爬虫--破解滑动验证
一、cv2基本库函数
cv2.imread(filepath，flags)：读入一张图像
- filepath：要读入图片的完整路径
- flags：读入图片的标志
- cv2.IMREAD_COLOR：默认参数，读入一副彩色图片，忽略alpha通道
- cv2.IMREAD_GRAYSCALE：读入灰度图片
- cv2.IMREAD_UNCHANGED：顾名思义，读入完整图片，包括alpha通道
cv2.imshow(wname，img)：显示图像
- wname：显示图像窗口的名字
- img：要显示的图像，窗口大小自动调整为图片大小
cv2.imwrite(file，img，num)：保存一张图像
- file：要保存的文件名
- img：保存的图像
- num：压缩的级别，默认为3
cv2.cvtColor(img，code) ：图像颜色空间转换
- img：要转换的图片
- code：要转换颜色的数值
- cv2.COLOR_RGB2GRAY：彩色图像转化为灰度图像
- cv2.COLOR_GRAY2RGB：灰度图像转化为彩色图像
- # cv2.COLOR_X2Y，其中X,Y = RGB, BGR, GRAY, HSV, YCrCb, XYZ, Lab, Luv, HLS
cv2.matchTemplate(img，templ，method)：模板匹配
- img：待搜索图像
- templ：搜索模板，需和原图一样的数据类型且尺寸不能大于源图像
- method：指定的匹配方法
- CV_TM_SQDIFF----平方差匹配法（最好匹配0）
- CV_TM_SQDIFF_NORMED----归一化平方差匹配法（最好匹配0）
- CV_TM_CCORR----相关匹配法（最坏匹配0）
- CV_TM_CCORR_NORMED----归一化相关匹配法（最坏匹配0）
- CV_TM_CCOEFF----系数匹配法（最好匹配1）
- CV_TM_CCOEFF_NORMED----化相关系数匹配法（最好匹配1）
cv2.minMaxLoc(res)：矩阵的最小值，最大值，并得到最大值，最小值的索引
- res：矩阵
cv2.rectangle(img，pt1，pt2，color[，thickness[，lineType[，shift]]])：计量图像的坐标轴
- img：图片
- pt1：矩形的左上角坐标
- pt2：矩形的右下角坐标
- color：矩形边框的颜色
- thickness：矩形边框的厚度，如果为负值，如 CV_FILLED，则表示填充整个矩形
- lineTpye：指定线形状
- shift：点坐标中的小数位数，但是我感觉这个参数是在将坐标右移 shift 位一样
参考博客：https://blog.csdn.net/sinat_41104353/article/details/85171185
二、破解滑动验证
1.找出缺口距离
def get_distance(self):
"""
计算缺口的位置，由于缺口位置查找偶尔会出现找不准的现象，这里进行判断，
:return: 距离和背景（模版）图
"""
block_img_path = self.image_path + 'block.jpg'
template_img_path = self.image_path + 'template.jpg'
# 获取图片并灰度化
block = cv2.imread(self.image_path + self.small_img, 0)
template = cv2.imread(self.image_path + self.big_img, 0)
# 将二值化后的图片进行保存
cv2.imwrite(template_img_path, template)
cv2.imwrite(block_img_path, block)
block = cv2.imread(block_img_path)
block = cv2.cvtColor(block, cv2.COLOR_BGR2GRAY)
block = abs(255 - block)
cv2.imwrite(block_img_path, block)
block = cv2.imread(block_img_path)
template = cv2.imread(template_img_path)
# 获取偏移量
result = cv2.matchTemplate(block, template, cv2.TM_CCOEFF_NORMED)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
y = max_loc[0]
cv2.rectangle(template, max_loc, (max_loc[0] + 50, max_loc[1] + 50), (7, 249, 151), 2)
return y, template
2.生成轨迹并滑动
1 def get_track1(dis):
2 """
3 这个是用来模拟人为拖动滑块行为，快到缺口位置时，
4 给定随机偏移量，最后在回归
5 :return:
6 """
7 v = 0
8 t = random.uniform(0.3, 0.8)
9 x_offset = random.randint(15, 27)
10 dis = dis + x_offset
11 tracks = []
12 current = 0
13 mid = dis * 3 / 4
14 while current <= dis:
15 if current < mid:
16 a = random.uniform(1, 24)
17 else:
18 a = -(random.uniform(-1, 3))
