meta-rt 0.1.4

Meta TR Toolkit

metart

metart部署通用框架

1、安装最新版 meta-cv

pip install meta-cv

2、安装最新版 meta-rt

pip install meta-rt

3、目标检测示例（参考detection_demo.py代码）

import platform, cv2
import metart as m

Detection = m.Detection

y = Detection(model_path='models/yolov8m.rt',
              input_width=640,
              input_height=480,
              use_preprocess=True,
              pad=True,
              normal=True,
              swap=(2, 0, 1),
              confidence_thresh=0.5,
              nms_thresh=0.3,
              class_names=classnames,
              device_id=0)

batch_size = 1
img = cv2.imread('models/bus.jpg')
img_list = [img[:, :, ::-1]] * batch_size if batch_size > 1 else img[:, :, ::-1]
_dets, _scores, _labels = y.predict(img_list)

# 显示
y.show(img, _dets[-1], _scores[-1], _labels[-1])
cv2.imwrite("models/bus.png", img)

4、实例分割示例（参考segment_demo.py代码）

import platform, cv2
import metart as m

Segment = m.Segment

y = Segment(model_path='models/yolov8m-seg.rt',
            input_width=640,
            input_height=480,
            use_preprocess=True,
            pad=True,
            normal=True,
            swap=(2, 0, 1),
            confidence_thresh=0.5,
            nms_thresh=0.3,
            class_names=classnames,
            device_id=0)

batch_size = 1
img = cv2.imread('models/bus.jpg')
img_list = [img[:, :, ::-1]] * batch_size if batch_size > 1 else img[:, :, ::-1]
_dets, _scores, _labels = y.predict(img_list)

# 显示
y.show(img, _dets[-1], _scores[-1], _labels[-1])
cv2.imwrite("models/bus.png", img)