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Caffe Models for DesignWare EV Processors, v2017.12

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@ebensou ebensou released this 12 Feb 22:36
· 142 commits to master since this release
MWEV2017.12
697f76d

This is release 2017.12 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 and the MetaWare EV Development Toolkit v2017.12, from Synopsys.

Supported Models

  • alexnet
  • denoiser
  • facedetect_v1
  • facedetect_v2
  • googlenet
  • lenet
  • resnet_50
  • scene_segmentation
  • Squeeze_Net_v1.0
  • SqueezeNet_v1.1
  • vgg16
  • yolo_tiny
  • yolo_v1
  • yolo_v2_coco
  • yolo_v2_voc

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

$ git –version
git version 2.9.3

  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
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