def _parse_image_in(self, parent_image, sub_image, phase_type='click'):
print 'Here is sub search img'
self._prepare()
if self.img_path:
parent_image = os.path.join(self.img_path, parent_image)
sub_image = os.path.join(self.img_path, sub_image)
else:
self._info("[>>>] img path not set")
im_source = ac.imread(self._screen.decode('utf-8').encode('gbk'))
im_parent = ac.imread(parent_image.decode('utf-8').encode('gbk'))
im_sub = ac.imread(sub_image.decode('utf-8').encode('gbk'))
intermediate = ac.find_template(im_source, im_parent, self.TH)
in_rect = intermediate['rectangle']
result = ac.find_all_template(im_source, im_sub, self.TH)
for i in range(0, len(result), 1):
result_rect = result[i]['rectangle']
# only cmp left-top && right-down 's coordinate
# rectangle[0~1]: left-top,left-down
# rectangle[2~3]: right-top,right-down
if self._coordinate_cmp(result_rect[0], in_rect[0]): # left-top
if self._coordinate_cmp(in_rect[3], result_rect[3]): # right-down
try:
if 'click' in phase_type:
self.click_a_point(result[i]['result'][0], result[i]['result'][1])
elif 'coordinate' in phase_type:
return result[i]['result'][0], result[i]['result'][1]
except Exception, e:
print '[xxx]: %s ' % traceback.format_exc()
def mobile_screen_should_contain(self, target):
"""assert current screen should contain target image
"""
self._prepare()
im_source = ac.imread(self._screen)
im_search = ac.imread(target)
re = ac.find_template(im_source, im_search, self.TH)
if re:
return True
return False
def _match_auto(self, screen, search_img, threshold):
"""Maybe not a good idea
"""
# 1. try template first
ret = ac.find_template(screen, search_img)
if ret and ret['confidence'] > threshold:
return FindPoint(ret['result'], ret['confidence'], consts.IMAGE_MATCH_METHOD_TMPL, matched=True)
# 2. try sift
ret = ac.find_sift(screen, search_img, min_match_count=10)
if ret is None:
return None
matches, total = ret['confidence']
if 1.0*matches/total > 0.5: # FIXME(ssx): sift just write here
return FindPoint(ret['result'], ret['confidence'], consts.IMAGE_MATCH_METHOD_SIFT, matched=True)
return None
def _imfind(self, bgimg, search):
method = self._image_match_method
print 'match-method:', method
imsrc, imsch = ac.imread(bgimg), ac.imread(search)
if method == 'auto':
point = ac.find(imsrc, imsch)
elif method == 'template':
res = ac.find_template(imsrc, imsch, self._threshold)
if res:
point, score = res
print 'match result:', point, score
return point
return None
elif method == 'sift':
point = imtsift.find(search, bgimg)
else:
raise RuntimeError("Unknown image match method: %s" %(method))
return point
def _match_auto(self, screen, search_img, threshold):
"""Maybe not a good idea
"""
# 1. try template first
ret = ac.find_template(screen, search_img)
if ret and ret['confidence'] > threshold:
return FindPoint(ret['result'],
ret['confidence'],
consts.IMAGE_MATCH_METHOD_TMPL,
matched=True)
# 2. try sift
ret = ac.find_sift(screen, search_img, min_match_count=10)
if ret is None:
return None
matches, total = ret['confidence']
if 1.0 * matches / total > 0.5: # FIXME(ssx): sift just write here
return FindPoint(ret['result'],
ret['confidence'],
consts.IMAGE_MATCH_METHOD_SIFT,
matched=True)
return None
def get_coordinate_by_image_identify(source, template, get_rect=False):
"""获取目标图片在原图片中的坐标
:param source:
:param template:
:param get_rect:
:return: get_rect=True
"""
try:
imsrc = ac.imread(template) # 原始图像
imsch = ac.imread(source) # 待查找的部分
position = ac.find_template(imsrc, imsch)
if position is not None:
x, y = position['result']
rect = position['rectangle']
else:
raise Exception("Cannot find the image that you provided.")
