def evolve(image_class, pop_class, pairs, mutation_probability):
"""
:param image_class: (class object)
:param pop_class: (class object)
:param pairs: (numpy array with dimensions (n_pairs, 2, 2, 2)) pairs of lines
:param mutation_probability: (float)
:return: (numpy array) loss functions for the population
"""
pop_class.exterminate()
slopes = map(image_class.slope, pairs)
loss_func = map(lambda s: loss(np.array(s[0]), np.array(s[1])), slopes)
pop_class.add_parents(pairs, loss_func, 200)
pop_class.add_children(image_class.mutation, p_mutate=mutation_probability)
pop_slopes = map(image_class.slope, pop_class.population)
pop_loss = map(lambda s: loss(np.array(s[0]), np.array(s[1])), pop_slopes)
return pop_loss
def main():
# initialization
pic = CorrectImage()
pic.add_path('data')
pic.add_image('initial.png')
pic.hough_transform(vary=False, plot=False) # set vary True to change edge filters, plot True for visualizations
pair = pic.line_pair(16)
slopes = map(pic.slope, pair)
loss_func = map(lambda s: loss(np.array(s[0]), np.array(s[1])), slopes)
# print pair
print loss_func
print health(loss_func, metric='arc_length'), '\n'
pop = Population()
pop.add_parents(pair, loss_func, 4)
pop.add_children(pic.mutation, p_mutate=0.01)