@dmitrygolovkin dmitrygolovkin released this Nov 6, 2018

Assets 2

This is release 2018.09 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 v2018.09 and the MetaWare EV Development Toolkit v2018.09 from Synopsys.

Supported Models

  • alexnet
  • 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
  • resnet_101_cnn
  • resnet_152_cnn
  • resnet_50
  • squeezenet
  • ssd
  • vgg16
  • yolo_tiny
  • yolo_v1
  • yolo_v2_coco
  • yolo_v2_voc

Changes vs v2018.06

New models

  • icnet
  • inception_resnet_v1
  • mobilenet_ssd
  • pvanet

Improved models

  • alexnet
  • squezenet - instead of SqueezeNet_v1.0 SqueezeNet_v1.1
  • denoizer
  • facedetect_v1
  • googlenet_cnn
  • inception_resnet_v2
  • inception_v1
  • inception_v2
  • inception_v3
  • inception_v4
  • mobilenet
  • resnet_101
  • resnet_152
  • resnet_50
  • ssd
  • vgg16
  • yolo_v2_voc

Removed models

  • scene_segmentation

Images

  • imagenet_mean - mean images for different image sizes
  • imagenet_test_images - simple set of test images
  • images - different image data sub-sets

Helper tools

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

@dmitrygolovkin dmitrygolovkin released this Oct 19, 2018

Assets 2

This is release 2018.09.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 v2018.09.RC2 and the MetaWare EV Development Toolkit v2018.09.RC2 from Synopsys.

Supported Models

  • alexnet
  • 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
  • resnet_101_cnn
  • resnet_152_cnn
  • resnet_50
  • squeezenet
  • ssd
  • vgg16
  • yolo_tiny
  • yolo_v1
  • yolo_v2_coco
  • yolo_v2_voc

Changes vs v2018.06

New models

  • icnet
  • inception_resnet_v1
  • mobilenet_ssd
  • pvanet

Improved models

  • alexnet
  • squezenet - instead of SqueezeNet_v1.0 SqueezeNet_v1.1
  • denoizer
  • facedetect_v1
  • googlenet_cnn
  • inception_resnet_v2
  • inception_v1
  • inception_v2
  • inception_v3
  • inception_v4
  • mobilenet
  • resnet_101
  • resnet_152
  • resnet_50
  • ssd
  • vgg16
  • yolo_v2_voc

Removed models

  • scene_segmentation

Images

  • imagenet_mean - mean images for different image sizes
  • imagenet_test_images - simple set of test images
  • images - different image data sub-sets

Helper tools

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

Oct 4, 2018

help

Add pvanet

@dmitrygolovkin dmitrygolovkin released this Oct 4, 2018 · 7 commits to master since this release

Assets 2

This is release 2018.09.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 v2018.09.RC1 and the MetaWare EV Development Toolkit v2018.09.RC1 from Synopsys.

Supported Models

  • alexnet
  • 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
  • resnet_101_cnn
  • resnet_152_cnn
  • resnet_50
  • Squeeze_Netv1.0
  • SqueezeNet_v1.1
  • ssd
  • vgg16
  • yolo_tiny
  • yolo_v1
  • yolo_v2_coco
  • yolo_v2_voc

Changes vs v2018.06

New models

  • icnet
  • inception_resnet_v1
  • mobilenet_ssd
  • pvanet

Improved models

  • alexnet
  • SqueezeNet_v1.0
  • SqueezeNet_v1.1)
  • denoizer
  • facedetect_v1
  • googlenet_cnn
  • inception_resnet_v2
  • inception_v1
  • inception_v2
  • inception_v3
  • inception_v4
  • mobilenet
  • resnet_101
  • resnet_152
  • resnet_50
  • ssd
  • vgg16
  • yolo_v2_voc

Removed models

  • scene_segmentation

Images

  • imagenet_mean - mean images for different image sizes
  • imagenet_test_images - simple set of test images
  • images - different image data sub-sets

@antonbaliasnikov antonbaliasnikov released this Jul 23, 2018 · 28 commits to master since this release

Assets 2

This is release 2018.06 RC3 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 and the MetaWare EV Development Toolkit v2018.06 RC3 from Synopsys.

