12

This is release 2018.12 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 v2018.12 and the MetaWare EV Development Toolkit v2018.12 from Synopsys.

Supported Models

• alexnet
• denoiser
• densenet
• 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
• openpose
• pspnet
• resnet_101_cnn
• resnet_152_cnn
• resnet_50
• segnet
• SRGAN
• squeezenet
• ssd
• pspnet
• unet
• 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 v2018.09

New models

• fcn
• openpose
• segnet
• SRGAN
• pspnet
• unet
• yolo_v3 (yolo_v3_tiny included)

Improved parts

• improved compressed, pruned and random-pruned models
• new ssd/VGG* models
• added images/COCO2014

Helper tools

git_sparse_download.sh(bat) - helps to download only part of models.

MWEV_O_2018_12_RC2

This is release 2018.12.RC2 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 v2018.12.RC2 and the MetaWare EV Development Toolkit v2018.12.RC2 from Synopsys.

Supported Models

• alexnet
• denoiser
• densenet
• 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
• openpose
• pspnet
• resnet_101_cnn
• resnet_152_cnn
• resnet_50
• segnet
• SRGAN
• squeezenet
• ssd
• pspnet
• unet
• 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 v2018.09

New models

• fcn
• openpose
• segnet
• SRGAN
• pspnet
• unet
• yolo_v3 (yolo_v3_tiny included)

Improved parts

• improved compressed, pruned and random-pruned models
• new ssd/VGG* models
• added images/COCO2014

Helper tools

git_sparse_download.sh(bat) - helps to download only part of models.