mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-11-01 04:12:58 +08:00
58d63f3e90
* Add Huawei Ascend NPU deploy through PaddleLite CANN * Add NNAdapter interface for paddlelite * Modify Huawei Ascend Cmake * Update way for compiling Huawei Ascend NPU deployment * remove UseLiteBackend in UseCANN * Support compile python whlee * Change names of nnadapter API * Add nnadapter pybind and remove useless API * Support Python deployment on Huawei Ascend NPU * Add models suppor for ascend * Add PPOCR rec reszie for ascend * fix conflict for ascend * Rename CANN to Ascend * Rename CANN to Ascend * Improve ascend * fix ascend bug * improve ascend docs * improve ascend docs * improve ascend docs * Improve Ascend * Improve Ascend * Move ascend python demo * Imporve ascend * Improve ascend * Improve ascend * Improve ascend * Improve ascend * Imporve ascend * Imporve ascend * Improve ascend * acc eval script * acc eval * remove acc_eval from branch huawei * Add detection and segmentation examples for Ascend deployment * Add detection and segmentation examples for Ascend deployment * Add PPOCR example for ascend deploy * Imporve paddle lite compiliation * Add FlyCV doc * Add FlyCV doc * Add FlyCV doc * Imporve Ascend docs * Imporve Ascend docs
58 lines
1.4 KiB
Python
Executable File
58 lines
1.4 KiB
Python
Executable File
import fastdeploy as fd
|
||
import cv2
|
||
import os
|
||
from fastdeploy import ModelFormat
|
||
|
||
|
||
def parse_arguments():
|
||
import argparse
|
||
import ast
|
||
parser = argparse.ArgumentParser()
|
||
parser.add_argument(
|
||
"--model", required=True, help="Path of yolov6 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', 'kunlunxin' or 'gpu'.")
|
||
return parser.parse_args()
|
||
|
||
|
||
def build_option(args):
|
||
option = fd.RuntimeOption()
|
||
if args.device.lower() == "gpu":
|
||
option.use_gpu(0)
|
||
|
||
if args.device.lower() == "kunlunxin":
|
||
option.use_kunlunxin()
|
||
|
||
if args.device.lower() == "ascend":
|
||
option.use_ascend()
|
||
|
||
return option
|
||
|
||
|
||
args = parse_arguments()
|
||
|
||
model_file = os.path.join(args.model, "model.pdmodel")
|
||
params_file = os.path.join(args.model, "model.pdiparams")
|
||
# 配置runtime，加载模型
|
||
runtime_option = build_option(args)
|
||
model = fd.vision.detection.YOLOv6(
|
||
model_file,
|
||
params_file,
|
||
runtime_option=runtime_option,
|
||
model_format=ModelFormat.PADDLE)
|
||
|
||
# 预测图片检测结果
|
||
im = cv2.imread(args.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")
|