SeetaPsych Face Enhanced
Enhanced face modules for SeetaPsych
Usage
This project is already included in the seetapsych-lib default configuration. Download and use it via seetapsych-manager download.
For usage, refer to SeetaPsych.
You can additionally add this algorithm module using the following methods.
WebUI
Run seetapsych-webui with the --dirs argument to use it.
seetapsych-webui --files seetapsych_face_ex/modules/dense_landmarks.yml
Programmatic Usage
Add the following code in your program to use this algorithm module.
from seetapsych_lib.runtime.factory import Factory
from seetapsych_lib.runtime.pipeline import Pipeline
factory = Factory()
factory.load_file_modules("seetapsych_face_ex/modules/dense_landmarks.yml")
pipeline = Pipeline(factory, ...)
pipeline.add_attributes("face/dense_landmarks")
Introduction
SeetaDenseLandmarks
ONNX-based dense facial landmark detection model by SeetaPsych, capable of detecting 280 2D landmarks. Accepts either a face bounding box or sparse landmarks (2/5/280 points) as input. When given a bbox, it first predicts an initial coarse set, then optionally runs a refinement pass aligned via 5-point similarity transform. Network input size is fixed at 192x192.
Module config: dense_landmarks.yml.
Provide Attributes: face/dense_landmarks.
Requires: face/detection (primary). Optionally leverages face/landmarks if available for better alignment.
Available model: seeta-face-ex-dense-landmarks-280.onnx (recommended).
Parameters:
refine(bool, defaulttrue): Enable the second-pass refinement using 5-point similarity alignment.
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