import cv2 #import numpy as np #import time game_modes = { 0: "0 Intro", 1: "1 Game menu", 2: "2 Level intro", 3: "3 gameplay", 4: "4 Credits" } dir_name = 'G:\Python\KMold\screenshots\categorized' extension = '.jpg' pathList = [] pathList = findFilesInFolder(dir_name, pathList, extension, True) sample = random.choice(pathList) screenshot = cv2.imread(sample, cv2.IMREAD_GRAYSCALE) if len(screenshot.shape) == 3: #check if the image is color screenshot = cv2.cvtColor(screenshot, cv2.COLOR_RGB2GRAY) screenshot = cv2.resize(screenshot, (image_width, image_height), interpolation=cv2.INTER_AREA) screenshot = screenshot / 255. screenshot = screenshot.reshape( (1, screenshot.shape[0], screenshot.shape[1], 1)) #add dimension to transform array into a batch start_time = time.time() classifier_output = classifier.predict(screenshot) end_time = time.time() classifier_output = classifier_output[0] #decrease dimensions
score_imgs = [] for i in range(1,7): score_imgs.append(screenshot[y:y+height, x-width:x]) # X and Y are flipped x = x - width lives = screenshot[y:y+height, lives_x_start-width:lives_x_start] return score_imgs, lives #%% DIGIT SCRAPPER input_dir_name = os.path.join(os.getcwd(),'screenshots') output_dir_name = os.path.join(input_dir_name,'digits') extension = ".jpg" pathList = [] pathList = findFilesInFolder(input_dir_name, pathList, extension, False) start_file_num = 1 file_num = start_file_num for image_path in pathList: img = cv2.imread(image_path) score_imgs, lives = get_score(img) digit_imgs = score_imgs + [lives] for img in digit_imgs: file_num_str = f'{file_num:05d}' file_name = file_num_str + '.jpg' file_name_path = os.path.join(output_dir_name, file_name) cv2.imwrite(file_name_path, img)