AzurLaneAutoScript/dev_tools/relative_record_gif.py

import os

import imageio
from PIL import Image

import module.config.server as server

server.server = 'cn'  # Don't need to edit, it's used to avoid error.

from dev_tools.relative_record import FOLDER, NAME
from module.base.utils import *
from module.map_detection.utils import *

"""
Usage:
    See relative_record.py

Arguments:
    FOLDER:     Save folder from relative_record.
    NAME:       Siren name from relative_record.
                Save gif file to <FOLDER>/TEMPLATE_SIREN_<NAME>.gif
    AREA:       Area to crop, such as (32, 32, 54, 52).
                Choose an area where things don't rotate too much.
    THRESHOLD:  If the similarity between a template and existing templates greater than THRESHOLD,
                this template will be dropped.
                Threshold in real detection is 0.85, for higher accuracy, threshold here should higher than 0.85.
"""
# FOLDER = ''
# NAME = 'Deutschland'
AREA = (32, 32, 54, 52)
THRESHOLD = 0.92

if __name__ == '__main__':
    images = [np.array(Image.open(os.path.join(FOLDER, NAME, file))) for file in os.listdir(os.path.join(FOLDER, NAME))
              if file[-4:] == '.png']
    templates = [crop(images[0], area=AREA)]


    def match(im):
        max_sim = 0
        max_loca = (0, 0)
        for template in templates:
            res = cv2.matchTemplate(im, template, cv2.TM_CCOEFF_NORMED)
            _, sim, _, loca = cv2.minMaxLoc(res)
            if sim > max_sim:
                max_sim = sim
                max_loca = loca

        return max_sim, max_loca


    for n, image in enumerate(images):
        sim, loca = match(image)
        if sim > THRESHOLD:
            continue
        print(f'New template: {n}')
        templates.append(crop(image, area=area_offset(AREA, np.subtract(loca, AREA[:2]))))

    imageio.mimsave(os.path.join(FOLDER, f'TEMPLATE_SIREN_{NAME}.gif'), templates, fps=3)