def test_input():
i = 0
folder_path = './imgs'
if not os.path.exists(folder_path):
os.mkdir(folder_path)
empty_folder(folder_path)
while True:
if keyboard.is_pressed('a'):
test_image_sct(i, folder_path)
i += 1
def start_no_driver():
i = 0
empty_folder('./imgs')
while (True):
image = np.array(sct.grab(coordinates))
image = image[::, 75:615]
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# image = cv2.resize(image, (0, 0), fx=0.5, fy=0.5)
image = processing_img(image)
p = model.predict_classes(
image.reshape(-1, image.shape[0], image.shape[1], 1))
print(p)
if (p):
print(i)
cv2.imwrite('./imgs/frame_{0}.jpg'.format(i), image)
i += 1
print("aa", p)
pyautogui.press('space')
time.sleep(2)
def start_no_driver():
i = 0
empty_folder('./imgs')
pressed = False
print('Start')
while (True):
pressed = False
image = np.array(sct.grab(coordinates))
image = image[::, 75:615]
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
image = processing_img(image)
# image = cv2.resize(image, dsize=(52, 69), interpolation=cv2.INTER_CUBIC)
p = model_select.predict_classes(
image.reshape(-1, image.shape[0], image.shape[1], 1))
if p[0] == 0 or p[0] == 1 or p[0] == 4:
#print("Not Zero")
pred = 0
while (pred != 1):
image = np.array(sct.grab(coordinates))
image = image[::, 75:615]
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
image = processing_img(image)
image = cv2.resize(image,
dsize=(52, 69),
interpolation=cv2.INTER_CUBIC)
image = np.stack((image, ) * 3, -1)
pred = model_first_level.predict_classes(
image.reshape(-1, image.shape[0], image.shape[1], 3))
if pred == 0:
pressed = False
if (pred) and not pressed:
print("select: ", p)
pyautogui.press('space')
pressed = True
cv2.imwrite('./imgs/frame_{0}.jpg'.format(i), image)
i += 1
time.sleep(1.2)
#cv2.imwrite('./imgs/frame_{0}.jpg'.format(i), image)
# print(i)
#cv2.imwrite('./imgs/frame_{0}.jpg'.format(i), image)
#i += 1
# print("aa", p)
# pyautogui.press('space')
# time.sleep(2)
#keyboard.write('space', delay=0)
else:
#print("Not Zero")
image = np.array(sct.grab(coordinates))
image = image[::, 75:615]
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# image = cv2.resize(image, (0, 0), fx=0.5, fy=0.5)
image = processing_img(image)
image = cv2.resize(image,
dsize=(52, 69),
interpolation=cv2.INTER_CUBIC)
pred = model.predict_classes(
image.reshape(-1, image.shape[0], image.shape[1], 1))
if pred == 0:
pressed = False
if (pred) and not pressed:
print("select: ", p)
pyautogui.press('space')
cv2.imwrite('./imgs/frame_{0}.jpg'.format(i), image)
i += 1
pressed = True
time.sleep(1.2)
import os
from capture_game_data import empty_folder
import cv2
import numpy as np
import shutil
#folder_to_read = '../images_not_basic'
folder_to_read = '../images12'
files = os.listdir(folder_to_read)
total = len(files) - 1
print(total)
#folder_to_create = './images_not_basic_smaller'
folder_to_create = folder_to_read[1:] + '_smaller'
print(folder_to_create)
empty_folder(folder_to_create)
shutil.copy(folder_to_read + '/actions.csv', folder_to_create + '/actions.csv')
for i in range(total):
im = cv2.imread('{1}/frame_{0}.jpg'.format(i, folder_to_read))
im = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
im = cv2.resize(im, dsize=(52, 69), interpolation=cv2.INTER_CUBIC)
cv2.imwrite(folder_to_create + '/frame_{0}.jpg'.format(i), im)
def start_no_driver2():
i = 0
empty_folder('./imgs')
print('Start')
while (True):
pressed = False
image = np.array(sct.grab(coordinates))
image = image[::, 75:615]
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
image = processing_img(image)
p = model_select.predict_classes(
image.reshape(-1, image.shape[0], image.shape[1], 1))
if p[0] == 0 or p[0] == 1 or p[0] == 4:
image = np.array(sct.grab(coordinates))
image = image[::, 75:615]
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
image = processing_smaller(image)
pred = model_first_level.predict_classes(
image.reshape(-1, image.shape[0], image.shape[1], 3))
if pred > 0.5:
print("select: ", p)
pyautogui.press('space')
pressed = True
# cv2.imwrite('./imgs/frame_{0}.jpg'.format(i), image)
i += 1
time.sleep(1.2)
# cv2.imwrite('./imgs/frame_{0}.jpg'.format(i), image)
# pred = 0
# while(pred != 1):
# image = np.array(sct.grab(coordinates))
# image = image[::, 75:615]
# image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
#
# image = processing_smaller(image)
# pred = model_first_level.predict_classes(image.reshape(-1, image.shape[0], image.shape[1], 3))
# if pred == 0:
# pressed = False
# if (pred) and not pressed:
# print("select: ", p)
# pyautogui.press('space')
# pressed = True
# #cv2.imwrite('./imgs/frame_{0}.jpg'.format(i), image)
# i += 1
# time.sleep(1.2)
# #cv2.imwrite('./imgs/frame_{0}.jpg'.format(i), image)
else:
image = np.array(sct.grab(coordinates))
image = image[::, 75:615]
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
image = processing_img(image)
image = cv2.resize(image,
dsize=(52, 69),
interpolation=cv2.INTER_CUBIC)
pred = model.predict_classes(
image.reshape(-1, image.shape[0], image.shape[1], 1))
if pred == 0:
pressed = False
if (pred) and not pressed:
print("select: ", p)
pyautogui.press('space')
cv2.imwrite('./imgs/frame_{0}.jpg'.format(i), image)
i += 1
time.sleep(1.2)