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sample_tflite.py
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sample_tflite.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
import copy
import time
import argparse
import cv2
from yolox.yolox_tflite import YoloxTFLite
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument("--device", type=int, default=0)
parser.add_argument("--movie", type=str, default=None)
parser.add_argument("--image", type=str, default=None)
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(
"--model",
type=str,
default='04.model/yolox_nano_float16_quantize.tflite',
)
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=0.3,
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
if args.movie is not None:
cap_device = args.movie
image_path = args.image
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
# カメラ準備 ###############################################################
if image_path is None:
cap = cv2.VideoCapture(cap_device)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, cap_width)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, cap_height)
# モデルロード #############################################################
yolox = YoloxTFLite(
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,
)
if image_path is not None:
image = cv2.imread(image_path)
# 推論実施 ##############################################################
start_time = time.time()
bboxes, scores, class_ids = yolox.inference(image)
elapsed_time = time.time() - start_time
print('Elapsed time', elapsed_time)
# 描画 ##################################################################
image = draw_debug(
image,
elapsed_time,
score_th,
bboxes,
scores,
class_ids,
)
cv2.imshow('YOLOX ONNX Sample', image)
cv2.waitKey(0)
cv2.destroyAllWindows()
else:
while True:
start_time = time.time()
# カメラキャプチャ ################################################
ret, frame = cap.read()
if not ret:
break
debug_image = copy.deepcopy(frame)
# 推論実施 ########################################################
bboxes, scores, class_ids = yolox.inference(frame)
elapsed_time = time.time() - start_time
# デバッグ描画
debug_image = draw_debug(
debug_image,
elapsed_time,
score_th,
bboxes,
scores,
class_ids,
)
# キー処理(ESC:終了) ##############################################
key = cv2.waitKey(1)
if key == 27: # ESC
break
# 画面反映 #########################################################
cv2.imshow('YOLOX ONNX Sample', debug_image)
cap.release()
cv2.destroyAllWindows()
def draw_debug(image, elapsed_time, score_th, bboxes, scores, class_ids):
debug_image = copy.deepcopy(image)
for bbox, score, class_id in zip(bboxes, scores, class_ids):
x1, y1, x2, y2 = int(bbox[0]), int(bbox[1]), int(bbox[2]), int(bbox[3])
if score_th > score:
continue
# バウンディングボックス
debug_image = cv2.rectangle(
debug_image,
(x1, y1),
(x2, y2),
(0, 255, 0),
thickness=2,
)
# クラスID、スコア
score = '%.2f' % score
text = '%s:%s' % (str(int(class_id)), score)
debug_image = cv2.putText(
debug_image,
text,
(x1, y1 - 10),
cv2.FONT_HERSHEY_SIMPLEX,
0.7,
(0, 255, 0),
thickness=2,
)
# 推論時間
text = 'Elapsed time:' + '%.0f' % (elapsed_time * 1000)
text = text + 'ms'
debug_image = cv2.putText(
debug_image,
text,
(10, 30),
cv2.FONT_HERSHEY_SIMPLEX,
0.7,
(0, 255, 0),
thickness=2,
)
return debug_image
if __name__ == '__main__':
main()