app.py

#!/usr/bin/env python

from __future__ import annotations
import pathlib
import cv2
import gradio as gr
import huggingface_hub
import insightface
import numpy as np
import onnxruntime as ort

TITLE = "insightface Person Detection"
DESCRIPTION = "https://github.com/deepinsight/insightface/tree/master/examples/person_detection"


def load_model():
    path = huggingface_hub.hf_hub_download("public-data/insightface", "models/scrfd_person_2.5g.onnx")
    options = ort.SessionOptions()
    options.intra_op_num_threads = 8
    options.inter_op_num_threads = 8
    session = ort.InferenceSession(
        path, sess_options=options, providers=["CPUExecutionProvider", "CUDAExecutionProvider"]
    )
    model = insightface.model_zoo.retinaface.RetinaFace(model_file=path, session=session)
    return model


def detect_person(
    img: np.ndarray, detector: insightface.model_zoo.retinaface.RetinaFace
) -> np.ndarray:
    bboxes, kpss = detector.detect(img)
    bboxes = np.round(bboxes[:, :4]).astype(int)
    return bboxes


def extract