Releases: FastSense/nnio
Releases · FastSense/nnio
Changed Detection boxes and updated file caching
Changed nnio.DetectionBox class:
- Attributes are now named
x_min, y_min, x_max, y_max x_minandx_maxare for width axis andy_min,y_maxare for height axis, like in PASCAL VOC.
Changed file caching. Now files from different urls will not conflict when they have the same name.
Added person-reid model
New models for person re-identification:
nnio.zoo.onnx.reid.OSNetnnio.zoo.openvino.reid.OSNetnnio.zoo.edgetpu.reid.OSNet
New class: nnio.utils.HumanDataBase for using with person re-id models.
Made Segmentation model lighter
nnio.zoo.edgetpu.DeepLabV3 model is now the light version.
Small changes for comfortable usage
- Now python's auto completion will not show non-relevant imports, especially for
nnio.zoo - Cache is now saved in
/home/user/.cache/nnio/0.2/. Earlier it was saved to.../nnio/0.2.1/. Now small updates will not affect saved models. - Added
__eq__operator fornnio.Preprocessing.
Convenient device naming and myriad's temperature measuring
More convenient device naming
- Names for all devices are written in the same form:
CPU,GPU,MYRIAD,TPU - When multiple myriads or TPU's are available, user can choose between them as:
MYRIAD:0,MYRIAD:1,TPU:0,TPU:1, ...
Measuring myriad temperature
- Temperature will be returned from the model call if
return_infoflag is used:
output, info = model(image_prepared, return_info=True) - Temperature of each myriad can be logged to
/home/$USER/.telemetryafter each model call.
To enable this:
nnio.utils.enable_logging_temperature(True)
Added support for openvino models
New ready models:
- nnio.zoo.edgetpu.segmentation.DeepLabV3
- nnio.zoo.onnx.classification.MobileNetV2
- nnio.zoo.openvino.detection.SSDMobileNetV2
Stable version with few models
Backends available:
- nnio.EdgeTPUModel
- nnio.OpenVINOModel
- nnio.ONNXModel
Ready models available:
- nnio.zoo.edgetpu.classification.MobileNet
- nnio.zoo.edgetpu.detection.SSDMobileNet
- nnio.zoo.edgetpu.detection.SSDMobileNetFace
- nnio.zoo.onnx.detection.SSDMobileNetV1