if get_rect:
return x, y, rect
else:
return x, y
except Exception as msg:
raise Exception(msg)
def pic_locate(pic_match,
pic_origin,
thresh,
findall=True,
rgb_bool=True
): #pic_match is the dir path, pic_origin is the data array
"""
:param pic_match: 源图像路径或图像数组
:param pic_origin: 背景图像，ndarray
:param thresh: 阈值，数值
:param findall: true 为寻找全部匹配图像，false为只返回一个
:param rgb_bool: true为匹配颜色，false为不匹配颜色
:return:
"""
if (isinstance(pic_match, str)): #若为路径，则根据当前分辨率动态调整实际对比图像
pic_test = Image.open(pic_match, 'r')
resolution = globalvar.get_window_resolution()
max_resolution = globalvar.get_max_resolution()
width = int(resolution[0] / max_resolution[0] * pic_test.size[0])
height = int(resolution[1] / max_resolution[1] * pic_test.size[1])
pic_test = np.array(pic_test.resize((width, height), Image.ANTIALIAS))
elif (isinstance(pic_match, np.ndarray)):
pic_test = pic_match
if findall:
position = aircv.find_all_template(pic_origin,
pic_test,
thresh,
rgb=rgb_bool)
else:
position = aircv.find_template(pic_origin,
pic_test,
thresh,
rgb=rgb_bool)
# C = np.fft.ifft2(np.fft.fft2(pic_origin)*fftpack.fft2(pic_match_path,(888,1435,3)))
return position
def search_img(imgsrc,
imgobj,
confidencevalue=0.7,
rgb=True): # imgsrc=原始图像，imgobj=待查找的图片
try:
import aircv as ac
print(imgsrc, imgobj)
imsrc = ac.imread(imgsrc)
imobj = ac.imread(imgobj)
except Exception as e:
print(e)
match_result = {'result': (-1, -1)}
return match_result['result'][0], match_result['result'][1]
match_result = ac.find_template(
imsrc, imobj, confidencevalue, rgb
) # {'confidence': 0.5435812473297119, 'rectangle': ((394, 384), (394, 416), (450, 384), (450, 416)), 'result': (422.0, 400.0)}
if match_result is not None:
match_result['shape'] = (imsrc.shape[1], imsrc.shape[0]) # 0为高，1为宽
else:
match_result = {'result': (-1, -1)}
print(match_result)
return match_result['result'][0], match_result['result'][1]
def MathPIC(Fpic,Cpic,confidence=0.95):
"""
对比图片,默认相似度95%,则认为是同一图片
:param Fpic:需要查找的图片
:param Cpic:目标图片
:param confidence:相似度
:return: 找到的坐标点,和匹配后相似度
"""
im_fpic = ac.imread(Fpic)
im_cpic = ac.imread(Cpic)
match_result = ac.find_template(im_fpic,im_cpic,confidence)
if match_result and 'confidence' in match_result and match_result["confidence"]>=confidence:
start= list(match_result["rectangle"][0])
end = list(match_result["rectangle"][-1])
# 展示匹配区域
# tmp = cv2.rectangle(im_fpic, match_result["rectangle"][0], match_result["rectangle"][-1], (0, 0, 225), 2)
# cv2.imshow("",tmp)
# cv2.waitKey()
# cv2.destroyAllWindows()
start.extend(end)
return [*start,match_result["confidence"]]
return "ERROR: 没有匹配到图片标志"
def process_cut(start_index=0):
order_anchor_image = ac.imread('order_anchor.png')
src_image = ac.imread('pic.png')
# 标准截图左上角应该是(668, X)
# 最左边的Quick卡是这个截图位置加一个截距(34, 72)
# 一张卡的大小是121 × 156
# 两张卡的距离为178
pos = ac.find_template(src_image, order_anchor_image)
pos_x, pos_y = pos['rectangle'][0]
delta_x = 34
delta_y = 72
card_w = 121
card_h = 156
delta_card = 178
for i in range(5):
crop_image = src_image[pos_y+delta_y:pos_y+delta_y+card_h,
pos_x+delta_x+delta_card*i:pos_x+delta_x+delta_card*i+card_w]
cv2.imwrite("pic\\card%d.png" % (i + start_index), crop_image)
print('已保存指令卡截图……')
def changeaccount(self):
time.sleep(2)
try:
automation.SendKeys('{Ctrl}k{Ctrl}k')
time.sleep(2)
automation.SendKeys(
'http://yct.sh.gov.cn/portal_yct/webportal/handle_progress.do?x=12{Enter}'
)
except Exception as e:
print(e)
else:
time.sleep(5)
pyautogui.screenshot(IMGSRC)
imgobj = file + r'\tc.jpg'
imsrc = ac.imread(IMGSRC)
imobj = ac.imread(imgobj)
match_result = ac.find_template(imsrc, imobj, 0.8)
if match_result:
automation.HyperlinkControl(Depth=12, Name='退出').Click()
time.sleep(5)
REDIS_GZ.hset('specify_account_session', {'session': 'false'})
automation.HyperlinkControl(Depth=11, Name='账号密码登录').Click()
else:
self.restart_login = True
def matchImg(imgobj, imgsrc=None, confidencevalue=0.5):#imgsrc=原始图像，imgobj=待查找的图片
'''
功能：在指定图片或当前桌面上定位目标图片所在位置
输入：
imgobj:必须，需定位目的图片路径。
imgsrc：可选，默认为None。源图片路径，若为空，默认为当前桌面截屏
返回：
图片在给定图片中的位置以及可靠率
'''
imobj = ac.imread(imgobj)
if not imgsrc:
current_abs_path = os.path.split(os.path.realpath(__file__))[0]
file_name = os.path.join(current_abs_path, 'total.png')
im = ImageGrab.grab()
im.save(file_name,'png')
imsrc = ac.imread(file_name)
else:
imsrc = ac.imread(imgsrc)
