This is a port of the caffe implementation of the ICCV'15 paper "FlowNet: Learning Optical Flow with Convolutional Networks" by Dosovitskiy et al to Theano and Lasagne. It contains both FlowNetS and FlowNetC models and a port of the correlation layer.
| Ground Truth | FlowNetS | FlowNetC |
|---|---|---|
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- flownet-caffe (for the weight conversion script only).
- Theano 0.8.2
- Lasagne
- numpy
- flow-io-opencv can be used to generate optical flow visualization from *.flo outputs
caffe_to_numpy.py script can be used to convert caffe models to the npz format.
caffemodel and prototxt files should be placed in the model subdirectory. Alternatively you can download weights from Google Drive.
python FlowNetS.py
python FlowNetC.pyThe source code is distributed under the MIT license. Please refer to us if you find this code useful.