Meta HB Toolkit
Project description
metahb
metahb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-hb
pip install meta-hb
3、目标检测示例(参考detection_demo.py代码)
import platform, cv2
import metahb as mh
Detection = mh.DetectionHB
y = Detection(model_path='models/yolov8m.onnx' if platform.machine() == 'x86_64' else 'models/yolov8m.bin',
input_width=640,
input_height=480,
confidence_thresh=0.5,
nms_thresh=0.3,
class_names=classnames,
device_id=0)
img = cv2.imread('models/bus.jpg')
_dets, _scores, _labels = y.predict(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), use_preprocess=True)
# 显示
y.show(img, _dets, _scores, _labels)
cv2.imwrite("models/bus.png", img)
4、实例分割示例(参考segment_demo.py代码)
import platform, cv2
import metahb as hb
Segment = mr.SegmentHB
y = Segment(model_path='models/yolov8m-seg.onnx' if platform.machine() == 'x86_64' else 'models/yolov8m-seg.bin',
input_width=640,
input_height=480,
confidence_thresh=0.5,
nms_thresh=0.3,
class_names=classnames,
device_id=0)
img = cv2.imread('models/bus.jpg')
_dets, _scores, _labels = y.predict(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), use_preprocess=True)
# 显示
y.show(img, _dets, _scores, _labels)
cv2.imwrite("models/bus.png", img)
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