-
Notifications
You must be signed in to change notification settings - Fork 283
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
How to use the projector? #29
Comments
Normally you should be able to color by label if you provided the labels. For MNIST, you will have one color for each digit. Maybe this post can help your understanding? https://stackoverflow.com/questions/40849116/how-to-use-tensorboard-embedding-projector |
Thank you. Can you point me out where in your code you add the images for the projector summary? |
It is in the visualize_embeddings.py
|
So it's in the metadata tsv file that you need to save: tensorflow-triplet-loss/visualize_embeddings.py Lines 83 to 90 in fc69836
# Specify where you find the metadata
# Save the metadata file needed for Tensorboard projector
metadata_filename = "mnist_metadata.tsv"
with open(os.path.join(eval_dir, metadata_filename), 'w') as f:
for i in range(params.eval_size):
c = labels[i]
f.write('{}\n'.format(c))
embedding.metadata_path = metadata_filename If you want to visualize other colors, you can add it in the tsv file as a new column like this: metadata_filename = "mnist_metadata.tsv"
with open(os.path.join(eval_dir, metadata_filename), 'w') as f:
f.write("label\tother")
for i in range(params.eval_size):
c = labels[I]
other = c % 2
f.write('{}\t{}\n'.format(c, other))
embedding.metadata_path = metadata_filename |
During training, the projector shows some points in the PCA space. Every point has the same color. What do they represent? What can I infer about the training process from this graph?
The text was updated successfully, but these errors were encountered: