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- File "/pythonpath/python3.7/site-packages/caffe/pycaffe.py", line 119, in _Net_forward
- outputs = set(self.outputs + blobs)
- TypeError: ufunc 'add' did not contain a loop with signature matching types dtype('<U32') dtype('<U32') dtype('<U32')
- nn = caffe.Net('/model_path/model.prototxt',
- '/model_path/model.caffemodel',
- caffe.TEST)
- WARNING: Logging before InitGoogleLogging() is written to STDERR
- W0423 14:53:15.663930 11914 _caffe.cpp:139] DEPRECATION WARNING - deprecated use of Python interface
- W0423 14:53:15.663944 11914 _caffe.cpp:140] Use this instead (with the named "weights" parameter):
- W0423 14:53:15.663946 11914 _caffe.cpp:142] Net('/path/model.prototxt', 1, weights='/path/model.caffemodel')
- I0423 14:53:15.665053 11914 net.cpp:51] Initializing net from parameters:
- state {
- phase: TEST
- level: 0
- }
- layer {
- name: "dense_1_input"
- type: "Input"
- top: "dense_1_input"
- input_param {
- shape {
- dim: 1
- dim: 40
- }
- }
- }
- .... more layers ...
- layer {
- name: "output_activation"
- type: "Softmax"
- bottom: "output"
- top: "output_activation"
- }
- I0423 14:53:15.665112 11914 layer_factory.hpp:77] Creating layer dense_1_input
- I0423 14:53:15.665118 11914 net.cpp:84] Creating Layer dense_1_input
- I0423 14:53:15.665122 11914 net.cpp:380] dense_1_input -> dense_1_input
- I0423 14:53:15.665140 11914 net.cpp:122] Setting up dense_1_input
- I0423 14:53:15.665143 11914 net.cpp:129] Top shape: 1 40 (40)
- I0423 14:53:15.665148 11914 net.cpp:137] Memory required for data: 160
- .... more layers ...
- I0423 14:53:15.665232 11914 layer_factory.hpp:77] Creating layer output_activation
- I0423 14:53:15.665236 11914 net.cpp:84] Creating Layer output_activation
- I0423 14:53:15.665239 11914 net.cpp:406] output_activation<- output
- I0423 14:53:15.665242 11914 net.cpp:380] output_activation-> output_activation
- I0423 14:53:15.665248 11914 net.cpp:122] Setting up output_activation
- I0423 14:53:15.665251 11914 net.cpp:129] Top shape: 1 3 (3)
- I0423 14:53:15.665254 11914 net.cpp:137] Memory required for data: 248
- I0423 14:53:15.665256 11914 net.cpp:200] output_activation does not need backward computation.
- .... more layers ...
- I0423 14:53:15.665269 11914 net.cpp:242] This network produces output output_activation
- I0423 14:53:15.665272 11914 net.cpp:255] Network initialization done.
- # print data, its shape and type
- print("Data:")
- print(test_data)
- print("Data shape:")
- print(test_data.shape)
- print("Data type:")
- print(type(test_data))
- print("Type of array elements:")
- print(type(test_data[0][0]))
- # forward data through caffe model
- out = nn.forward(test_data)
- pred_probas = out['prob']
- print(pred_probas.argmax())
- Data:
- [[ 0.2655475 0.2655475 0.2655475 0.2655475 0.2655475 0.26516597
- 0.26516597 0.26516597 0.26516597 0.26516597 -0.03401361 -0.04166667
- -0.03996599 -0.01870748 -0.01785714 -0.02636054 -0.0255102 -0.03401361
- -0.03231293 -0.0212585 0.02047792 0.02047792 0.02047792 0.02047792
- 0.02047792 0.02047792 0.02319407 0.02319407 0.02319407 0.02594073
- 0. 0. 0. 0. 0. 0.
- 0.01176471 0. 0. 0.01189689]]
- Data shape:
- (1, 40)
- Data type:
- <class 'numpy.ndarray'>
- Type of array elements:
- <class 'numpy.float64'>
- Traceback (most recent call last):
- File "/path/caffe_nn_test.py", line 41, in <module>
- out = nn.forward(test_data)
- File "//python3.7/site-packages/caffe/pycaffe.py", line 119, in _Net_forward
- outputs = set(self.outputs + blobs)
- TypeError: ufunc 'add' did not contain a loop with signature matching types dtype('<U32') dtype('<U32') dtype('<U32')
- # load net from files
- nn = caffe.Net('/model_path/model.prototxt',
- '/model_path/model.caffemodel',
- caffe.TEST)
- # test_data is a numpy array with the shape (1, 40)
- # set input for neural network
- nn.blobs['dense_1_input'] = test_data
- # forward data through caffe model
- out = nn.forward(test_data)
- # get class prediction
- pred_probas = out['prob']
- print(pred_probas.argmax())
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