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Facemap Pose Estimation Inference #24
Facemap Pose Estimation Inference #24
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sidhulyalkar
commented
Sep 21, 2023
- Add facial_pose_model.py. Contains new facemap_model_schema with classes BodyPart, FacemapModel, FacemapPoseEstimationTask, and FacemapPoseEstimation.
- Explanatory Jupyter notebook not included for now. (Using LuLab data, and local testing pipeline). Includes functions ingest_model, and generate_pose_estimation_task, which insert into the FacemapModel, FacemapPoseEstimationTask, and fbe.VideoRecording tables.
…map pose inference
Co-authored-by: Thinh Nguyen <thinh@datajoint.com>
Co-authored-by: Thinh Nguyen <thinh@datajoint.com>
…hulyalkar/element-facemap into new_facemap_integration_test
…nk to facemap model table --> make into a secondary attr
…efault model is intially inserted
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Just a small consideration before merging. @ttngu207, do you agree that the table should be renamed here? Facemap's documentation uses keypoints and body parts interchangeably in their tutorials.
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# ----------------------------- Table declarations ---------------------- | ||
@schema | ||
class BodyPart(dj.Lookup): |
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Is this table better identified as KeyPoints
?
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I agree but then I believe Facemap itself still refers to those as bodyparts
, right?
The results are orofacial features, calling it body parts seems wrong. But if this is the terminology used in facemap, we should stick to the same term.
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Yes agreed, Facemap incorrectly uses the term 'BodyParts' to define their keypoints, but we should stick with their convention.
model_description='' : varchar(1000) # optional model description | ||
""" | ||
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class BodyPart(dj.Part): |
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This table could also be renamed KeyPoints
if the Lookup table above is renamed
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# ----------------------------- Table declarations ---------------------- | ||
@schema | ||
class BodyPart(dj.Lookup): |
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I agree but then I believe Facemap itself still refers to those as bodyparts
, right?
The results are orofacial features, calling it body parts seems wrong. But if this is the terminology used in facemap, we should stick to the same term.