Gluon CV Toolkit v0.2.0

Gluon CV Toolkit v0.2 Release Notes

Note: This release rely on some features of mxnet 1.3.0. You can early access these features by installing nightly build of mxnet.

You can update mxnet with pip:

pip install mxnet --upgrade --pre
# or 
pip install mxnet-cu90 --upgrade --pre

New Features in 0.2

Image Classification

Highlight: Much more accurate pre-trained ResNet models on ImageNet classification

These high accuracy models are updated to Gluon Model Zoo.

• ResNet50 v1b achieves over 77% accuracy, ResNet101 v1b at 78.8%, and ResNet152 v1b over 79%.
• Training with large batchsize, with float16 data type
• Speeding up training with ImageRecordIter interface
• ResNeXt for ImageNet and CIFAR10 classification
• SE-ResNet(v1b) for ImageNet

Object Detection

Highlight: Faster-RCNN model with training/testing scripts

• Faster-RCNN

  • RPN (region proposal network)
  • Region Proposal
  • ROI Align operator

• Train SSD on COCO dataset

Semantic Segmentation

Highlight: PSPNet for Semantic Segmentation

• PSPNet
• ResNetV1b for ImageNet classification and Semantic Segmentation
  • Network dilation is an option

Datasets

Added the following datasets and usage tutorials

• MS COCO
• ADE20k

New Pre-trained Models in GluonCV

• cifar_resnext29_16x64d
• resnet{18|34|50|101}_v1b
• ssd_512_mobilenet1.0_voc
• faster_rcnn_resnet50_v2a_voc
• ssd_300_vgg16_atrous_coco
• ssd_512_vgg16_atrous_coco
• ssd_512_resnet50_v1_coco
• psp_resnet50_ade

Breaking changes

• Rename DilatedResnetV0 to ResNetV1b