match_result = ac.find_template(imsrc,imobj,confidencevalue) # {'confidence': 0.5435812473297119, 'rectangle': ((394, 384), (394, 416), (450, 384), (450, 416)), 'result': (422.0, 400.0)}
if match_result is not None:
match_result['shape']=(imsrc.shape[1],imsrc.shape[0])#0为高，1为宽
return match_result
#
# code = pytesseract.image_to_string(image)
# print code
# print circle_center_pos
def draw_circle(img, p1, p2, color, line_width):
#cv2.circle(img, pos, circle_radius, color, line_width)
cv2.rectangle(img, p1, p2, color, line_width)
cv2.imshow('objDetect', img)
cv2.waitKey(0)
cv2.destroyAllWindows()
if __name__ == "__main__":
im = cv2.imread(path + "3.png")
obj = cv2.imread(path + "obj.png")
pos = ac.find_template(im, obj)
ran = pos["rectangle"]
objrex = ran[2][0] - ran[0][0]
objrey = ran[1][1] - ran[0][1]
re = im[ran[0][1] + int(1.0 / 2.0 * objrey):ran[3][1], ran[0][0] +
int(1.0 / 4.0 * objrex):ran[3][0] - int(1.0 / 2.0 * objrex)]
cv2.imwrite('./aa.png', re)
ima = cv2.imread('./aa.png')
yx = ima.shape[1]
yy = ima.shape[0]
res = cv2.resize(ima, (yx * 2, yy * 2), interpolation=cv2.INTER_CUBIC)
cv2.imwrite('./aa1.png', res)
image = Image.open('./aa1.png')
#
code = pytesseract.image_to_string(image)
print code
import cv2
import aircv
import numpy
partImg = aircv.imread("D:/part.png")
allImg = aircv.imread("D:/all.png")
match_result = aircv.find_template(allImg, partImg, 0.6)
print(match_result)
data = match_result["rectangle"]
points = numpy.array([data[0], data[1], data[3], data[2]], numpy.int)
cv2.polylines(allImg, [points], True, (0, 0, 255), 2)
cv2.imwrite("D:/result.png", allImg)
cv2.imshow("pic", allImg)
key = cv2.waitKey(0)
if 27 == key:
print("ecs")
cv2.destroyAllWindows()
# img = image.load_img('test2.png', target_size=(40, 65))
# img = np.array(img)
src = 't1.png'
sch = 't2.png'
imsrc = ac.imread(src) # 原始图像
imsch = ac.imread(sch) # 带查找的部分
print(src, sch)
res1 = ac.find_all_template(imsrc,
imsch,
threshold=0.5,
maxcnt=0,
rgb=False,
bgremove=True)
print(res1)
res = ac.find_template(imsrc, imsch)
print(res)
# path = 'sliceImage/{num}/{imgUrl}'.format(num=num, imgUrl=imgUrl)
# path = 'test.png'
# path = 't1.png'
# path = 'newSliceImage/113/0054c0fa-9191-11e9-be10-f018980779c1.png'
# path = 'test.png'
path = '/Users/zejun/Downloads/test1.png'
print(path)
imsrc = cv2.imread(path, 0)
im = imsrc
cv2.namedWindow("Python opencv")
length = 0
# cv2.setMouseCallback("Python opencv", on_EVENT_LBUTTONDOWN, length)
def match(modeImage):
srcImage = cut(savePicture=False)
pos = ac.find_template(srcImage, modeImage)
if pos is not None and pos['confidence'] > 0.9:
return True
return False
import cv2
import aircv as ac
# print circle_center_pos
def draw_circle(img, pos, circle_radius, color, line_width):
cv2.circle(img, pos, circle_radius, color, line_width)
cv2.imshow('objDetect', imsrc)
cv2.waitKey(0)
cv2.destroyAllWindows()
if __name__ == "__main__":
imsrc = ac.imread('test2.png')
imobj = ac.imread('test1.png')
# find the match position
pos = ac.find_template(imsrc, imobj)
circle_center_pos = pos['result']
circle_radius = 50
color = (0, 255, 0)
line_width = 10
# draw circle
draw_circle(imsrc, circle_center_pos, circle_radius, color, line_width)
def find_template(source, target):
result = ac.find_template(source, target)
print(3, '直接模版匹配结果：')
print(result)
def filterImage(base):
test = base + 'test.png'
testBg = base + 'testBg.png'
imsrc = cv2.imread(test, 0) # 原始图像
imsch = cv2.imread(testBg, 0)
print(imsch.shape)
height, width = imsch.shape
print(height, width)
top, bottom, left, right = 0, 100000, 10000, 0
for i in range(height):
for j in range(width):
if imsch[i][j] > 0:
if top <= i:
top = i
if bottom >= i:
bottom = i
if left >= j:
left = j
if right <= j:
right = j
imsch1 = imsch[bottom:top, left:right]
cv2.imwrite(base + 'testBg1.png', imsch1)
imsch2 = ac.imread(base + 'testBg1.png')
imsrc2 = ac.imread(test)
res1 = ac.find_all_template(imsrc2,
imsch2,
threshold=0.5,
maxcnt=0,
rgb=False,
bgremove=True)
print(res1)
res = None
if (len(res1) > 0):
res = res1[0]
for final in res1:
if res['confidence'] < final['confidence']:
res = final
else:
return base + 'test.png'
left = res['rectangle'][0][0]
right = left + 50
print('res-->', res, len(res1), res['rectangle'][0][0])
print('1: ', res1)
res = ac.find_template(imsrc2, imsch2)
