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openFrameworks addon for visualizing and interfacing with pre-trained models in Caffe: Convolutional Architectures for Fast Feature Embedding. Requires Caffe, openFrameworks 64-bit, glog, hdf5, OpenCV, CUDA, pkmMatrix, and pkmHeatmap. Pre-trained models not included but can be found linked in Caffe's "Model Zoo" and placed in the bin/data directory of the example project.

Home Page: http://pkmital.com/home/2015/01/04/real-time-object-recognition-with-ofxcaffe/

Makefile 0.03% GLSL 0.13% C++ 36.58% C 63.26% Python 0.01%

ofxcaffe's Introduction

ofxCaffe

Interface for Caffe: Convolutional Architectures for Fast Feature Embedding from BVLC.

img0 img1 img2 img3

Current Models

  • VGG ILSVRC 2014 (16 Layers): 1000 Object Categories
  • VGG ILSVRC 2014 (19 Layers): 1000 Object Categories
  • BVLC GoogLeNet: 1000 Object Categories
  • Region-CNN ILSVRC 2013: 200 Object Categories (Region proposals not yet implemented)
  • BVLC Reference CaffeNet: 1000 Object Categories
  • BVLC Reference CaffeNet (Fully Convolutional) 8ร—8: 1000 Object Categories
  • BVLC Reference CaffeNet (Fully Convolutional) 34ร—17: 1000 Object Categories
  • MIT Places-CNN Hybrid (Places + ImageNet): 971 Object Categories + 200 Scene Categories = 1171 Categories

Instructions

(Warning: these probably won't work and will require edits/your help)

  • Install Caffe and all dependencies (-lglog -lgflags -lprotobuf -lleveldb -lsnappy -llmdb -lboost_system -lhdf5_hl -lhdf5 -lm -lopencv_core -lopencv_highgui -lopencv_imgproc -lcblas)
  • Install openFrameworks master
  • clone this repo into of_directory/addons/ofxCaffe
  • clone pkmMatrix into of_directory/../pkm/pkmMatrix (This is OSX only due to its depency on Accelerate.framework; provides vectorized operations; can be replaced with OpenCV; please submit pull request and I wiil merge...)
  • clone pkmHeatmap into of_directory/../pkm/pkmHeatmap (Converts grayscale images to RGB JET colormap using GPU)
  • Go to the Caffe Model Zoo and download all necessary .caffemodel files into the bin/data directory

Example Project: Visualization

  • '1': Toggle predicted label output
  • '2': Toggle layer parameters
  • '3': Toggle layer outputs
  • '4': Toggle probabilities graph
  • '[' / ']': Change the current layer visualized
  • '-' / '+': Change the current model
  • '0': Toggle webcamera image

Troubleshooting

  • First make sure you can run Caffe and all tests (make runall)
  • Check the Project.xcconfig defines and make sure they match up with where things should be (library files/source code)

To Do

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