def qq_captcha_pass():
big_image = cv.imread(GlobalParam.get_test_image_path() +
'test_qq_mail_big.png')
small_image = cv.imread(GlobalParam.get_test_image_path() +
'test_qq_mail_small.png')
cv.imshow('1', small_image)
cv.waitKey(0)
def qq_login(qq_driver, user_name, user_pass):
element = find_element_by_id(qq_driver, 'qqLoginTab')
element.click()
qq_driver.switch_to.frame('login_frame')
element = find_element_by_id(qq_driver, 'u')
element.click()
element.send_keys(user_name)
element = find_element_by_id(qq_driver, 'p')
element.click()
element.send_keys(user_pass)
element = find_element_by_id(qq_driver, 'login_button')
element.click()
wait_for_frame_and_switch_to_frame(qq_driver, 'tcaptcha_iframe')
img_element = find_element_by_id(qq_driver, 'slideBg')
wait_for_element_appeared(qq_driver, img_element)
big = img_element.get_attribute('src')
request_download_file_by_url(
big,
GlobalParam.get_test_image_path() + 'test_qq_mail_big.png')
img_element = find_element_by_id(qq_driver, 'slideBlock')
wait_for_element_appeared(qq_driver, img_element)
small = img_element.get_attribute('src')
request_download_file_by_url(
small,
GlobalParam.get_test_image_path() + 'test_qq_mail_small.png')
def fetch_housing_data(housing_url=HOUSING_URL, housing_path=GlobalParam.get_ml_ch2_housing_data()):
if not os.path.isdir(housing_path):
os.makedirs(housing_path)
print(GlobalParam.get_ml_ch2_housing_data())
tgz_path = os.path.join(housing_path, "housing.tgz")
request.urlretrieve(housing_url, tgz_path)
housing_tgz = tarfile.open(tgz_path)
housing_tgz.extractall(path=housing_path)
housing_tgz.close()
def android_aapt_install():
print(
WindowsOsUtil.get_command_output(' '.join(
('adb push', GlobalParam.get_aapt_path(), '/data/local/tmp'))))
print(
WindowsOsUtil.get_command_output(
'adb shell chmod 0755 /data/local/tmp/aapt-arm-pie'))
def android_all_package_list():
msg = filter(
None,
WindowsOsUtil.get_shell_output(['adb', 'shell'],
'pm list packages -3 -f').split('\r\n'))
package_list = []
for ms in msg:
ms = android_aapt_get_app_info(
ms[ms.index('/'):ms.rindex('=')]).replace('\r\n', '').split('\'')
if ms.count('package: name=') == 1:
pkg = ms[ms.index('package: name=') + 1]
else:
pkg = ''
if ms.count('application-label-zh-CN:') == 1:
name = ms[ms.index('application-label-zh-CN:') + 1]
elif ms.count('application-label:') == 1:
name = ms[ms.index('application-label:') + 1]
elif ms.count('application: label=') == 1:
name = ms[ms.index('application: label=') + 1]
else:
name = 'no label name'
if ms.count('launchable-activity: name=') == 1:
launch = ms[ms.index('launchable-activity: name=') + 1]
else:
launch = android_search_app_activity(pkg)
package_list.append(','.join((pkg, name, launch)))
write_string_to_file(
GlobalParam.get_android_apk_list().replace(
'android_apk_list',
android_product_info() + '_android_apk_list'), package_list,
'utf8')
return package_list
def android_search_package_by_name(app_name):
read_list = list(
read_file(
GlobalParam.get_android_apk_list().replace(
'android_apk_list',
android_product_info() + '_android_apk_list'),
'utf8').strip('][').replace('\'', '').split(', '))
for rl in read_list:
if rl.__contains__(app_name):
return rl.split(',')[0], rl.split(',')[2]
def split_gif_to_images(gif_path):
image_object = Image.open(gif_path)
if image_object.is_animated:
for frame in range(0, image_object.n_frames):
image_object.seek(frame)