print('2: ', res)
height1, width1 = imsrc.shape
# left = res['rectangle'][0][0]
# right = left + 50
print(height1, width1)
for i in range(height1):
for j in range(width1):
if i <= top and i >= bottom and j >= left and j <= right:
# print('ixj: ', i, ' ', j)
pass
else:
imsrc[i][j] = 0
print(top, bottom, left, right)
cv2.imwrite(base + 'test1.png', imsrc)
return (base + 'test1.png', left)
def match(self, pattern, screen=None, rect=None, offset=None, threshold=None, method=None):
"""Check if image position in screen
Args:
- pattern: Image file name or opencv image object
- screen (PIL.Image): optional, if not None, screenshot method will be called
- threshold (float): it depends on the image match method
- method (string): choices on <template | sift>
Returns:
None or FindPoint, For example:
FindPoint(pos=(20, 30), method='tmpl', confidence=0.801, matched=True)
Only when confidence > self.image_match_threshold, matched will be True
Raises:
TypeError: when image_match_method is invalid
"""
pattern = self.pattern_open(pattern)
search_img = pattern.image
pattern_scale = self._cal_scale(pattern)
if pattern_scale != 1.0:
search_img = cv2.resize(search_img, (0, 0),
fx=pattern_scale, fy=pattern_scale,
interpolation=cv2.INTER_CUBIC)
screen = screen or self.region_screenshot()
threshold = threshold or pattern.threshold or self.image_match_threshold
# handle offset if percent, ex (0.2, 0.8)
dx, dy = offset or pattern.offset or (0, 0)
dx = pattern.image.shape[1] * dx # opencv object width
dy = pattern.image.shape[0] * dy # opencv object height
dx, dy = int(dx*pattern_scale), int(dy*pattern_scale)
# image match
screen = imutils.from_pillow(screen) # convert to opencv image
if rect and isinstance(rect, tuple) and len(rect) == 4:
(x0, y0, x1, y1) = [int(v*pattern_scale) for v in rect]
(dx, dy) = dx+x0, dy+y0
screen = imutils.crop(screen, x0, y0, x1, y1)
#cv2.imwrite('cc.png', screen)
match_method = method or self.image_match_method
ret = None
confidence = None
matched = False
position = None
if match_method == consts.IMAGE_MATCH_METHOD_TMPL: #IMG_METHOD_TMPL
ret = ac.find_template(screen, search_img)
if ret is None:
return None
confidence = ret['confidence']
if confidence > threshold:
matched = True
(x, y) = ret['result']
position = (x+dx, y+dy) # fix by offset
elif match_method == consts.IMAGE_MATCH_METHOD_SIFT:
ret = ac.find_sift(screen, search_img, min_match_count=10)
if ret is None:
return None
confidence = ret['confidence']
matches, total = confidence
if 1.0*matches/total > 0.5: # FIXME(ssx): sift just write here
matched = True
(x, y) = ret['result']
position = (x+dx, y+dy) # fix by offset
elif match_method == consts.IMAGE_MATCH_METHOD_AUTO:
fp = self._match_auto(screen, search_img, threshold)
if fp is None:
return None
(x, y) = fp.pos
position = (x+dx, y+dy)
return FindPoint(position, fp.confidence, fp.method, fp.matched)
else:
raise TypeError("Invalid image match method: %s" %(match_method,))
(x, y) = ret['result']
position = (x+dx, y+dy) # fix by offset
if self.bounds:
x, y = position
position = (x+self.bounds.left, y+self.bounds.top)
return FindPoint(position, confidence, match_method, matched=matched)
def find_status_tansuo(statusNow, imsrc):
status = -1
imobj = imobj_combat
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold:
status = status_combat
print("---This is in battle t...")
if status < 0:
imobj = imobj_tansuo10
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold:
status = status_begin
print("---There is a battle begin t...")
if status < 0:
imobj = imobj_tansuo13
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold - 0.1:
status = status_ts_choose
print("---There choose tansuo t3...")
if status < 0:
imobj = imobj_tansuo11
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold - 0.1:
status = status_ts_choose
print("---There choose tansuo t1...")
if status < 0:
imobj = imobj_tansuo12
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold - 0.1:
status = status_ts_choose
print("---There choose tansuo t2...")
if status < 0:
imobj = imobj_tansuo31
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold:
status = status_end2
print("---This is in end t1...")
if status < 0:
imobj = imobj_yuhun32
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold:
status = status_end2
print("---This is in end t2...")
