Skip to content

@dmitrygolovkin dmitrygolovkin released this Jan 21, 2021

This is release R-2020.12-RC2 of the Synopsys-caffe-models, a set of Caffe Deep Learning Models adapted for use with DesignWare EV Processors.

These models must be used together with Synopsys-Caffe R-2020.12-RC2 and the MetaWare EV Development Toolkit R-2020.12-RC2 from Synopsys.

Supported Models

Alexnet, DAN, Denoiser, Densenet, Deeplab, Facedetect v1/v2, FaceNet, Faster_rcnn_resnet101, FCN, Googlenet. ICNet,
Inception_Resnet v1/v2, Inception v1/v2/v3/v4, LeNet, Mobilenet, Mobilenet_ssd, mtcnn v1, OpenPose, PSPNet,
Resnet 50/101/152, Resnet50_ssd, ResNext 50/101/152, RetinaNet, SegNet, ShuffleNet v1/v2, SRGAN, SqueezeNet, SRCNN, SSD,
PSPNet, UNet, VDCR, VGG16, Yolo v1/v1_tiny/v2_coco/v2_voc/v3/v3_tiny

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 2020.09

Updated models

  • DeepLab,
  • ICNet,
  • Inception-Resnet-V1
  • MobileNet
  • MobileNet-SSD
  • RetinaNet
  • SEGNet
  • SSD
  • Yolo-V3

Other changes

Add Yolo-V3 annotation test_images

Helper tools

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

Assets 2

@dmitrygolovkin dmitrygolovkin released this Dec 21, 2020 · 5 commits to master since this release

This is release R-2020.12-RC1 of the Synopsys-caffe-models, a set of Caffe Deep Learning Models adapted for use with DesignWare EV Processors.

These models must be used together with Synopsys-Caffe R-2020.12-RC1 and the MetaWare EV Development Toolkit R-2020.12-RC1 from Synopsys.

Supported Models

Alexnet, DAN, Denoiser, Densenet, Deeplab, Facedetect v1/v2, FaceNet, Faster_rcnn_resnet101, FCN, Googlenet. ICNet,
Inception_Resnet v1/v2, Inception v1/v2/v3/v4, LeNet, Mobilenet, Mobilenet_ssd, mtcnn v1, OpenPose, PSPNet,
Resnet 50/101/152, Resnet50_ssd, ResNext 50/101/152, RetinaNet, SegNet, ShuffleNet v1/v2, SRGAN, SqueezeNet, SRCNN, SSD,
PSPNet, UNet, VDCR, VGG16, Yolo v1/v1_tiny/v2_coco/v2_voc/v3/v3_tiny

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 2020.09

Updated models

  • DeepLab,
  • ICNet,
  • MobileNet
  • RetinaNet
  • SEGNet
  • Yolo-V3

Other changes

None

Helper tools

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

Assets 2

@dmitrygolovkin dmitrygolovkin released this Nov 5, 2020 · 6 commits to master since this release

This is release R-2020.09 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 R-2020.09 and the MetaWare EV Development Toolkit R-2020.09 from Synopsys.

Supported Models

Alexnet, DAN, Denoiser, Densenet, Deeplab, Facedetect v1/v2, FaceNet, Faster_rcnn_resnet101, FCN, Googlenet. ICNet,
Inception_Resnet v1/v2, Inception v1/v2/v3/v4, LeNet, Mobilenet, Mobilenet_ssd, mtcnn v1, OpenPose, PSPNet,
Resnet 50/101/152, Resnet50_ssd, ResNext 50/101/152, RetinaNet, SegNet, ShuffleNet v1/v2, SRGAN, SqueezeNet, SRCNN, SSD,
PSPNet, UNet, VDCR, VGG16, Yolo v1/v1_tiny/v2_coco/v2_voc/v3/v3_tiny

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 2020.06

New models

  • FaceNet

Updated models

  • SRGAN- added new prototxt for Dynamic input

Other changes

None

Helper tools

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

Assets 2

@dmitrygolovkin dmitrygolovkin released this Sep 21, 2020 · 6 commits to master since this release

This is release R-2020.09-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 R-2020.09-RC1 and the MetaWare EV Development Toolkit R-2020.09-RC1 from Synopsys.

