# caffe_plus

**Repository Path**: phillip_huang/caffe_plus

## Basic Information

- **Project Name**: caffe_plus
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-11-26
- **Last Updated**: 2024-11-30

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Update
- 2020-03-29 Add `caffemodel2txt.cpp` 
- 2020-03-28 Add some new layers, `permute`( from[ssd](https://github.com/weiliu89/caffe/tree/ssd)) and `Upsample`(`nearest` and `bilinear`,only forward) based on origin [caffe](https://github.com/BVLC/caffe). Source is:
```
include/caffe/layers/permute_layer.hpp
src/caffe/layers/permute_layer.cpp
src/caffe/layers/permute_layer.cu
include/caffe/layers/upsample_layer.hpp
src/caffe/layers/upsample_layer.cpp
src/caffe/layers/upsample_layer.cu
```
# Example

## `Caffemodle2txt layer`

- Convert a caffemodel to txt or txt to caffemodel

```shell
Usage:
	./build/tools/caffemodel2txt c2t[t2c] caffemodel_path[txt_path] txt_path[caffemodel_path]
```

## `Upsample layer`

- Upsample shape of bottom[0] to shape of bottom[1]

```
layer{
    name:"Upsample_nearest"
    type:"Upsample"
    bottom:"Conv2d_87" #Blob Conv2d_87's shape is [1,16,32,32]
    bottom:"Conv2d_84" #Blob Conv2d_84's shape is [1,16,48,48]
    top:"Upsample_nearest" #Blob Upsample_nearest's shape is [1,16,48,48]
    upsample_param{
	    mode: NEAREST # or BILINEAR
    }
}
```

- Upsample shape of bottom to `HEIGHT` and `WIDTH`

```
layer{
    name:"Upsample_nearest"
    type:"Upsample"
    bottom:"Conv2d_87" #Blob Conv2d_87's shape is [1,16,32,32]
    top:"Upsample_nearest" #Blob Upsample_nearest's shape is [1,16,HEIGHT,WIDTH]
    upsample_param{
        mode: NEAREST # or BILINEAR
        height: HEIGHT
        width: WIDTH
    }
}
```


- Upsample shape of bottom to `HEIGHT_SCALE` x `bottom_height` and `WIDTH_SCALE` x `bottom_width`

```
layer{
    name:"Upsample_nearest"
    type:"Upsample"
    bottom:"Conv2d_87" #Blob Conv2d_87's shape is [1,16,32,32]
    top:"Upsample_nearest" #Blob Upsample_nearest's shape is [1,16,32*HEIGHT_SCALE,32*WIDTH_SCALE]
    upsample_param{
        mode: NEAREST # or BILINEAR
        height_scale: HEIGHT_SCALE
        width_scale: WIDTH_SCALE
    }
}
```
- A face detection example  using above upsample see[Pytorch_Retinaface_To_Caffe](https://github.com/jnulzl/Pytorch_Retinaface_To_Caffe/tree/master/toCaffe/models)


# Caffe

[![Build Status](https://travis-ci.org/BVLC/caffe.svg?branch=master)](https://travis-ci.org/BVLC/caffe)
[![License](https://img.shields.io/badge/license-BSD-blue.svg)](LICENSE)

Caffe is a deep learning framework made with expression, speed, and modularity in mind.
It is developed by Berkeley AI Research ([BAIR](http://bair.berkeley.edu))/The Berkeley Vision and Learning Center (BVLC) and community contributors.

Check out the [project site](http://caffe.berkeleyvision.org) for all the details like

- [DIY Deep Learning for Vision with Caffe](https://docs.google.com/presentation/d/1UeKXVgRvvxg9OUdh_UiC5G71UMscNPlvArsWER41PsU/edit#slide=id.p)
- [Tutorial Documentation](http://caffe.berkeleyvision.org/tutorial/)
- [BAIR reference models](http://caffe.berkeleyvision.org/model_zoo.html) and the [community model zoo](https://github.com/BVLC/caffe/wiki/Model-Zoo)
- [Installation instructions](http://caffe.berkeleyvision.org/installation.html)

and step-by-step examples.

## Custom distributions

 - [Intel Caffe](https://github.com/BVLC/caffe/tree/intel) (Optimized for CPU and support for multi-node), in particular Intel® Xeon processors.
- [OpenCL Caffe](https://github.com/BVLC/caffe/tree/opencl) e.g. for AMD or Intel devices.
- [Windows Caffe](https://github.com/BVLC/caffe/tree/windows)

## Community

[![Join the chat at https://gitter.im/BVLC/caffe](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/BVLC/caffe?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)

Please join the [caffe-users group](https://groups.google.com/forum/#!forum/caffe-users) or [gitter chat](https://gitter.im/BVLC/caffe) to ask questions and talk about methods and models.
Framework development discussions and thorough bug reports are collected on [Issues](https://github.com/BVLC/caffe/issues).

Happy brewing!

## License and Citation

Caffe is released under the [BSD 2-Clause license](https://github.com/BVLC/caffe/blob/master/LICENSE).
The BAIR/BVLC reference models are released for unrestricted use.

Please cite Caffe in your publications if it helps your research:

    @article{jia2014caffe,
      Author = {Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor},
      Journal = {arXiv preprint arXiv:1408.5093},
      Title = {Caffe: Convolutional Architecture for Fast Feature Embedding},
      Year = {2014}
    }