- 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) 8×8: 1000 Object Categories
- BVLC Reference CaffeNet (Fully Convolutional) 34×17: 1000 Object Categories
- MIT Places-CNN Hybrid (Places + ImageNet): 971 Object Categories + 200 Scene Categories = 1171 Categories
(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 64-bit for osx I used this 1 year old branch which is about 1000 commits behind the master... I think the oF community is getting ready to release a stable 64-bit osx version??? Nick Hardeman's OSX 64-bit openFrameworks branch
- clone this repo into of_directory/addons/ofxCaffe
- clone ofxOpenCv2461 into of_directory/addons/ofxOpenCv2461 (could possibly be replaced by other opencv libraries, likely not the one that ships with openframeworks though; I've included OSX compiled OpenCV 2461 libraries in the addon/libs/opencv folder)
- 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 (could make a script for this...; I know this last step is ridiculous. You have to go into the code and see what the names are and I probably changed the names too... well some of them anyways. I will make a script if there is enough interest...)
- '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
- 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)
- Properly crop images and mirror them to produce batch images
- R-CNN region proposals
- Possibly other models can support region proposals and still be fast
- Add Network in Network
- Add Flickr style Fine Tuning
- Alternatives to visualizing layers? Deconvnets? Projections?