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Welcome to the orcagsoc wiki!
- Report progress on goals from last week
- Discuss any blocking issues or strategic decisions (e.g. upcoming scheduled events, code reviews, etc.)
- Set new goals for next week
Mentor thoughts on process for weekly Friday meetings? Jesse: report on progress, blocking issues Scott: include goals for next week Valentina: also schedule (code) review events
Kunal report:
Scott chat links:
How to visualize the model performance?
- ROC curves
- Confusion matrices
Diego Q for Kunal: What is difference in performance if mp3 is used instead of WAV?
Scott thot: Two experiment ideas to seek an answer --
- stream both HLS and FLAC when SRKWs are next calling, &
- Go back to WAV files in training (e.g. Pod.Cast rounds) and convert WAV samples to mp3, then re-run model... Ask Val for ideas, too...
Kunal goals:
- VGG may be best, but also trying ResNet and convolution 2D model
- Jesse: look at how to make code reusable (e.g. Orca), Kunal will convert from collab to to Python scripts…
- Valentina: Add markdown cells to document code (including organizing packages), and even images
- Abhishek: For next notebook, add subsections in notebook and a top-level README
Diego report:
- Added Bigg’s to classification UI
- Added option to indicate experience level of labeler
- Table of labels, including mp3 filename, label, and user experience level
Diego goals:
- Test GUI with Kunal’s processed data (e.g. put it in S3 bucket)
- Jesse: include tests (for Flask you can use libraries to mock a post, and ensure something is returned) and embed in continuous integration
- Abhishek goal: you had chance to look at JS library?
- Valentina: look into each cloud environment’s app service…
- Diego: Heroku is easier (Github integration vs ssh from Ubuntu instance), but is more expensive
**Diego updates: ** -- UI branch w/ J,K,L and no orca categories (bird, ship…) -- SV: send goals for “expert user (SRKW, orca)” to Diego -- Error testing pod.cast - Goal: Will compare w/Valentina - SV: share Akash/Prakruti emails?
Kunal updates: -- Will share notebook with Ketos error -- Goals: -- Why getting error in Ketos (share w/Jesse to document for Fabio/Oliver)
Abhishek: -- keep documenting in the orcasoc repo README!
Val: -- experimenting with edge computing (with Fabio!)
Kunal, Val, and Scott discussed Kunal's initial call modeling efforts training with Podcast round 3 set and Val's latest pre-processing approaches.
Scott's list of insights from the discussion New open-source bioacoustic labeling tools should provide guidance about decisions made by domain experts (e.g. when validating predictions in a tool like Podcast and move towards standardization of annotation metadata:
- time bounds (fixed duration or variable procedure, start bound time vs signal start time, how much background noise included before/after...) and resolution
- frequency bounds and resolution
- Whether to exclude calls with clicks, or whistles, or snaps?
- What is a sufficient signal to noise ratio to qualify as a call vs a faint call vs a possible call?
Kunal ended with a good question about what to do next to improve his model performance...