-
Notifications
You must be signed in to change notification settings - Fork 0
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
LitData Refactor PR1: Get individual functions for data pipelines #89
Conversation
* Refactor preprocessing config * Merge train and val data configs * Remove pipeline name * Modify backbone_config * Modify ckpts * Fix inference tests * Fix device for inference * Fix scale in inference * Fix Predictor * Modify `bottom_up` to `bottomup` * Fix bottomup inference * Fix scale in augmentation
* Refactor preprocessing config * Merge train and val data configs * Remove pipeline name * Modify backbone_config * Modify ckpts * Fix inference tests * Fix device for inference * Fix scale in inference * Fix Predictor * Modify `bottom_up` to `bottomup` * Fix bottomup inference * Fix scale in augmentation * Test remove image * Fix instance cropping * Fix tests * Remove scale in pipelines
…talmolab/sleap-nn into greg/minimalinstances
Note Currently processing new changes in this PR. This may take a few minutes, please wait... Files selected for processing (51)
Thank you for using CodeRabbit. We offer it for free to the OSS community and would appreciate your support in helping us grow. If you find it useful, would you consider giving us a shout-out on your favorite social media? TipsChatThere are 3 ways to chat with CodeRabbit:
Note: Be mindful of the bot's finite context window. It's strongly recommended to break down tasks such as reading entire modules into smaller chunks. For a focused discussion, use review comments to chat about specific files and their changes, instead of using the PR comments. CodeRabbit Commands (Invoked using PR comments)
Other keywords and placeholders
CodeRabbit Configuration File (
|
This is the first PR for #80. Here, we breakdown the operations in iter() of all data processing modules into individual functions that would be useful for implementing the get_chunks() (second PR for #80 ).