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infer-det.py
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infer-det.py
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from models import TRTModule # isort:skip
import argparse
from pathlib import Path
import cv2
import torch
from config import CLASSES, COLORS
from models.torch_utils import det_postprocess
from models.utils import blob, letterbox, path_to_list
def main(args: argparse.Namespace) -> None:
device = torch.device(args.device)
Engine = TRTModule(args.engine, device)
H, W = Engine.inp_info[0].shape[-2:]
# set desired output names order
Engine.set_desired(['num_dets', 'bboxes', 'scores', 'labels'])
images = path_to_list(args.imgs)
save_path = Path(args.out_dir)
if not args.show and not save_path.exists():
save_path.mkdir(parents=True, exist_ok=True)
for image in images:
save_image = save_path / image.name
bgr = cv2.imread(str(image))
draw = bgr.copy()
bgr, ratio, dwdh = letterbox(bgr, (W, H))
rgb = cv2.cvtColor(bgr, cv2.COLOR_BGR2RGB)
tensor = blob(rgb, return_seg=False)
dwdh = torch.asarray(dwdh * 2, dtype=torch.float32, device=device)
tensor = torch.asarray(tensor, device=device)
# inference
data = Engine(tensor)
bboxes, scores, labels = det_postprocess(data)
bboxes -= dwdh
bboxes /= ratio
for (bbox, score, label) in zip(bboxes, scores, labels):
bbox = bbox.round().int().tolist()
cls_id = int(label)
cls = CLASSES[cls_id]
color = COLORS[cls]
cv2.rectangle(draw, bbox[:2], bbox[2:], color, 2)
cv2.putText(draw,
f'{cls}:{score:.3f}', (bbox[0], bbox[1] - 2),
cv2.FONT_HERSHEY_SIMPLEX,
0.75, [225, 255, 255],
thickness=2)
if args.show:
cv2.imshow('result', draw)
cv2.waitKey(0)
else:
cv2.imwrite(str(save_image), draw)
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser()
parser.add_argument('--engine', type=str, help='Engine file')
parser.add_argument('--imgs', type=str, help='Images file')
parser.add_argument('--show',
action='store_true',
help='Show the detection results')
parser.add_argument('--out-dir',
type=str,
default='./output',
help='Path to output file')
parser.add_argument('--device',
type=str,
default='cuda:0',
help='TensorRT infer device')
args = parser.parse_args()
return args
if __name__ == '__main__':
args = parse_args()
main(args)