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)