main.py

__author__ = 'fucus'
import logging
from data_tool import load_training_validation_data
from model.models import RandomForestClassification
from feature.hog import flatten
import data_tool

logger = logging.getLogger("main")

level = logging.INFO
log_filename = '%s.log' % __file__
format = '%(asctime)-12s[%(levelname)s] %(message)s'
datefmt ='%Y-%m-%d %H:%M:%S'
logging.basicConfig(level=level,
                    format=format,
                    filename=log_filename,
                    datefmt=datefmt)

if __name__ == '__main__':
    view_list = ["%03d" % x for x in range(0, 181, 18)]
    train_dir = ["nm-%02d" % i for i in range(1, 5)]
    val_dir = ["cl-01", "cl-02"]

    # "{train_view}-{val_view}" as key, "090-072" means 090 as train data, 072 as validation data
    correct_tbl = {}

    for train_view in view_list:
        val_view = train_view
        training_x, training_y, validation_x, validation_y = load_training_validation_data(train_view=train_view
                                                                                           , val_view=val_view
                                                                                           , train_dir=train_dir
                                                                                           , val_dir=val_dir)
        training_feature_x = [flatten(x) for x in training_x]
        validation_feature_x = [flatten(x) for x in validation_x]

        model = RandomForestClassification()
        model.fit(x_train=training_feature_x, y_train=training_y)
        predict_y = model.predict(validation_feature_x)
        correct_count = sum(predict_y == validation_y)
        correct_percent = correct_count * 1.0 / len(predict_y)
        correct_tbl["%s-%s" % (train_view, val_view)] = correct_percent

        logger.info("train by %s, val by %s, precision %d/%d %.3f" % (train_view, val_view, correct_count, len(predict_y), correct_percent))

    data_tool.output_result(view_list, correct_tbl)