# 从结果中读取坐标
if status >= 0:
statusNow = status
pos = res['result']
# 在目标范围内做一次随机取点
w, h, r = imobj.shape
posaim = (int(posbase[0] + pos[0] + w * (random.random() - 0.5) * 0.3),
int(posbase[1] + pos[1] + h * (random.random() - 0.5) * 0.3))
print(posaim, res['confidence'])
else:
posaim = (int(posbase[0]), int(posbase[1]))
# 如果是第二次进入choose则可执行点击
if statusNow == status_ts_choose:
status = status_choose
return status, posaim
def match(target, ignore_err=False):
global ROOT_DIR
# global threshold
if '-' in target:
target_path = target.split("-")[0]
target_name = target.split("-")[1]
appname = ROOT_DIR + '/testimage/' + target_path + '/' + target_name + '.png'
appname_2 = ROOT_DIR + '/testimage/' + target_path + '/' + target_name + '_2.png'
appname_3 = ROOT_DIR + '/testimage/' + target_path + '/' + target_name + '_3.png'
else:
appname = ROOT_DIR + '/testimage/' + target + '.png'
appname_2 = ROOT_DIR + '/testimage/' + target + '_2.png'
appname_3 = ROOT_DIR + '/testimage/' + target + '_3.png'
##根据桌面路径进行截屏
##获取当前桌面路径
path = os.path.join(os.path.expanduser('~'), "Desktop")
hwnd = win32gui.FindWindow(None, path)
app = QApplication(sys.argv)
screen = QApplication.primaryScreen()
img = screen.grabWindow(hwnd).toImage()
# img = ImageGrab.grab()
##保存截屏
root_desk = ROOT_DIR + '/desktop.png'
img.save(root_desk)
##等待图片保存
time.sleep(0.5)
# 支持图片名为中英文名，也支持路径中英文
imsrc = cv2.imdecode(np.fromfile(root_desk, dtype=np.uint8), -1)
imobj = cv2.imdecode(np.fromfile(appname, dtype=np.uint8), -1)
# 匹配图标位置
pos = ac.find_template(imsrc, imobj, threshold)
if pos == None and os.path.exists(appname_2):
print(u"第一张图标没匹配到，2秒后匹配第二张：")
time.sleep(2)
print(appname_2)
imobj_2 = cv2.imdecode(np.fromfile(appname_2, dtype=np.uint8), -1)
pos = ac.find_template(imsrc, imobj_2, threshold)
if pos == None and os.path.exists(appname_3):
print(u"第二张图标没匹配到，2秒后匹配第三张：")
time.sleep(2)
print(appname_3)
imobj_3 = cv2.imdecode(np.fromfile(appname_3, dtype=np.uint8), -1)
pos = ac.find_template(imsrc, imobj_3, threshold)
# 如果第三张还未匹配到，用另一种方法重新截图
if pos == None:
print(u"2秒后重新截全屏...")
time.sleep(2)
##保存截屏
root_desk = ROOT_DIR + '/desktop_2.png'
img = ImageGrab.grab()
img.save(root_desk)
##等待图片保存
time.sleep(0.5)
# 支持图片名为中英文名，也支持路径中英文
imsrc = cv2.imdecode(np.fromfile(root_desk, dtype=np.uint8), -1)
imobj = cv2.imdecode(np.fromfile(appname, dtype=np.uint8), -1)
# 匹配图标位置
pos = ac.find_template(imsrc, imobj, threshold)
if pos == None and os.path.exists(appname_2):
print(u"第一张图标没匹配到，2秒后匹配第二张：")
time.sleep(2)
print(appname_2)
imobj_2 = cv2.imdecode(np.fromfile(appname_2, dtype=np.uint8), -1)
# imobj_2 = ac.imread(appname_2)
pos = ac.find_template(imsrc, imobj_2, threshold)
if pos == None and os.path.exists(appname_3):
print(u"第二张图标没匹配到，2秒后匹配第三张：")
time.sleep(2)
print(appname_3)
imobj_3 = cv2.imdecode(np.fromfile(appname_3, dtype=np.uint8), -1)
# imobj_3 = ac.imread(appname_3)
pos = ac.find_template(imsrc, imobj_3, threshold)
if pos == None:
print(u"第二种截图方式也没有匹配到：" + target)
if not ignore_err:
raise Exception('匹配失败')
elif pos != None:
x, y = pos['result']
print(x, y, 'pos')
pyautogui.moveTo(x=x, y=y, duration=0.5)
print(u"匹配成功：{}，坐标位置为：{}".format(target, pyautogui.position()))
time.sleep(0.5)
return x, y
def get_cookie_by_phantomjs(self):
"""
获得cookie，需要selenium和phantomjs, 在建立webdriver时需要指定phantomjs的安装路径
"""
result = {'result': False}
params = webdriver.common.desired_capabilities.DesiredCapabilities.PHANTOMJS.copy(
)
params['phantomjs.page.settings.userAgent'] = (
'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:58.0) Gecko/20100101 Firefox/58.0'
)
url = 'http://search.anccnet.com/searchResult2.aspx'
# windows环境指定目录driver = webdriver.PhantomJS(executable_path='phantomjs.exe', desired_capabilities=params)
driver = webdriver.PhantomJS(executable_path='phantomjs',
