Comments (1)
Hi, the DataAugmentation layer generates parameters from scratch and directly augments data. The GenerateAugmentationParameters layer only generates parameters. It can additionally take existing parameters and modify them by adding transformations.
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Related Issues (20)
- train.prototxt for flying chairs HOT 2
- Generating .prototxt files HOT 2
- Check failed: mdb_env_open(mdb_env_, this->layer_param_.data_param().source().c_str(), 0x20000|0x200000, 0664) == 0 (2 vs. 0) mdb_env_open failed HOT 3
- diagonal filler in Flownet_S deploy HOT 2
- How can I test dataset with png format? HOT 8
- Confused about the FlyingThings3d dataset HOT 2
- Mean layer question HOT 1
- Train dataset HOT 2
- Data augmentation parameter HOT 10
- weight distribution for deconv layer HOT 4
- data augmentation horizontal flip HOT 5
- 3D motion vectors HOT 3
- Shadow suppression HOT 1
- how to generate optial flow .flo and .rflo files? HOT 2
- [libprotobuf ERROR C:\ci\libprotobuf_1523040574637\work\src\google\protobuf\text_format.cc:288] Error parsing text-format caffe.NetParameter: 524:15: Message type "caffe.LayerParameter" has no field named "irnn_param" HOT 1
- Can we set this up on Google Colab? HOT 2
- Models from download-model.sh HOT 4
- Dataloader for loading images HOT 2
- High error rate for KITTI 2015 Training dataset HOT 1
- Error parsing text-format caffe.NetParameter. But I can't find scripts folder in /home/user/caffe/build. HOT 1
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