mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-06 00:57:33 +08:00
65 lines
1.7 KiB
Python
65 lines
1.7 KiB
Python
import fastdeploy as fd
|
||
import cv2
|
||
|
||
|
||
def parse_arguments():
|
||
import argparse
|
||
import ast
|
||
parser = argparse.ArgumentParser()
|
||
parser.add_argument(
|
||
"--model", required=True, help="Path of modnet onnx model.")
|
||
parser.add_argument(
|
||
"--image", required=True, 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(
|
||
"--bg",
|
||
type=str,
|
||
required=True,
|
||
default=None,
|
||
help="Path of test background image file.")
|
||
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("input", [1, 3, 256, 256])
|
||
return option
|
||
|
||
|
||
args = parse_arguments()
|
||
|
||
# 配置runtime，加载模型
|
||
runtime_option = build_option(args)
|
||
model = fd.vision.matting.MODNet(args.model, runtime_option=runtime_option)
|
||
|
||
#设置推理size, 必须和模型文件一致
|
||
model.size = (256, 256)
|
||
# 预测图片抠图结果
|
||
im = cv2.imread(args.image)
|
||
bg = cv2.imread(args.bg)
|
||
result = model.predict(im)
|
||
print(result)
|
||
# 可视化结果
|
||
vis_im = fd.vision.vis_matting_alpha(im, result)
|
||
vis_im_with_bg = fd.vision.swap_background(im, bg, result)
|
||
cv2.imwrite("visualized_result_fg.png", vis_im)
|
||
cv2.imwrite("visualized_result_replaced_bg.jpg", vis_im_with_bg)
|
||
print(
|
||
"Visualized result save in ./visualized_result_replaced_bg.jpg and ./visualized_result_fg.jpg"
|
||
)
|