fabopsy-lib 0.0.1

Face and body based psychology analysis

FaboPsy Lib

Face and body based psychology analysis

FaboPsy Lib is a Python library for face- and body-based psychology analysis. It provides a modular Pipeline/Runner runtime and an optional Streamlit WebUI.

Requirements

• Python >= 3.10
• (Recommended) uv package manager: https://github.com/astral-sh/uv

Installation

Using uv (recommended)

uv sync

Install development dependencies (WebUI, etc.):

uv sync --group dev

Using pip

Install runtime dependencies:

python -m pip install .

If you want to run the WebUI, install extra tools manually:

python -m pip install streamlit opencv-python

Quick Start

Run WebUI (Streamlit)

streamlit run fabopsy_lib/webui/app.py -- --log INFO

Common arguments (pass them after --):

• --dirs <DIR...>: load modules from directories
• --files <FILE...>: load modules from local config files
• --urls <URL...>: load modules from remote URLs
• --disable-builtin: disable builtin modules
• --cache-dir <DIR>: model cache directory
• --upload-dir <DIR>: upload directory
• --log <LEVEL>: log level (e.g., DEBUG, INFO, WARNING, or an integer like 10)

Programmatic Usage

import numpy as np

from fabopsy_lib.api import Device
from fabopsy_lib.runtime import Factory, Pipeline, Runner

factory = Factory()
factory.load_builtin_modules()
factory.load_local_module("fabopsy_lib/example/example.toml")

pkg = next(p for p in factory.packages if p.name == "Example Package")

pipeline = Pipeline(factory, packages=[pkg.uid])
pipeline.add_model(pkg.uid, pkg.models[0].uid)
pipeline.solve()

ok, _ = pipeline.satisfied()
if not ok:
    pipeline.install_requirements()

runner = Runner(pipeline, device=Device("cpu"))
result = runner.run(np.zeros((64, 64, 3), dtype=np.uint8))
print(result)

Configuration

Environment Variables

The following environment variables are supported:

Env	Description
FABOPSY_LOG_LEVEL	Change default log level. Could be WARNING, INFO, DEBUG, or an integer (e.g., 10).
FABOPSY_CACHE_DIR	Base directory for model cache. Models are cached under <CACHE_DIR>/models.

Development

Version check:

python tests/version.py