desired_capabilities=params) # centos环境
driver.set_window_size(382, 415)
driver.get(url)
sleep(10)
if driver.title == '401 - 未授权: 由于凭据无效，访问被拒绝。':
print(driver.title)
sys.exit()
iframe = driver.find_element_by_id('captcha_widget')
driver.switch_to.frame(iframe)
btn = driver.find_element_by_class_name('captcha-widget-event')
btn.click()
sleep(5)
driver.switch_to.default_content()
# 获得验证码图片所在iframe, iframe.size 中保存框架的height, width
iframe = driver.find_element_by_id('captcha_frame')
driver.switch_to.frame(iframe)
# 从iframe中获得验证图片，并转换成aircv对象
img = driver.find_element_by_id(
'lc-image-panel').find_element_by_class_name('captcha-list')
imsrc = self.get_imsrc(img)
# 从iframe中获得需要验证的点击步骤，可能会需要按顺序点击星形,圆点,方块
checklist = driver.find_element_by_css_selector(
'span#lc-captcha-word i').text
checklist = checklist.split(',')
for i in checklist:
imobj = self.get_shape(i)
# 在验证图片中查找验证点
pos = aircv.find_template(im_source=imsrc,
im_search=imobj,
threshold=0.7)['result']
# 点击验证点
webdriver.ActionChains(driver).move_to_element_with_offset(
iframe, pos[0], pos[1]).click().perform()
sleep(1)
sleep(5)
# 获得cookie
tmp = driver.get_cookies()
driver.quit()
if tmp:
cookie = '%s=%s' % (tmp[0]['name'], tmp[0]['value'])
print('get cookie : %s ' % cookie)
self.header['Cookie'] = cookie
result['result'] = True
result['cookie'] = cookie
return result
else:
print('get cookie failed! check : %s' % ','.join(checklist))
return result
def compare_(objs):
imobj = ac.imread(objs)
imsrc = ac.imread('%s\\src.jpg' % os.getcwd())
pos = ac.find_template(imsrc, imobj, 0.5)
return pos
def FindOnImg(srcImg, targetImg, th=0.7):
imobj = ac.imread(targetImg)
pos = ac.find_template(srcImg, imobj)
if pos:
if (pos['confidence'] > th):
return pos['result']
#coding=utf-8
'''
Created on 2019/7/17 12:49:54
@author: tsfissure
'''
import aircv
imgSrc = aircv.imread("a.png")
imgSch = aircv.imread("img\challenge.png")
rlt = aircv.find_template(imgSrc, imgSch)
print(rlt)
if __name__ == '__main__':
pass
def match(self, pattern, screen=None, threshold=None):
"""Check if image position in screen
Args:
- pattern: Image file name or opencv image object
- screen: opencv image, optional, if not None, screenshot method will be called
Returns:
None or FindPoint, For example:
FindPoint(pos=(20, 30), method='tmpl', confidence=0.801, matched=True)
Only when confidence > self.image_match_threshold, matched will be True
Raises:
TypeError: when image_match_method is invalid
"""
pattern = self.pattern_open(pattern)
search_img = pattern.image
pattern_scale = self._cal_scale(pattern)
if pattern_scale != 1.0:
search_img = cv2.resize(search_img, (0, 0),
fx=pattern_scale, fy=pattern_scale,
interpolation=cv2.INTER_CUBIC)
screen = screen or self.region_screenshot()
threshold = threshold or self.image_match_threshold
dx, dy = pattern.offset
dx, dy = int(dx*pattern_scale), int(dy*pattern_scale)
# image match
screen = imutils.from_pillow(screen) # convert to opencv image
match_method = self.image_match_method
ret = None
if match_method == consts.IMAGE_MATCH_METHOD_TMPL:
ret = ac.find_template(screen, search_img)
elif match_method == consts.IMAGE_MATCH_METHOD_SIFT:
ret = ac.find_sift(screen, search_img, min_match_count=10)
else:
raise TypeError("Invalid image match method: %s" %(match_method,))
if ret is None:
return None
(x, y) = ret['result']
# fix by offset
position = (x+dx, y+dy)
if self.bounds:
x, y = position
position = (x+self.bounds.left, y+self.bounds.top)
confidence = ret['confidence']
matched = True
if match_method == consts.IMAGE_MATCH_METHOD_TMPL:
if confidence < threshold:
matched = False
elif match_method == consts.IMAGE_MATCH_METHOD_SIFT:
matches, total = confidence
if 1.0*matches/total > 0.5: # FIXME(ssx): sift just write here
matched = True
return FindPoint(position, confidence, match_method, matched=matched)