image_object.save(fp=GlobalParam.get_gif_import() +
str(frame) + '.png',
format='PNG')
# fp_out = GlobalParam.get_gif_export() + 'out.gif'
# split_gif_to_images(fp_out)
# fp_in = GlobalParam.get_gif_import()
# fp_out = GlobalParam.get_gif_export() + 'out.gif'
# ImageUtils.combine_images_to_gif(fp_in, 'png', fp_out)
def visualizing_geographical_data(train_set_data):
california_img=mpimg.imread(GlobalParam.get_ml_ch2_housing_image())
visual_housing = train_set_data.copy()
visual_housing.plot(kind="scatter", x="longitude", y="latitude", figsize=(10,7),
s=visual_housing['population']/100, label="Population",
c="median_house_value", cmap=plt.get_cmap("jet"),
colorbar=False, alpha=0.4,)
plt.imshow(california_img, extent=[-124.55, -113.80, 32.45, 42.05], alpha=0.5,
cmap=plt.get_cmap("jet"))
plt.ylabel("Latitude", fontsize=14)
plt.xlabel("Longitude", fontsize=14)
prices = visual_housing["median_house_value"]
tick_values = np.linspace(prices.min(), prices.max(), 11)
cbar = plt.colorbar()
cbar.ax.set_yticklabels(["$%dk"%(round(v/1000)) for v in tick_values], fontsize=14)
cbar.set_label('Median House Value', fontsize=16)
plt.legend(fontsize=16)
plt.show()
from opencv.cvutils import *
from python_common.global_param import GlobalParam
# write video not working now, need resize frame before write video file
play_and_save_Video(GlobalParam.get_video_input(),
GlobalParam.get_video_output(), 1, 1)
# screen record show opencv window and write video file
screen_record(0, 0, 2560, 1600, 'avc1', 'mp4', 10, 0.5)
# screen record not show opencv window and write video file use timeout
screen_record(0, 0, 640, 400, 'avc1', 'mp4', 10, 0.5, 30)
# screen record show opencv window and write video file use screen offset
screen_record(100, 200, 640, 400, 'avc1', 'mp4', 10, 0.5)
from opencv.cvutils import *
from python_common.global_param import GlobalParam
import os
'''
clean characters images when characters folder isn't empty
'''
if len(os.listdir(GlobalParam.get_character_output())) > 0:
for i in os.listdir(GlobalParam.get_character_output()):
os.remove(GlobalParam.get_character_output() + i)
'''
get text area, and write to file
'''
input = cv.imread(GlobalParam.get_image_input(),cv.IMREAD_UNCHANGED)
# showAllContours(input,detectTextAreaFromImage(input), 10, 5)
input =findTextAreaContours(input,detectTextAreaFromImage(input),7,10,0,0,7,12)
cv.imwrite(GlobalParam.get_image_output(),input)
'''
split text area image to single character images, collect all images names and sort by names
'''
getLastWordsContour(GlobalParam.get_image_output(),
GlobalParam.get_character_output(), 50, 50,
GlobalParam.get_sentence_output())
char_image_list=[]
for i in os.listdir(GlobalParam.get_character_output()):
char_image_list.append(int(i.replace('.png', '')))
char_length = len(char_image_list)
for (x, y, w, h) in faces:
center = (x + w // 2, y + h // 2)
face_frame = cv.ellipse(face_frame, center, (w // 2, h // 2), 0, 0, 360, (255, 0, 255), 4)
face_roi = frame_gray[y:y + h, x:x + w]
# -- In each face, detect eyes
eyes = eyes_cascade.detectMultiScale(face_roi)
for (x2, y2, w2, h2) in eyes:
eye_center = (x + x2 + w2 // 2, y + y2 + h2 // 2)
radius = int(round((w2 + h2) * 0.25))
face_frame = cv.circle(face_frame, eye_center, radius, (255, 0, 0), 4)
cv.imshow('Capture - Face detection', face_frame)
face_cascade_name = GlobalParam.get_face_detect_face_xml()
