SeetaPsych Face Enhanced

Enhanced face modules for SeetaPsych

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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")

For complete end-to-end examples with visualization, see:

• examples/image_dense_landmarks.py — static-image face detection via InsightFace RetinaFace followed by 280-point dense landmarks.

Module Catalog

SeetaDenseLandmarks

Predict 280-point dense facial landmarks from face bounding box or sparse facial landmarks with optional second-pass refinement.

Figure 1. SeetaDenseLandmarks output visualization — detected face bbox and 280-point dense facial landmarks.

Module config: dense_landmarks.yml

Description: 280-point dense facial landmark predictor supporting bbox→initial→refine two-pass or sparse-landmark input paths.

Parameters

Models

Output Attributes

• face/dense_landmarks — spec.