simple_demo.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-

import csv
import time
import copy
import argparse

import cv2 as cv

from model.yolox.yolox_onnx import YoloxONNX


def get_args():
    parser = argparse.ArgumentParser()

    parser.add_argument("--device", type=int, default=0)
    parser.add_argument("--file", type=str, default=None)
    parser.add_argument("--fps", type=int, default=30)
    parser.add_argument("--width", help='cap width', type=int, default=960)
    parser.add_argument("--height", help='cap height', type=int, default=540)

    parser.add_argument("--skip_frame", type=int, default=0)

    parser.add_argument(
        "--model",
        type=str,
        default='model/yolox/yolox_nano.onnx',
    )
    parser.add_argument(
        '--input_shape',
        type=str,
        default="416,416",
        help="Specify an input shape for inference.",
    )
    parser.add_argument(
        '--score_th',
        type=float,
        default=0.7,
        help='Class confidence',
    )
    parser.add_argument(
        '--nms_th',
        type=float,
        default=0.45,
        help='NMS IoU threshold',
    )
    parser.add_argument(
        '--nms_score_th',
        type=float,
        default=0.1,
        help='NMS Score threshold',
    )
    parser.add_argument(
        "--with_p6",
        action="store_true",
        help="Whether your model uses p6 in FPN/PAN.",
    )

    args = parser.parse_args()

    return args


def main():
    # 引数解析 #################################################################
    args = get_args()
    cap_device = args.device
    cap_width = args.width
    cap_height = args.height
    fps = args.fps
    skip_frame = args.skip_frame

    model_path = args.model
    input_shape = tuple(map(int, args.input_shape.split(',')))
    score_th = args.score_th
    nms_th = args.nms_th
    nms_score_th = args.nms_score_th
    with_p6 = args.with_p6

    if args.file is not None:
        cap_device = args.file

    frame_count = 0

    # カメラ準備 ###############################################################
    cap = cv.VideoCapture(cap_device)
    cap.set(cv.CAP_PROP_FRAME_WIDTH, cap_width)
    cap.set(cv.CAP_PROP_FRAME_HEIGHT, cap_height)

    # モデルロード #############################################################
    yolox = YoloxONNX(
        model_path=model_path,
        input_shape=input_shape,
        class_score_th=score_th,
        nms_th=nms_th,
        nms_score_th=nms_score_th,
        with_p6=with_p6,
        # providers=['CPUExecutionProvider'],
    )

    # ラベル読み込み ###########################################################
    with open('setting/labels.csv', encoding='utf8') as f:
        labels = csv.reader(f)
        labels = [row for row in labels]

    while True:
        start_time = time.time()

        # カメラキャプチャ #####################################################
        ret, frame = cap.read()
        if not ret:
            continue
        debug_image = copy.deepcopy(frame)

        frame_count += 1
        if (frame_count % (skip_frame + 1)) != 0:
            continue

        # 検出実施 #############################################################
        bboxes, scores, class_ids = yolox.inference(frame)

        for bbox, score, class_id in zip(bboxes, scores, class_ids):
            class_id = int(class_id) + 1
            if score < score_th:
                continue

            # 検出結果可視化 ###################################################
            x1, y1 = int(bbox[0]), int(bbox[1])
            x2, y2 = int(bbox[2]), int(bbox[3])

            cv.putText(
                debug_image, 'ID:' + str(class_id) + ' ' +
                labels[class_id][0] + ' ' + '{:.3f}'.format(score),
                (x1, y1 - 15), cv.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2,
                cv.LINE_AA)
            cv.rectangle(debug_image, (x1, y1), (x2, y2), (0, 255, 0), 2)

        # キー処理(ESC：終了) #################################################
        key = cv.waitKey(1)
        if key == 27:  # ESC
            break

        # FPS調整 #############################################################
        elapsed_time = time.time() - start_time
        sleep_time = max(0, ((1.0 / fps) - elapsed_time))
        time.sleep(sleep_time)

        cv.putText(
            debug_image,
            "Elapsed Time:" + '{:.1f}'.format(elapsed_time * 1000) + "ms",
            (10, 30), cv.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 0), 2, cv.LINE_AA)

        # 画面反映 #############################################################
        cv.imshow('NARUTO HandSignDetection Simple Demo', debug_image)

    cap.release()
    cv.destroyAllWindows()


if __name__ == '__main__':
    main()