e pascalcontext-fcn32s-heavy.caffemodel and am trying to run it on a test image similar to the Caffe ImageNet tutorial:
import numpy as np
import caffe
import pascalcontext_layers
model_def = 'pascalcontext-fcn32s/val.prototxt'
model_weights = 'pascalcontext-fcn32s/pascalcontext-fcn32s-heavy.caffemodel'
net = caffe.Net(model_def, model_weights, caffe.TEST)
however I'm running into the error:
F0621 16:54:56.941515 21806 layer_factory.hpp:81] Check failed: registry.count(type) == 1 (0 vs. 1) Unknown layer type: Python (known types: AbsVal, Accuracy, ArgMax, BNLL, BatchNorm, BatchReindex, Bias, Concat, ContrastiveLoss, Convolution, Crop, Data, Deconvolution, Dropout, DummyData, ELU, Eltwise, Embed, EuclideanLoss, Exp, Filter, Flatten, HDF5Data, HDF5Output, HingeLoss, Im2col, ImageData, InfogainLoss, InnerProduct, Input, LRN, LSTM, LSTMUnit, Log, MVN, MemoryData, MultinomialLogisticLoss, PReLU, Parameter, Pooling, Power, RNN, ReLU, Reduction, Reshape, SPP, Scale, Sigmoid, SigmoidCrossEntropyLoss, Silence, Slice, Softmax, SoftmaxWithLoss, Split, TanH, Threshold, Tile, WindowData)
*** Check failure stack trace: ***
when I specify the val.prototxt file since the first layer defined is a type: "Python" layer which is a custom layer defined in "pascalcontext_layers.py" which is provided in the FCN model git repo.
Can anyone help me with this issue? Any help would be appreciated.
Also, if someone has a step-by-step guide on how to use the FCN models provided from the git repo it would be greatly appreciated. I am confused with what the "net.py" and "solve.py" function are used for for each model.
Thanks
You should use deploy.prototxt instead of val.prototxt. There is an example of deploy.prototxt in the folder "voc-fcn8s"
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