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simple_demo_without_post.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
import csv
import time
import copy
import argparse
import cv2 as cv
from model.yolox.yolox_onnx_without_post 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_with_post.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(
"--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
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)
cap_fps = cap.get(cv.CAP_PROP_FPS)
fourcc = cv.VideoWriter_fourcc('m', 'p', '4', 'v')
video_writer = cv.VideoWriter(
filename='output.mp4',
fourcc=fourcc,
fps=cap_fps,
frameSize=(cap_width, cap_height),
)
# モデルロード #############################################################
yolox = YoloxONNX(
model_path=model_path,
input_shape=input_shape,
class_score_th=score_th,
with_p6=with_p6,
)
# 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])
score = float(score)
cv.putText(
debug_image, f'ID:{str(class_id)} {labels[class_id][0]} {score:.3f}',
(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)
# 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)
video_writer.write(debug_image)
# キー処理(ESC:終了) #################################################
key = cv.waitKey(1) if args.file is None else cv.waitKey(0)
if key == 27: # ESC
break
if video_writer:
video_writer.release()
if cap:
cap.release()
cv.destroyAllWindows()
if __name__ == '__main__':
main()