Supported Models

  • alexnet
  • denoiser
  • densenet
  • facedetect_v1
  • facedetect_v2
  • faster_rcnn_resnet101
  • googlenet
  • imagenet_test_images
  • inception_resnet_v1
  • inception_resnet_v2
  • inception_v3
  • inception_v4
  • lenet
  • mobilenet
  • resnet_101_cnn
  • resnet_152_cnn
  • resnet_50
  • scene_segmentation
  • Squeeze_Net_v1.0
  • SqueezeNet_v1.1
  • ssd
  • vgg16
  • yolo_tiny
  • yolo_v1
  • yolo_v2_coco
  • yolo_v2_voc

New models vs v2018.03

  • faster_rcnn_resnet101
  • inception_resnet_v1
  • inception_resnet_v2
  • resnet_101_cnn
  • resnet_152_cnn

Fixed models vs v2018.03

  • inception_resnet_v2
  • inception_v3
  • inception_v4
  • mobilnet
  • resnet_50

Usage Instructions

IMPORTANT NOTE: This repository uses git-lfs for large file storage. You can't use zip and tar files listed in the "Assets" section above (added by default by github). You must clone the repository using the instructions below

  1. Install git-lfs

  2. Ensure git-lfs and git versions you use are compatible (equal or greater than below)

$ git lfs version
git-lfs/2.0.2 # or newer

$ git –version
git version 2.9.3 # or newer
  1. Add SSH key to your GitHub account (if you haven't already)

  2. clone the repo:

$ git clone https://github.com/foss-for-synopsys-dwc-arc-processors/synopsys-caffe-models.git

@antonbaliasnikov antonbaliasnikov released this Aug 24, 2018 · 29 commits to master since this release

Assets 2

This is release 2018.09-ENG-180824 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 and the MetaWare EV Development Toolkit v2018.06 RC3 from Synopsys.

Supported Models

  • alexnet
  • denoiser
  • densenet
  • facedetect_v1
  • facedetect_v2
  • faster_rcnn_resnet101
  • googlenet
  • imagenet_test_images
  • inception_resnet_v1
  • inception_resnet_v2
  • inception_v3
  • inception_v4
  • lenet
  • mobilenet
  • resnet_101_cnn
  • resnet_152_cnn
  • resnet_50
  • scene_segmentation
  • Squeeze_Net_v1.0
  • SqueezeNet_v1.1
  • ssd
  • vgg16
  • yolo_tiny
  • yolo_v1
  • yolo_v2_coco
  • yolo_v2_voc

New models vs v2018.03

  • faster_rcnn_resnet101
  • inception_resnet_v1
  • inception_resnet_v2
  • resnet_101_cnn
  • resnet_152_cnn

Fixed models vs v2018.03

  • inception_resnet_v2
  • inception_v3
  • inception_v4
  • mobilnet
  • resnet_50

Usage Instructions

IMPORTANT NOTE: This repository uses git-lfs for large file storage. You can't use zip and tar files listed in the "Assets" section above (added by default by github). You must clone the repository using the instructions below

  1. Install git-lfs

  2. Ensure git-lfs and git versions you use are compatible (equal or greater than below)

$ git lfs version
git-lfs/2.0.2 # or newer

$ git –version
git version 2.9.3 # or newer
  1. Add SSH key to your GitHub account (if you haven't already)

  2. clone the repo:

$ git clone https://github.com/foss-for-synopsys-dwc-arc-processors/synopsys-caffe-models.git
Jul 23, 2018
MWEV 2018.06 RC3 tag

@antonbaliasnikov antonbaliasnikov released this Jul 19, 2018 · 31 commits to master since this release

Assets 2

This is release 2018.06 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 and the MetaWare EV Development Toolkit v2018.06 RC2 from Synopsys.

