mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-06 09:07:10 +08:00
77cb9db6da
* [cmake] add faiss.cmake -> pp-shituv2 * [PP-ShiTuV2] Support PP-ShituV2-Det model * [PP-ShiTuV2] Support PP-ShiTuV2-Det model * [PP-ShiTuV2] Add PPShiTuV2Recognizer c++&python support * [PP-ShiTuV2] Add PPShiTuV2Recognizer c++&python support * [Bug Fix] fix ppshitu_pybind error * [benchmark] Add ppshituv2-det c++ benchmark * [examples] Add PP-ShiTuV2 det & rec examples * [vision] Update vision classification result * [Bug Fix] fix trt shapes setting errors
97 lines
3.0 KiB
Python
Executable File
97 lines
3.0 KiB
Python
Executable File
import fastdeploy as fd
|
||
import cv2
|
||
import os
|
||
|
||
|
||
def parse_arguments():
|
||
import argparse
|
||
import ast
|
||
parser = argparse.ArgumentParser()
|
||
parser.add_argument(
|
||
"--model", required=True, help="Path of PP-ShiTuV2 detector model.")
|
||
parser.add_argument(
|
||
"--image", type=str, 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' or 'ipu' or 'kunlunxin' or 'ascend' ."
|
||
)
|
||
parser.add_argument(
|
||
"--device_id",
|
||
type=int,
|
||
default=0,
|
||
help="Define which GPU card used to run model.")
|
||
parser.add_argument(
|
||
"--backend",
|
||
type=str,
|
||
default="default",
|
||
help="Type of inference backend, support ort/trt/paddle/openvino, default 'openvino' for cpu, 'tensorrt' for gpu"
|
||
)
|
||
return parser.parse_args()
|
||
|
||
|
||
def build_option(args):
|
||
|
||
option = fd.RuntimeOption()
|
||
|
||
if args.device.lower() == "gpu":
|
||
option.use_gpu(args.device_id)
|
||
|
||
if args.backend.lower() == "trt":
|
||
assert args.device.lower(
|
||
) == "gpu", "TensorRT backend require inference on device GPU."
|
||
option.use_trt_backend()
|
||
|
||
elif args.backend.lower() == "pptrt":
|
||
assert args.device.lower(
|
||
) == "gpu", "Paddle-TensorRT backend require inference on device GPU."
|
||
option.use_paddle_infer_backend()
|
||
option.paddle_infer_option.enable_trt = True
|
||
option.paddle_infer_option.collect_trt_shape = True
|
||
option.trt_option.set_shape("image", [1, 3, 640, 640],
|
||
[1, 3, 640, 640], [1, 3, 640, 640])
|
||
option.trt_option.set_shape("scale_factor", [1, 2], [1, 2], [1, 2])
|
||
option.trt_option.set_shape("im_shape", [1, 2], [1, 2], [1, 2])
|
||
|
||
elif args.backend.lower() == "ort":
|
||
option.use_ort_backend()
|
||
|
||
elif args.backend.lower() == "paddle":
|
||
option.use_paddle_infer_backend()
|
||
|
||
elif args.backend.lower() == "openvino":
|
||
assert args.device.lower(
|
||
) == "cpu", "OpenVINO backend require inference on device CPU."
|
||
option.use_openvino_backend()
|
||
|
||
elif args.backend.lower() == "pplite":
|
||
assert args.device.lower(
|
||
) == "cpu", "Paddle Lite backend require inference on device CPU."
|
||
option.use_lite_backend()
|
||
|
||
return option
|
||
|
||
|
||
args = parse_arguments()
|
||
|
||
# 配置runtime，加载模型
|
||
runtime_option = build_option(args)
|
||
|
||
model_file = os.path.join(args.model, "inference.pdmodel")
|
||
params_file = os.path.join(args.model, "inference.pdiparams")
|
||
config_file = os.path.join(args.model, "infer_cfg.yml")
|
||
model = fd.vision.classification.PPShiTuV2Detector(
|
||
model_file, params_file, config_file, runtime_option=runtime_option)
|
||
|
||
# 预测主体检测结果
|
||
im = cv2.imread(args.image)
|
||
result = model.predict(im)
|
||
|
||
# 预测结果可视化
|
||
vis_im = fd.vision.vis_detection(im, result, score_threshold=0.5)
|
||
cv2.imwrite("visualized_result.jpg", vis_im)
|
||
print("Visualized result save in ./visualized_result.jpg")
|
||
|
||
print(result)
|