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063da7b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | import cv2
import argparse
from yolov8m import Yolov8M
from utils import draw_detect_res
def parser_args():
parser = argparse.ArgumentParser(description="Run model benchmarks")
parser.add_argument('--target_model',type=str,default='./models/cutoff_yolov8m_qcs8550_fp16.qnn236.ctx.bin',help="inference model path")
parser.add_argument('--imgs',type=str,default='./python/bus.jpg',help="Predict images path")
parser.add_argument('--height',type=int,default=640,help="run backend")
parser.add_argument('--weight',type=int,default=640,help="run backend")
parser.add_argument('--cls_num',type=int,default=80,help="run backend")
parser.add_argument('--invoke_nums',type=int,default=10,help="Inference nums")
parser.add_argument('--model_type',type=str,default='QNN',help="run backend")
args = parser.parse_args()
return args
if __name__ == "__main__":
args = parser_args()
height = args.height
weight = args.weight
model = Yolov8M(args.target_model, args.weight, args.height, args.cls_num)
frame = cv2.imread(args.imgs)
out_boxes= model(frame,args.invoke_nums)
print(f"=================== \n Detect {len(out_boxes)} targets.")
result = draw_detect_res(frame, out_boxes)
cv2.imwrite("./python/result.jpg", result) |