ransac.py

import random

def run_ransac(data, estimate, is_inlier, sample_size, goal_inliers, max_iterations, stop_at_goal=True, random_seed=None):
    best_ic = 0
    best_model = None
    random.seed(random_seed)
    # random.sample cannot deal with "data" being a numpy array
    data = list(data)
    for i in range(max_iterations):
        s = random.sample(data, int(sample_size))
        m = estimate(s)
        ic = 0
        for j in range(len(data)):
            if is_inlier(m, data[j]):
                ic += 1

        print(s)
        print('estimate:', m,)
        print('# inliers:', ic)

        if ic > best_ic:
            best_ic = ic
            best_model = m
            if ic > goal_inliers and stop_at_goal:
                break
    print('took iterations:', i+1, 'best model:', best_model, 'explains:', best_ic)
    return best_model, best_ic