This release is a pre-release and may not be stable for production use.
SeetaPsych Gaze
Gaze estimation 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.
The gaze estimation algorithms depend on open-gaze-estimation. Please install it from GitHub separately:
uv pip install git+https://github.com/Elorfiniel/open-gaze-estimation-2025-release.git
You can additionally add this algorithm module using the following methods.
WebUI
Run seetapsych-webui with the --files argument to use it.
seetapsych-webui --files \
seetapsych_gaze_screen/modules/affnet.yml \
seetapsych_gaze_screen/modules/itracker-plus.yml \
seetapsych_gaze_screen/modules/tdgazenet.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_gaze_screen/modules/affnet.yml")
pipeline = Pipeline(factory, ...)
pipeline.add_attributes("face/gaze_screen")
Module Catalog
| Module YAML | Package Name |
|---|---|
affnet.yml |
GazeScreen-AFFNet(OpenGaze) |
itracker-plus.yml |
GazeScreen-ITrackerPlus(OpenGaze) |
tdgazenet.yml |
GazeScreen-TDGazeNet(OpenGaze) |
GazeScreen-AFFNet(OpenGaze)
Open-source gaze estimation toolkit providing screen gaze coordinates from facial landmarks or mesh.
Module config: affnet.yml
| Package | Provides | Requires |
|---|---|---|
| GazeScreen-AFFNet(OpenGaze) | face/gaze_screen |
face/mesh |
Description
Estimate screen gaze coordinates via AFFNet attention fusion network; outputs one shared gaze vector applied to both eyes. Suitable for single-user desktop scenarios with medium accuracy and compute cost.
Parameters
| Name | Type | Default | Description |
|---|---|---|---|
data |
object | (see yml) | Camera/screen calibration and image preprocessing settings. camera and screen physical dimensions (mm/px) and sensor frame size must match the real setup for accurate gaze projection; adjust_size resizes input for throughput, larger increases accuracy but slows inference. |
Models
| Model | Version | Recommended |
|---|---|---|
opengaze-affnet-v2.safetensors |
2.0 | ✓ |
opengaze-affnet.safetensors |
1.0 |
GazeScreen-ITrackerPlus(OpenGaze)
Open-source gaze estimation toolkit providing screen gaze coordinates from facial landmarks or mesh.
Module config: itracker-plus.yml
| Package | Provides | Requires |
|---|---|---|
| GazeScreen-ITrackerPlus(OpenGaze) | face/gaze_screen |
face/mesh |
Description
Lightweight eye-and-face gaze point estimation; outputs one shared gaze vector applied to both eyes. Best for resource-constrained devices or real-time low-latency use cases with acceptable accuracy.
Parameters
| Name | Type | Default | Description |
|---|---|---|---|
data |
object | (see yml) | Camera/screen calibration and image preprocessing settings. camera and screen physical dimensions (mm/px) and sensor frame size must match the real setup for accurate gaze projection; adjust_size resizes input for throughput, larger increases accuracy but slows inference. |
Models
| Model | Recommended |
|---|---|
opengaze-itrackerplus.onnx |
✓ |
GazeScreen-TDGazeNet(OpenGaze)
Open-source gaze estimation toolkit providing screen gaze coordinates from facial landmarks or mesh.
Module config: tdgazenet.yml
| Package | Provides | Requires |
|---|---|---|
| GazeScreen-TDGazeNet(OpenGaze) | face/gaze_screen |
face/mesh |
Description
High-accuracy gaze estimation via TdGazeNet with 3D face prior, camera intrinsics and multi-task head; outputs distinct per-eye gaze vectors for left and right eye. Highest accuracy among OpenGaze variants at the cost of heavier compute.
Parameters
| Name | Type | Default | Description |
|---|---|---|---|
optimize |
selection | none |
Post-load structural optimization of the backbone. Set to reparameterize to fold BatchNorm into convolutions for faster inference at load-time cost; use none for training or debug workflows where exact weights must be preserved. Possible values: none, reparameterize. |
data |
object | (see yml) | Model topology, camera/screen calibration and image preprocessing settings. camera intrinsic/extrinsic/distortion matrices and screen physical dimensions must match the real setup for the 3D-face-prior projection to be accurate; image_size and bbox_scale tune face crop resolution vs. context margin. |
Models
| Model | Recommended |
|---|---|
opengeze-tdgazenet.safetensors |
✓ |
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