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detect.py
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detect.py
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# coding: utf-8
import argparse
from util.loaders import read_classes, get_color_dict, read_anchors
from models import YOLO
def parse_args():
parser = argparse.ArgumentParser(description="Object detection.")
parser.add_argument('--model_load_path', type=str, default='',
help='Input path to models.')
parser.add_argument('--class_path', type=str, default='data/coco.names',
help='Path to a file to store names of the classes.')
parser.add_argument('--color_path', type=str, default='data/colors',
help='Path to a file which stores colors.')
parser.add_argument('--anchor_path', type=str, default='data/anchors',
help='Input path to anchors.')
parser.add_argument('--input_path', type=str, default='',
help='Path to the file used for detection. '
'If zero, camera on your computer will be used.')
parser.add_argument('--output_path', type=str, default='',
help='Path to the output image or video. '
'If Empty, the predicted image will not be saved.')
parser.add_argument('--do_show', action='store_true', default=False,
help="Whether to show predictions.")
parser.add_argument('--score_threshold', type=float, default=0.5,
help='Threshold of score(IOU * P(Object)).')
parser.add_argument('--iou_threshold', type=float, default=0.5,
help='Threshold of IOU used for calculation of NMS.')
parser.add_argument('--device_ids', type=str, default='-1',
help="Device ids. "
"Should be seperated by commas. "
"-1 means cpu.")
parser.add_argument('--num_processes', type=int, default=0,
help='number of processes.')
return parser.parse_args().__dict__
if __name__ == '__main__':
args = parse_args()
classes = read_classes(args["class_path"])
color_dict = get_color_dict(classes, args["color_path"])
anchors = read_anchors(args["anchor_path"]) if args["anchor_path"] else None
model = YOLO(classes,
model_load_path=args["model_load_path"],
anchors=anchors,
device_ids=args["device_ids"])
if args["input_path"].endswith(".jpg") or \
args["input_path"].endswith(".jpeg") or \
args["input_path"].endswith(".png"):
model.detect_image(
args["input_path"],
args["score_threshold"],
args["iou_threshold"],
color_dict,
do_show=args["do_show"],
delay=0,
output_path=args["output_path"] if args["output_path"] else None
)
elif args["input_path"].endswith(".mp4"):
model.detect_video(
args["input_path"],
args["score_threshold"],
args["iou_threshold"],
color_dict,
do_show=args["do_show"],
delay=1,
output_path=args["output_path"] if args["output_path"] else None
)
elif args["input_path"] == '0':
model.detect_video(
0,
args["score_threshold"],
args["iou_threshold"],
color_dict,
do_show=args["do_show"],
delay=1,
output_path=args["output_path"] if args["output_path"] else None
)
else:
print("Wrong type!")
exit(-1)