import numpy as np
import cv2
import aircv as ac
from appium import webdriver
import time
import unittest
from selenium.webdriver.common import desired_capabilities
img = cv2.imread('D:\\GitRex\\pic.png')
x = type(img)
print(x)
y = img.shape
print(y)
#cv2.imshow('My Image', img) # open the picture
#cv2.waitKey(0)
#cv2.destroyAllWindows()
img2 = cv2.imread('D:\\GitRex\\set.png')
y2 = img.shape
print(y2)
pos = ac.find_template(img, img2)
print(pos)
def match(self, pattern, screen=None, threshold=None):
"""Check if image position in screen
Args:
- pattern: Image file name or opencv image object
- screen: opencv image, optional, if not None, screenshot method will be called
Returns:
None or FindPoint, For example:
FindPoint(pos=(20, 30), method='tmpl', confidence=0.801, matched=True)
Only when confidence > self.image_match_threshold, matched will be True
Raises:
TypeError: when image_match_method is invalid
"""
pattern = self.pattern_open(pattern)
search_img = pattern.image
pattern_scale = self._cal_scale(pattern)
if pattern_scale != 1.0:
search_img = cv2.resize(search_img, (0, 0),
fx=pattern_scale,
fy=pattern_scale,
interpolation=cv2.INTER_CUBIC)
screen = screen or self.region_screenshot()
threshold = threshold or self.image_match_threshold
dx, dy = pattern.offset
dx, dy = int(dx * pattern_scale), int(dy * pattern_scale)
# image match
screen = imutils.from_pillow(screen) # convert to opencv image
match_method = self.image_match_method
ret = None
if match_method == consts.IMAGE_MATCH_METHOD_TMPL:
ret = ac.find_template(screen, search_img)
elif match_method == consts.IMAGE_MATCH_METHOD_SIFT:
ret = ac.find_sift(screen, search_img, min_match_count=10)
else:
raise TypeError("Invalid image match method: %s" %
(match_method, ))
if ret is None:
return None
(x, y) = ret['result']
# fix by offset
position = (x + dx, y + dy)
if self.bounds:
x, y = position
position = (x + self.bounds.left, y + self.bounds.top)
confidence = ret['confidence']
matched = True
if match_method == consts.IMAGE_MATCH_METHOD_TMPL:
if confidence < threshold:
matched = False
elif match_method == consts.IMAGE_MATCH_METHOD_SIFT:
matches, total = confidence
if 1.0 * matches / total > 0.5: # FIXME(ssx): sift just write here
matched = True
return FindPoint(position, confidence, match_method, matched=matched)
cv2.circle(img, pos, circle_radius, color, line_width)
cv2.imshow('objDetect', imsrc)
cv2.waitKey(0)
cv2.destroyAllWindows()
if __name__ == "__main__":
while True:
# imsrc = ac.imread('C:\\Users\\SakataKin\\Desktop\\src.jpg')
im = ImageGrab.grab()
im.save('d:\\grabtmp.jpg')
imsrc = ac.imread('d:\\grabtmp.jpg')
imobj = ac.imread('C:\\Users\\SakataKin\\Desktop\\tag.png')
# find the match position
pos = ac.find_template(imsrc, imobj, rgb=True, bgremove=False)
print(pos)
if not (pos is None):
circle_center_pos = tuple_f2i(pos['result'])
print(circle_center_pos)
circle_radius = 50
color = (0, 255, 0)
line_width = 10
draw_circle(imsrc, circle_center_pos, circle_radius, color,
line_width)
time.sleep(3)
else:
print("Cannot find the target")
time.sleep(3)
def find_status_tansuo(taskNow, tansuocnt, imsrc, posbase):
#使用的临时状态量
status = -1
#检测是否处于战斗状态
imobj = imobj_combat
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold:
status = tansuo_combat
#检测是否在探索选择界面
if status < 0:
imobj = imobj_tansuo0
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold:
status = tansuo_explore
#检测是否有开始按钮
if status < 0:
imobj = imobj_tansuo11
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold:
status = tansuo_begin
#检测是否在选择界面
if status < 0:
imobj = imobj_tansuo20
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold:
status = tansuo_choose
if status < 0:
imobj = imobj_tansuo21
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold:
status = tansuo_choose
