I tried running the code in a keras blog post.
The code writes to a .npy file as follows:
bottleneck_features_train = model.predict_generator(generator, nb_train_samples // batch_size)
np.save(open('bottleneck_features_train.npy', 'w'),bottleneck_features_train)
It then reads from this file:
def train_top_model():
train_data = np.load(open('bottleneck_features_train.npy'))
Now I get an error saying:
Found 2000 images belonging to 2 classes.
Traceback (most recent call last):
File "kerasbottleneck.py", line 103, in <module>
save_bottlebeck_features()
File "kerasbottleneck.py", line 69, in save_bottlebeck_features
np.save(open('bottleneck_features_train.npy', 'w'),bottleneck_features_train)
File "/opt/anaconda3/lib/python3.6/site-packages/numpy/lib/npyio.py", line 511, in save
pickle_kwargs=pickle_kwargs)
File "/opt/anaconda3/lib/python3.6/site-packages/numpy/lib/format.py", line 565, in write_array
version)
File "/opt/anaconda3/lib/python3.6/site-packages/numpy/lib/format.py", line 335, in _write_array_header
fp.write(header_prefix)
TypeError: write() argument must be str, not bytes
After this, I tried changing the file mode from 'w' to 'wb'. This resulted in an error while reading the file:
Found 2000 images belonging to 2 classes.
Found 800 images belonging to 2 classes.
Traceback (most recent call last):
File "kerasbottleneck.py", line 104, in <module>
train_top_model()
File "kerasbottleneck.py", line 82, in train_top_model
train_data = np.load(open('bottleneck_features_train.npy'))
File "/opt/anaconda3/lib/python3.6/site-packages/numpy/lib/npyio.py", line 404, in load
magic = fid.read(N)
File "/opt/anaconda3/lib/python3.6/codecs.py", line 321, in decode
(result, consumed) = self._buffer_decode(data, self.errors, final)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x93 in position 0: invalid start byte
How can I fix this error?