19 v0 = v
20 t = random.uniform(0.05, 0.2)
21 s = v0 * t + 0.5 * a * (t ** 2)
22 current += s
23 tracks.append(round(s))
24 v = v0 + a * t
25 tracks.append(dis - sum(tracks))
26
27 for x in range(x_offset):
28 tracks.append(-1)
29 return tracks
1 def get_track2(distance):
2 """
3 根据偏移量和手动操作模拟计算移动轨迹
4 :param distance: 偏移量
5 :return: 移动轨迹
6 """
7 # 移动轨迹
8 tracks = []
9 # 当前位移
10 current = 0
11 # 减速阈值
12 mid = distance * 4 / 5
13 # 时间间隔
14 t = 0.2
15 # 初始速度
16 v = 0
17
18 while current < distance:
19 if current < mid:
20 a = random.uniform(2, 5)
21 else:
22 a = -(random.uniform(12.5, 13.5))
23 v0 = v
24 v = v0 + a * t
25 x = v0 * t + 1 / 2 * a * t * t
26 current += x
27
28 if 0.6 < current - distance < 1:
29 x = x - 0.53
30 tracks.append(round(x))
31
32 elif 1 < current - distance < 1.5:
33 x = x - 1.4
34 tracks.append(round(x))
35 elif 1.5 < current - distance < 3:
36 x = x - 1.8
37 tracks.append(round(x))
38
39 else:
40 tracks.append(round(x))
41
42 return tracks, 0
def get_track3(distance):
"""
:param distance:
:return:
"""
total_dis = 0
tracks = []
while True:
random_v = random.uniform(2, 4)
random_t = random.uniform(1.5, 2.5)
s = random_v * random_t
total_dis += round(s)
tracks.append(round(s))
if total_dis > distance:
offset = total_dis - distance
tracks.append(-offset)
break
return tracks, 0
def get_track4(distance):
"""
没有随机性
:param distance:
:return:
"""
track = []
current = 0
mid = distance * 3 / 5.
t = 0.2
v = 0
while current < distance:
if current < mid:
a = 2.
else:
a = -3.
v0 = v
v = v0 + a * t
move = v0 * t + 1 / 2. * a * t * t
current += move
track.append(round(move))
return track, 0
def get_track5(distance):
"""
本质来源于物理学中的加速度算距离： s = vt + 1/2 at^2
v = v_0 + at
在这里：总距离S= distance+20
加速度：前3/5S加速度2，后半部分加速度是-3
在上面的上增加随机回退
"""
x_offset = random.randint(10, 30)
distance += x_offset # 先滑过一点，最后再反着滑动回来
v = 0
t = 0.2
tracks = []
current = 0
mid = distance * 3 / 5
while current < distance:
if current < mid:
a = random.randint(1, 3)
else:
a = int(random.uniform(-2, -4))
s = v * t + 0.5 * a * (t ** 2)
v = v + a * t
current += s
tracks.append(round(s))
# 反着滑动到准确位置
back_tracks = VerifySlider.random_num(random.randint(2, 5), -x_offset)
print(tracks)
print(back_tracks)
return tracks, back_tracks
3.获取滑块
element = self.driver.find_element_by_css_selector(self.element_chunk_name)#获取滑块
ActionChains(self.driver).click_and_hold(on_element=element).perform()#鼠标点击到滑块位置
for track in tracks:#移动鼠标
ActionChains(self.driver).move_by_offset(xoffset=track, yoffset=0).perform()
