mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-31 11:56:44 +08:00
62 lines
1.5 KiB
Python
62 lines
1.5 KiB
Python
import fastdeploy as fd
|
||
import cv2
|
||
|
||
|
||
def parse_arguments():
|
||
import argparse
|
||
import ast
|
||
parser = argparse.ArgumentParser()
|
||
parser.add_argument(
|
||
"--model", default=None, help="Path of scaledyolov4 onnx model.")
|
||
parser.add_argument(
|
||
"--image", default=None, help="Path of test image file.")
|
||
parser.add_argument(
|
||
"--device",
|
||
type=str,
|
||
default='cpu',
|
||
help="Type of inference device, support 'cpu' or 'gpu'.")
|
||
parser.add_argument(
|
||
"--use_trt",
|
||
type=ast.literal_eval,
|
||
default=False,
|
||
help="Wether to use tensorrt.")
|
||
return parser.parse_args()
|
||
|
||
|
||
def build_option(args):
|
||
option = fd.RuntimeOption()
|
||
|
||
if args.device.lower() == "gpu":
|
||
option.use_gpu()
|
||
|
||
if args.use_trt:
|
||
option.use_trt_backend()
|
||
option.set_trt_input_shape("images", [1, 3, 640, 640])
|
||
return option
|
||
|
||
|
||
args = parse_arguments()
|
||
|
||
if args.model is None:
|
||
model = fd.download_model(name='ScaledYOLOv4-P5')
|
||
else:
|
||
model = args.model
|
||
|
||
# 配置runtime，加载模型
|
||
runtime_option = build_option(args)
|
||
model = fd.vision.detection.ScaledYOLOv4(model, runtime_option=runtime_option)
|
||
|
||
# 预测图片检测结果
|
||
if args.image is None:
|
||
image = fd.utils.get_detection_test_image()
|
||
else:
|
||
image = args.image
|
||
im = cv2.imread(image)
|
||
result = model.predict(im)
|
||
print(result)
|
||
|
||
# 预测结果可视化
|
||
vis_im = fd.vision.vis_detection(im, result)
|
||
cv2.imwrite("visualized_result.jpg", vis_im)
|
||
print("Visualized result save in ./visualized_result.jpg")
|