Supported Models

Alexnet, DAN, Denoiser, Densenet, Deeplab, Facedetect v1/v2, FaceNet, Faster_rcnn_resnet101, FCN, Googlenet. ICNet,
Inception_Resnet v1/v2, Inception v1/v2/v3/v4, LeNet, Mobilenet, Mobilenet_ssd, mtcnn v1, OpenPose, PSPNet,
Resnet 50/101/152, Resnet50_ssd, ResNext 50/101/152, RetinaNet, SegNet, ShuffleNet v1/v2, SRGAN, SqueezeNet, SRCNN, SSD,
PSPNet, UNet, VDCR, VGG16, Yolo v1/v1_tiny/v2_coco/v2_voc/v3/v3_tiny

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 2020.06

New models

  • FaceNet

Updated models

  • SRGAN- added new prototxt for Dynamic input

Other changes

None

Helper tools

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

Assets 2

@dmitrygolovkin dmitrygolovkin released this Jul 24, 2020 · 8 commits to master since this release

This is release 2020.06 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 v2020.06 and the MetaWare EV Development Toolkit v2020.06 from Synopsys.

Supported Models

  • alexnet
  • DAN
  • 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
  • retinanet
  • 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 v2020.03

New models

  • retinanet

Updated models

  • fcn- added FCN-ResNet18
  • Inception V1 - added one new updated prototxt
  • mobilenet_v3. Update pb_converted
  • openpose. Add pose_deploy
  • ResNet-152. Update models

Other changes

None

Helper tools

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

Assets 2

@dmitrygolovkin dmitrygolovkin released this Jun 23, 2020 · 11 commits to master since this release

This is release 2020.06.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 v2020.06.RC1 and the MetaWare EV Development Toolkit v2020.06.RC1 from Synopsys.

Supported Models

  • alexnet
  • DAN
  • 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
  • retinanet
  • 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 v2020.03

New models

  • retinanet

Updated models

  • fcn- added FCN-ResNet18
  • Inception V1 - added one new updated prototxt
  • mobilenet_v3. Update pb_converted
  • openpose. Add pose_deploy
  • ResNet-152. Update models

Other changes

None

Helper tools

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

Assets 2

@dmitrygolovkin dmitrygolovkin released this Apr 16, 2020 · 18 commits to master since this release

This is release 2020.03 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 v2020.03 and the MetaWare EV Development Toolkit v2020.03 from Synopsys.

Supported Models

  • alexnet
  • DAN
  • 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 v2019.12

New models

Updated models

  • fcn- added new models
  • Inception V1 - added one new updated prototxt
  • mobilenet - added V3 models
  • resnet_152 - added one new model
  • resnet_50 - added 1920x1080 model

Other changes

  • images - added new dummy images

Helper tools

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

Assets 2

@dmitrygolovkin dmitrygolovkin released this Mar 19, 2020 · 18 commits to master since this release

This is release 2020.03.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 v2020.03.RC1 and the MetaWare EV Development Toolkit v2020.03.RC1 from Synopsys.

Supported Models

  • alexnet
  • DAN
  • 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 v2019.12

New models

Updated models

  • fcn- added new models
  • Inception V1 - added one new updated prototxt
  • resnet_152 - add one new model

Other changes

  • images - added new dummy images

Helper tools

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

Assets 2

@dmitrygolovkin dmitrygolovkin released this Feb 17, 2020 · 18 commits to master since this release

This is release 2019.12 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 v2019.12 and the MetaWare EV Development Toolkit v2019.12 from Synopsys.

Supported Models

  • alexnet
  • DAN
  • 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
  • MobileNet- updated models

Other changes

Helper tools

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

Assets 2

@dmitrygolovkin dmitrygolovkin released this Jan 21, 2020 · 18 commits to master since this release

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.

Assets 2