train_scripts

You can also train on Maixhub.com, just upload your datasets and you will get the result(kmodel and usage code)

Train type

• Object classification(Mobilenet V1): judge class of image
• Object detection(YOLO v2): find a recognizable object in the picture

Usage

0. Prepare

• only support Linux
• Prepare environment, use CPU or GPU to train At your fist time train, CPU is recommended, just

pip3 install -r requirements.txt

or use aliyun's source if you are in China

pip3 install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/

• Download nncase and unzip it to tools/ncc/ncc_v0.1, and the executable path is tools/ncc/ncc_v0.1/ncc
• python3 train.py init
• Edit instance/config.py according to your hardware
• Prepare dataset, in the datasets directory has some example datasets, input size if 224x224 or you just fllow maixhub's conduct

1. Object classification (Mobilenet V1)

python3 train.py -t classifier -z datasets/test_classifier_datasets.zip train

or assign datasets directory

python3 train.py -t classifier -d datasets/test_classifier_datasets train

more command seepython3 train.py -h

and you will see output in the out directory, packed as a zip file

2. Object detection (YOLO V2)

python3 train.py -t detector -z datasets/test_detector_xml_format.zip train

more command seepython3 train.py -h

and you will see output in the out directory, packed as a zip file

License

Apache 2.0, see LICENSE