eyes_cascade_name = GlobalParam.get_face_detect_eyes_xml()
face_cascade = cv.CascadeClassifier()
eyes_cascade = cv.CascadeClassifier()
# 1. Load the cascades
if not face_cascade.load(cv.samples.findFile(face_cascade_name)):
print('--(!)Error loading face cascade')
exit(0)
if not eyes_cascade.load(cv.samples.findFile(eyes_cascade_name)):
print('--(!)Error loading eyes cascade')
exit(0)
camera_device = 0
# 2. Read the video stream
from selenium.common.exceptions import NoAlertPresentException
from selenium.common.exceptions import TimeoutException
from file_and_system.file_utils import write_binary_to_file
from file_and_system.windows_os_utils import WindowsOsUtil
from python_common.global_param import GlobalParam
from selenium_test.selenium_utils import *
WindowsOsUtil.kill_process_by_name('MicrosoftWebDriver.exe')
driver = init_driver('edge', GlobalParam.get_edge_driver_path())
open_browser_single_tab(driver, 'https://www.12306.cn/index/')
# wait dom return complete state
wait_for_page_full_loaded(driver)
loading_element = find_element_by_xpath(driver, '//div[@id="page-loading"]')
wait_for_element_disappeared(driver, loading_element)
try:
wait_for_element_to_be_clickable(driver, '//a[text()="登录"]')
wait_for_page_full_loaded(driver)
wait_for_element_to_be_clickable(driver, '//a[text()="账号登录"]')
# get captcha picture
img_text = find_element_by_xpath(driver,
'//img[@id="J-loginImg"]').get_attribute(
'src')[len('data:image/jpg;base64,'):]
write_binary_to_file(GlobalParam.get_image_input(), img_text)
find_element_by_xpath(driver,
'//input[@id="J-userName"]').send_keys('username')
find_element_by_xpath(driver,
'//input[@id="J-password"]').send_keys('password')
def sort_by_target(mnist):
reorder_train = np.array(
sorted([(target, i)
for i, target in enumerate(mnist.target[:60000])]))[:, 1]
reorder_test = np.array(
sorted([(target, i)
for i, target in enumerate(mnist.target[60000:])]))[:, 1]
mnist.data[:60000] = mnist.data[reorder_train]
mnist.target[:60000] = mnist.target[reorder_train]
mnist.data[60000:] = mnist.data[reorder_test + 60000]
mnist.target[60000:] = mnist.target[reorder_test + 60000]
mnist = fetch_openml('mnist_784',
data_home=GlobalParam.get_ml_ch3_sklearn_data_home(),
version=1,
cache=True)
mnist.target = mnist.target.astype(np.int8)
sort_by_target(mnist)
X, y = mnist["data"], mnist["target"]
X_train, X_test, y_train, y_test = X[:60000], X[60000:], y[:60000], y[60000:]
shuffle_index = np.random.permutation(60000)
X_train, y_train = X_train[shuffle_index], y_train[shuffle_index]
y_train_5 = (y_train == 5)
y_test_5 = (y_test == 5)
sgd_clf = SGDClassifier(max_iter=5, tol=-np.infty, random_state=42)
sgd_clf.fit(X_train, y_train_5)
some_digit = X[36000]
# y_train_pred = cross_val_predict(sgd_clf, X_train, y_train_5, cv=3)
from file_and_system.windows_os_utils import WindowsOsUtil
from selenium_test.selenium_utils import init_driver, open_browser_single_tab
from python_common.global_param import GlobalParam
WindowsOsUtil.kill_process_by_name('MicrosoftWebDriver.exe')
WindowsOsUtil.kill_process_by_name('chromedriver.exe')
WindowsOsUtil.kill_process_by_name('IEDriverServer.exe')
chrome_driver = init_driver('chrome', GlobalParam.get_chrome_driver_path())
open_browser_single_tab(chrome_driver,'https://www.baidu.com')
chrome_driver.quit()
edge_driver = init_driver('edge', GlobalParam.get_edge_driver_path())
