Open Entel opened 5 years ago
Are you trying to learn from your own dataset?
Then you have to create an LMDB. Train with it
Are you trying to learn from your own dataset?
Then you have to create an LMDB. Train with it
Thanks for your reply. Excuse me, my dataset is a list like:
FEATURE_0_0, FEATURE_0_1, FEATURE_0_2, ... FEATURE_0_N
FEATURE_1_0, FEATURE_1_1, FEATURE_1_2, ... FEATURE_1_N
FEATURE_2_0, FEATURE_2_1, FEATURE_2_2, ... FEATURE_2_N
...
If I want to make a autoencoder to train this data, how can I make it into a LMDB? I know the LMDB format likes:
IMAGE_PATH LABEL
IMAGE_PATH LABEL
IMAGE_PATH LABEL
...
Should I make the list into:
FEATURE_0_0, FEATURE_0_1, FEATURE_0_2, ... FEATURE_0_N FEATURE_0_0, FEATURE_0_1, FEATURE_0_2, ... FEATURE_0_N
FEATURE_1_0, FEATURE_1_1, FEATURE_1_2, ... FEATURE_1_N FEATURE_1_0, FEATURE_1_1, FEATURE_1_2, ... FEATURE_1_N
FEATURE_2_0, FEATURE_2_1, FEATURE_2_2, ... FEATURE_2_N FEATURE_2_0, FEATURE_2_1, FEATURE_2_2, ... FEATURE_2_N
...
Can I use a full connection layer as output? Thank you.
Are you trying to learn from your own dataset? Then you have to create an LMDB. Train with it
Thanks for your reply. Excuse me, my dataset is a list like:
FEATURE_0_0, FEATURE_0_1, FEATURE_0_2, ... FEATURE_0_N FEATURE_1_0, FEATURE_1_1, FEATURE_1_2, ... FEATURE_1_N FEATURE_2_0, FEATURE_2_1, FEATURE_2_2, ... FEATURE_2_N ...
If I want to make a autoencoder to train this data, how can I make it into a LMDB? I know the LMDB format likes:
IMAGE_PATH LABEL IMAGE_PATH LABEL IMAGE_PATH LABEL ...
Should I make the list into:
FEATURE_0_0, FEATURE_0_1, FEATURE_0_2, ... FEATURE_0_N FEATURE_0_0, FEATURE_0_1, FEATURE_0_2, ... FEATURE_0_N FEATURE_1_0, FEATURE_1_1, FEATURE_1_2, ... FEATURE_1_N FEATURE_1_0, FEATURE_1_1, FEATURE_1_2, ... FEATURE_1_N FEATURE_2_0, FEATURE_2_1, FEATURE_2_2, ... FEATURE_2_N FEATURE_2_0, FEATURE_2_1, FEATURE_2_2, ... FEATURE_2_N ...
Can I use a full connection layer as output? Thank you.
I think you need to make the feature data into a image file.
and make file list (.txt) like this
IMAGE_PATH LABEL
9/label9_77.jpg 9
9/label9_78.jpg 9
9/label9_80.jpg 9
9/label9_82.jpg 9
9/label9_83.jpg 9
9/label9_84.jpg 9
9/label9_85.jpg 9
9/label9_86.jpg 9
9/label9_91.jpg 9
and You can create an LMDB using convert_imageset
I don't know everything, so there may be other ways. :)
I am a very new user of caffe. I just installed caffe and run the mnist example well. However, I don't quite understand how I can use caffe to implement my own dataset which is a list of features or vectors in same dimension? What should the data format be? Is it the same way to load data like image dataset?
Many thanks!!!! Any advice would be appreciated!