Metadata-Version: 2.0
Name: fpga4p
Version: 1.2
Summary: Python package / GNU Linux terminal utility for porting machine learning algorithms to FPGA.
Home-page: UNKNOWN
Author: Dmitriy Mandjiev, Pavel Ivanov
Author-email: fmnpro19@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Requires-Dist: Click
Requires-Dist: singleton-decorator
Requires-Dist: pyserial
Requires-Dist: colorama
Requires-Dist: pandas
Requires-Dist: setuptools


MANUAL:

Training opportunities:

    1) Training tasks executes in parallel processes.

    2) Each training task generates: ".sv" file for FPGA, ".wd" file
     and ".tar" archive with model data for prospective
         classification task.


Training specialities:

    1) "training_file.csv" must contain classes in the first column.

    2) "training_file.csv" must not contain a column head.

    3) The character - separator of "training_file.csv" must be ",".

    4) You can check available training algorithms with option "--info".


Classification opportunities:

    1) Classification tasks might be executed parallel on several FPGAs.

    2) Several classification tasks, addressed to FPGA, execute consistently.

    3) Each classification task generates ".csv" file with predicted answers.


Classification specialities:

    1) "classification_file.csv" must not contain a column head.

    2) The character - separator of "training_file.csv" must be ",".

    3) The "word_dict.wd" might match to firmware of FPGA.

    4) You can check available training algorithms and USB serial ports
        with option "--info".

Examples:

     1) This example starts the training task:

        $ fpga4p --trn "training.csv,train_nbc"

    2) This example starts the classification task:

        $ fpga4p --cls "class.csv,classify_nbc,training.wd,/dev/ttyUSB0"

    3) This example prints available modules for training and
        classification, as well as available serial USB ports:


        $ fpga4p --info