open_browser_single_tab(edge_driver,'https://www.baidu.com')
edge_driver.quit()
ie_driver = init_driver('ie', GlobalParam.get_ie_driver_path())
open_browser_single_tab(ie_driver,'https://www.baidu.com')
ie_driver.quit()
# create table
create_table_sql = '''
CREATE TABLE movie
(
id INT PRIMARY KEY NOT NULL,
name VARCHAR(100) NOT NULL,
chnname VARCHAR(50),
main_cast VARCHAR(50),
year VARCHAR(10) NOT NULL,
region VARCHAR(20) NOT NULL,
type VARCHAR(20),
viewed VARCHAR(5) NOT NULL,
want_to_review VARCHAR(5) NOT NULL
);
'''
maria_connection = connect_to_databases(GlobalParam.get_mariadb_url(),
GlobalParam.get_mariadb_user(),
GlobalParam.get_mariadb_password())
execute_sql(maria_connection, create_table_sql, False)
maria_connection.close()
postgresql_connection = connect_to_databases(GlobalParam.get_pgsql_url(),
GlobalParam.get_pgsql_user(),
GlobalParam.get_pgsql_password())
execute_sql(postgresql_connection, create_table_sql, False)
postgresql_connection.close()
# read excel sheet datasets then insert into database table
insert_many_sql = '''
INSERT INTO movie (id, name, chnname, main_cast, year, region, type, viewed, want_to_review)
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s)
'''
from selenium_test.selenium_utils import *
from file_and_system.windows_os_utils import WindowsOsUtil
from python_common.global_param import GlobalParam
import time
WindowsOsUtil.kill_process_by_name('MicrosoftWebDriver.exe')
# open multiple tabs and switch to one tab before closed
driver = init_driver('edge', GlobalParam.get_edge_driver_path())
url_list = ['tieba.baidu.com','www.baidu.com','cn.bing.com']
open_browser_multi_tab(driver, url_list)
time.sleep(2)
switch_to_tab(driver,'www.baidu.com')
time.sleep(5)
close_driver(driver)
from opencv.cvutils import *
from python_common.global_param import GlobalParam
#------------examples----------------#
'''
image read, modify, show and write functions
'''
input = cv.imread(GlobalParam.get_image_input(), cv.IMREAD_UNCHANGED)
output = resizeImage(input, 2, 1, 3)
output = reverse_color_image(input)
output = denoiseImage(input)
output = rotateImage(input, 20)
cv.imshow('12', output)
cv.waitKey(0)
cv.imwrite(GlobalParam.get_image_output(), output)
'''
combine two images
'''
input1 = cv.imread(GlobalParam.get_image_input(), cv.IMREAD_UNCHANGED)
input2 = cv.imread(GlobalParam.get_image_output(), cv.IMREAD_UNCHANGED)
output = resizeImage(combineTwoImages(input1, input2, 'portrait'), 1, 1, 2)
'''
write text in image
'''
# only can write ascii text
input = cv.imread(GlobalParam.get_sentence_output(), cv.IMREAD_UNCHANGED)
output = writeTextOnImageAscii(input, '12444', (20, 20),
cv.FONT_HERSHEY_SIMPLEX, 1, (209, 80, 0, 255),
3)
# write unicode text, like chinese, japanese...
def load_housing_data(housing_path=GlobalParam.get_ml_ch2_housing_data()):
csv_path = os.path.join(housing_path, "housing.csv")
return pd.read_csv(csv_path)
from python_common.global_param import GlobalParam
from datasets.datasets_utils import read_excel
# read excel, use converters decide column type, if all column type is str,
# function equals:read_excel(excel_datasets, 'movie', True, dtype=str)
result = read_excel(GlobalParam.get_excel_datasets(),
'movie_maria',
True,
converters={
'id': int,
'name': str,
'chnname': str,
'main_cast': str,
'year': str,
'region': str,
'type': str,
'viewed': str,
'want_to_review': str
})
print(result)