Supported Models

  • alexnet
  • denoiser
  • densenet
  • facedetect_v1
  • facedetect_v2
  • faster_rcnn_resnet101
  • googlenet
  • imagenet_test_images
  • inception_resnet_v1
  • inception_resnet_v2
  • inception_v3
  • inception_v4
  • lenet
  • mobilenet
  • resnet_101_cnn
  • resnet_152_cnn
  • resnet_50
  • scene_segmentation
  • Squeeze_Net_v1.0
  • SqueezeNet_v1.1
  • ssd
  • vgg16
  • yolo_tiny
  • yolo_v1
  • yolo_v2_coco
  • yolo_v2_voc

New models vs v2018.03

  • faster_rcnn_resnet101
  • inception_resnet_v1
  • inception_resnet_v2
  • resnet_101_cnn
  • resnet_152_cnn

Fixed models vs v2018.03

  • inception_resnet_v2
  • inception_v3
  • inception_v4
  • mobilnet
  • resnet_50

Usage Instructions

IMPORTANT NOTE: This repository uses git-lfs for large file storage. You can't use zip and tar files listed in the "Assets" section above (added by default by github). You must clone the repository using the instructions below

  1. Install git-lfs

  2. Ensure git-lfs and git versions you use are compatible (equal or greater than below)

$ git lfs version
git-lfs/2.0.2 # or newer

$ git –version
git version 2.9.3 # or newer
  1. Add SSH key to your GitHub account (if you haven't already)

  2. clone the repo:

$ git clone https://github.com/foss-for-synopsys-dwc-arc-processors/synopsys-caffe-models.git
Assets 2

This is release 2018.06 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 and the MetaWare EV Development Toolkit v2018.06 RC1 from Synopsys.

Supported Models

  • alexnet
  • denoiser
  • densenet
  • facedetect_v1
  • facedetect_v2
  • faster_rcnn_resnet101
  • googlenet
  • imagenet_test_images
  • inception_resnet_v1
  • inception_resnet_v2
  • inception_v3
  • inception_v4
  • lenet
  • mobilenet
  • resnet_101_cnn
  • resnet_152_cnn
  • resnet_50
  • scene_segmentation
  • Squeeze_Net_v1.0
  • SqueezeNet_v1.1
  • ssd
  • vgg16
  • yolo_tiny
  • yolo_v1
  • yolo_v2_coco
  • yolo_v2_voc

New models vs v2018.03

  • faster_rcnn_resnet101
  • inception_resnet_v1
  • inception_resnet_v2
  • resnet_101_cnn
  • resnet_152_cnn

Fixed models vs v2018.03

  • inception_resnet_v2
  • inception_v3
  • inception_v4
  • mobilnet
  • resnet_50

Usage Instructions

IMPORTANT NOTE: This repository uses git-lfs for large file storage. You can't use zip and tar files listed in the "Assets" section above (added by default by github). You must clone the repository using the instructions below

  1. Install git-lfs

  2. Ensure git-lfs and git versions you use are compatible (equal or greater than below)

$ git lfs version
git-lfs/2.0.2 # or newer

$ git –version
git version 2.9.3 # or newer
  1. Add SSH key to your GitHub account (if you haven't already)

  2. clone the repo:

$ git clone https://github.com/foss-for-synopsys-dwc-arc-processors/synopsys-caffe-models.git
Assets 2

This is release 2018.03 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 and the MetaWare EV Development Toolkit v2018.03 from Synopsys.

Supported Models

  • alexnet
  • denoiser
  • densenet
  • facedetect_v1
  • facedetect_v2
  • googlenet
  • imagenet_test_images
  • inception_resnet_v2
  • inception_v3
  • inception_v4
  • lenet
  • mobilenet
  • resnet_50
  • scene_segmentation
  • Squeeze_Net_v1.0
  • SqueezeNet_v1.1
  • ssd
  • vgg16
  • yolo_tiny
  • yolo_v1
  • yolo_v2_coco
  • yolo_v2_voc

New models vs v2017.12

  • densenet
  • inception_resnet_v2
  • inception_v3
  • inception_v4
  • mobilenet
  • ssd

Usage Instructions

IMPORTANT NOTE: This repository uses git-lfs for large file storage. You can't use zip and tar files listed in the "Assets" section above (added by default by github). You must clone the repository using the instructions below

  1. Install git-lfs

  2. Ensure git-lfs and git versions you use are compatible (equal or greater than below)

$ git lfs version
git-lfs/2.0.2 # or newer

$ git –version
git version 2.9.3 # or newer
  1. Add SSH key to your GitHub account (if you haven't already)

  2. clone the repo:

$ git clone https://github.com/foss-for-synopsys-dwc-arc-processors/synopsys-caffe-models.git