Caffe Models for DesignWare EV Processors, R-2020.12
This is release R-2020.12 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 and the MetaWare EV Development Toolkit R-2020.12 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
- DAN
- DeepLab,
- ICNet,
- Inception-Resnet-V1
- LeNet
- MobileNet
- MobileNet-SSD
- ResNet50-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.