def run_analysis():
    population_size = np.arange(start=25, stop=35, step=5)
    pixels_percentage_to_change = np.arange(start=0.4, stop=0.5, step=0.1)
    max_generation_count = [100]
    population_percentage_to_keep = np.arange(start=0.1,stop=0.3, step=0.1)
    mutation_prob = np.arange(start=0.4, stop=0.6, step=0.2)
    crossover_prob = np.arange(start=0.7, stop=0.8, step=0.1)

    all_params_combination = itertools.product(population_size,
                                               pixels_percentage_to_change,
                                               max_generation_count,
                                               population_percentage_to_keep,
                                               mutation_prob,
                                               crossover_prob)

    fake_img_generator = FakeImgGenerator(Utils.get_test_image_path(IMG_NAME),
                                          P_MAX,
                                          P_MIN,
                                          FAKE_CLASS_PROB_TO_GET)

    results = []
    output_dir = Utils.get_new_output_dir()
    for i, c in enumerate(all_params_combination):
        print("Test generation set number: {}".format(i))
        generation_result = fake_img_generator.run(population_size=c[0],
                                                   pixels_percentage_to_change=c[1],
                                                   max_generations_count=c[2],
                                                   population_percentage_to_keep=c[3],
                                                   mutation_prob=c[4],
                                                   crossover_prob=c[5])
        results.append(generation_result)
        result_path = Utils.create_child_dir(basepath=output_dir, child_dir="result_{}".format(str(i)))
        print("Result probability: {}".format(generation_result.get_last_probability()))
        generation_result.save(output_dir=result_path)

    _save_results_comparison(results, output_dir)
Exemplo n.º 2
0
from src.FakeImgGenerator import FakeImgGenerator
from src.Utils import Utils
from Config import *

if __name__ == '__main__':
    img_name = IMG_NAME
    img_path = Utils.get_test_image_path(img_name)

    p_max = P_MAX
    p_min = P_MIN
    fake_class_prob_to_get = FAKE_CLASS_PROB_TO_GET
    fake_img_generator = FakeImgGenerator(img_path, p_max, p_min,
                                          fake_class_prob_to_get)

    population_size = 30
    pixels_percentage_to_change = 0.4
    max_generations_count = 100
    population_percentage_to_keep = 0.1
    mutation_prob = 0.6
    crossover_prob = 0.7
    result = fake_img_generator.run(population_size,
                                    pixels_percentage_to_change,
                                    max_generations_count,
                                    population_percentage_to_keep,
                                    mutation_prob, crossover_prob)
    output_dir = Utils.get_new_output_dir()
    result.save(output_dir)