brute_force_matching.py

import os
from cv2 import cv2
from algorithm.imageprocessing import create_salamander_image
import glob

min_good_match = 15
match_dist = 0.75
def match_single_image(input_image, match_image) -> bool:
    bf = cv2.BFMatcher()
    input_salamander = create_salamander_image(input_image)
    match_salamander = create_salamander_image(match_image)

    match = bf.knnMatch(input_salamander.descriptors, match_salamander.descriptors, k=2)

    goodmatch = []
    for m, n in match:
        if m.distance < match_dist * n.distance:
            goodmatch.append([m])
    print("good matches", len(goodmatch))
    if len(goodmatch) > min_good_match:
        return True
    return False

def match_file_structure(input_image: str, match_directory: str) -> int:
    # check if input path is valid:
    if os.path.isfile(input_image):
        for folder in os.listdir(match_directory):
            name_list = glob.glob(os.path.join(match_directory, folder, "*_str.*"))
            current_dir = os.path.join(match_directory, folder)
            for filename in name_list:
                res = match_single_image(input_image, filename)
                if res:
                    return int(folder)
        return -1
    else:
        return None