if status < 0:
imobj = imobj_tansuo22
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold:
status = tansuo_choose
#检测是否有准备按钮
if status < 0:
imobj = imobj_tansuo2R
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold:
status = tansuo_ready
#检查结算界面1
if status < 0:
imobj = imobj_tansuo31
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold:
status = tansuo_end
if status < 0:
imobj = imobj_tansuo32
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold:
status = tansuo_end
#检查是否在关卡结算界面
if status < 0:
imobj = imobj_tansuo41
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold_H:
status = tansuo_over1
if status < 0:
imobj = imobj_tansuo42
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold:
status = tansuo_over2
#如果无任何结果判断是否探索中
if status < 0:
imobj = imobj_tansuo30
res = ac.find_template(imsrc, imobj)
if res != None and res['confidence'] > confthreshold:
status = tansuo_find
# 从结果中读取坐标
if status >= 0:
offset = res['result']
# 在目标范围内做一次随机取点
rect = imobj.shape
taskNow, tansuocnt = click_action_tansuo(taskNow, tansuocnt, status,
posbase, offset, rect[0],
rect[1])
return taskNow, tansuocnt
def compareTwoImg(srcImg, objImg):
imgSrc = ac.imread(srcImg)
imgObj = ac.imread(objImg)
return ac.find_template(imgSrc, imgObj)
def main():
imsrc = ac.imread(sys.argv[1])
imobj = ac.imread(sys.argv[2])
pos = ac.find_template(imsrc, imobj)
print(pos['result'])
def 宝具(user, 手动选卡=False, 敌对目标=0, 选卡策略=[]):
global remain_phase_number
if 敌对目标 > 0:
tap_key('234'[敌对目标 - 1], 普通操作时间)
tap_key('\n', 进入选卡界面时间)
index = 查找从者(user)
# 识别5张牌都是啥
# 5张牌在标准化图片（992*611）上的位置：
# （10+200X,300）-（190+200X,5320），X=0,1,2,3,4
if 自动选卡策略:
src_image = cv2.resize(cut(save_picture=False), (992, 611))
found_card_list = []
for i in range(5):
card_area_image = src_image[300:520, 10 + 200 * i:190 + 200 * i]
found = '未定义-未定义'
for servant_name in 阵容[:3]:
if servant_name != '':
for color in ['红', '蓝', '绿']:
for test_image in 阵容卡组[servant_name][color]:
pos = ac.find_template(card_area_image, test_image)
# 这里有一个助战图标的问题
if pos is not None and pos['confidence'] > 0.8:
found = '%s-%s' % (servant_name, color)
break
break
break
found_card_list.append(found)
print('检测结果:')
print(found_card_list)
if not 手动选卡:
result = []
if 自动选卡策略:
for 策略 in 选卡策略:
# 试图匹配策略
result = 选卡匹配(策略, found_card_list)
if len(result) > 0:
break
if len(result) == 0:
result = ['WER'[index], 'S', 'D']
tap_key(result[0], 普通操作时间)
tap_key(result[1], 普通操作时间)
if not 自动选卡策略:
tap_key(result[2], treasure_time(user) + 换面时间)
else:
tap_key(result[2], 普通操作时间)
remain_phase_number -= 1
print('剩余面数：%d' % remain_phase_number)
wait_until_next_phase()
if remain_phase_number <= 0:
remain_phase_number = 3
else:
tap_key('WER'[index], 普通操作时间)
等待操作()
等待(treasure_time(user) + 换面时间)
if user == '大英雄':
阵容[index] = 阵容[3]
阵容[3] = 阵容[4]
阵容[4] = 阵容[5]
阵容[5] = ''
def draw_circle(img, pos, circle_radius, color, line_width):
# print(img, pos, circle_radius, color, line_width)
cv2.circle(img, pos, circle_radius, color, line_width)
cv2.imshow('objDetect', imsrc)
cv2.waitKey(0)
cv2.destroyAllWindows()
if __name__ == "__main__":
imsrc = ac.imread('0-common_pics/bg.jpg')
imobj = ac.imread('0-common_pics/obj.png')
imsrc_, imobj_ = imsrc[:], imobj[:]
pos = ac.find_template(imsrc_, imobj_) # find the match position
# help( ac.find_template )
# print( pos ) # {'result': (793.0, 450.0), 'rectangle': ((744, 405), (744, 495), (842, 405), (842, 495)), 'confidence': 0.543538510799408}
circle_center_pos = pos['result']
'''
TypeError: integer argument expected, got float 参数预期应该是 整型，结果得到浮点型
因为 circle_center_pos 是浮点型。所以要转整型为 new_int_circle_center_pos
'''
new_int_circle_center_pos = []
for i in list(circle_center_pos):
new_int_circle_center_pos.append(int(i))
print(tuple(new_int_circle_center_pos)) # (793, 450)
circle_radius = 50
color = (0, 255, 0)