I currently work myself through the caffe/examples/
to learn more about caffe/pycaffe
.
In the 02-fine-tuning.ipynb-notebook
there is a codecell which shows how to create a caffenet which takes unlabeled "dummmy data"
as input, allowing us to set its input images externally. The notebook can be found here:
https://github.com/BVLC/caffe/blob/master/examples/02-fine-tuning.ipynb
There is a given code-cell, which throws an error:
dummy_data = L.DummyData(shape=dict(dim=[1, 3, 227, 227]))
imagenet_net_filename = caffenet(data=dummy_data, train=False)
imagenet_net = caffe.Net(imagenet_net_filename, weights, caffe.TEST)
error:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-6-9f0ecb4d95e6> in <module>()
1 dummy_data = L.DummyData(shape=dict(dim=[1, 3, 227, 227]))
----> 2 imagenet_net_filename = caffenet(data=dummy_data, train=False)
3 imagenet_net = caffe.Net(imagenet_net_filename, weights, caffe.TEST)
<ipython-input-5-53badbea969e> in caffenet(data, label, train, num_classes, classifier_name, learn_all)
68 # write the net to a temporary file and return its filename
69 with tempfile.NamedTemporaryFile(delete=False) as f:
---> 70 f.write(str(n.to_proto()))
71 return f.name
~/anaconda3/envs/testcaffegpu/lib/python3.6/tempfile.py in func_wrapper(*args, **kwargs)
481 @_functools.wraps(func)
482 def func_wrapper(*args, **kwargs):
--> 483 return func(*args, **kwargs)
484 # Avoid closing the file as long as the wrapper is alive,
485 # see issue #18879.
TypeError: a bytes-like object is required, not 'str'
Anyone knows how to do this right?