def img2str(self, captcha_body):
with BytesIO(captcha_body) as captcha_filelike, Image.open(
captcha_filelike) as img:
new_img = img.convert('L') # 转换为RGBA
pix = new_img.load() # 转换为像素
# 处理上下黑边框，size[0]即图片长度
for x in range(new_img.size[0]):
pix[x, 0] = pix[x, new_img.size[1] - 1] = 255
# 处理左右黑边框，size[1]即图片高度
for y in range(new_img.size[1]):
pix[0, y] = pix[new_img.size[0] - 1, y] = 255
# 二值化处理，这个阈值为140比较合适
threshold = 140 # 阈值
table = []
for i in range(256):
if i < threshold:
table.append(0)
else:
table.append(1)
new_img = new_img.point(table, '1')
# 识别图片上的值
text = get_text_from_image(
new_img,
psm=7,
tessedit_char_whitelist=self.captcha_char_whitelist).replace(
' ', '')
new_img.close()
return text
def parse_capatcha(captcha_body):
with BytesIO(captcha_body) as captcha_filelike, Image.open(captcha_filelike) as img:
# img.show()
# 构造算子为32位浮点三维矩阵kernel：[(1 / 20, 1 / 20, 1 / 20, 1 / 20, 1 / 20)
# (1 / 20, 1 / 20, 1 / 20, 1 / 20, 1 / 20)
# (1 / 20, 1 / 20, 1 / 20, 1 / 20, 1 / 20)
# (1 / 20, 1 / 20, 1 / 20, 1 / 20, 1 / 20)
# (1 / 20, 1 / 20, 1 / 20, 1 / 20, 1 / 20)]
# kernel = numpy.ones((5, 5), numpy.float32) / 19
# sobelX = numpy.array([[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]])
# sobelY = numpy.array([[1, 2, 1], [0, 0, 0], [-1, -2, -1]])
# kernel = numpy.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
# 做卷积去噪点
eroded = numpy.array(img)
eroded = cv2.fastNlMeansDenoisingColored(eroded)
mask_img_arr = numpy.zeros((eroded.shape[0], eroded.shape[1]), numpy.uint8)
dst_img = numpy.array(img)
cv2.inpaint(eroded, mask_img_arr, 10, cv2.INPAINT_TELEA, dst=dst_img)
# 图像灰度化处理
eroded = cv2.cvtColor(eroded, cv2.COLOR_BGR2GRAY)
# 图像二值化处理
ret, eroded = cv2.threshold(eroded, 125, 255, cv2.THRESH_BINARY)
dest_img = Image.fromarray(eroded)
code = get_text_from_image(dest_img,
tessedit_char_whitelist=captcha_char_whitelist).replace(' ', '')
dest_img.close()
return code
def img2str(captcha_body):
captcha_char_whitelist = digits
with Image.open(captcha_body) as img:
new_img = img.convert('L') # 转换为RGBA
pix = new_img.load() # 转换为像素
# # 处理上下黑边框，size[0]即图片长度
# for x in range(new_img.size[0]):
# pix[x, 0] = pix[x, new_img.size[1] - 1] = 255
# # 处理左右黑边框，size[1]即图片高度
# for y in range(new_img.size[1]):
# pix[0, y] = pix[new_img.size[0] - 1, y] = 255
# 二值化处理，这个阈值为140比较合适
threshold = 180 # 阈值 # 201
table = []
for i in range(256):
if i < threshold:
table.append(0)
else:
table.append(1)
new_img = new_img.point(table, '1')
# 保存图片下来方便后面训练
# new_img.save("captcha/" + str(int(time())) + ".jpg")
# 识别图片上的值
text = get_text_from_image(
new_img, psm=7,
tessedit_char_whitelist=captcha_char_whitelist).replace(' ', '')
new_img.close()
return text
def test_options(self):
quick_fox_image = get_test_image('quickfox.png')
text = get_text_from_image(
quick_fox_image,
psm=10 #single character
)
assert isinstance(text, six.text_type)
assert len(text) == 1
def test_options(self):
quick_fox_image = get_test_image('quickfox.png')
text = get_text_from_image(
quick_fox_image,
psm=10 #single character
)
assert isinstance(text, six.text_type)
assert len(text) == 1
def test_configs(self):
allowed_chars = "0123456789-"
white_list_set = set(allowed_chars)
alphanum_image = get_test_image('alphanumeric.png')
#default with alphas
text = get_text_from_image(alphanum_image)
assert isinstance(text, six.text_type)
assert not all(char in white_list_set for char in text if char != ' ')
#digits config file
text = get_text_from_image(alphanum_image, config_name='digits')
assert isinstance(text, six.text_type)
assert all(char in white_list_set for char in text if char != ' ')
#manual config
allowed_chars = "123"
white_list_set = set(allowed_chars)
text = get_text_from_image(
alphanum_image,
tessedit_char_whitelist=allowed_chars,
)
assert isinstance(text, six.text_type)
assert all(char in white_list_set for char in text if char != ' ')
def test_configs(self):
allowed_chars = "0123456789-"
white_list_set = set(allowed_chars)
alphanum_image = get_test_image('alphanumeric.png')
#default with alphas
text = get_text_from_image(alphanum_image)
assert isinstance(text, six.text_type)
assert not all(char in white_list_set for char in text if char != ' ')
#digits config file
text = get_text_from_image(alphanum_image, config_name='digits')
assert isinstance(text, six.text_type)
assert all(char in white_list_set for char in text if char != ' ')
#manual config
allowed_chars = "123"
white_list_set = set(allowed_chars)
text = get_text_from_image(
alphanum_image,
tessedit_char_whitelist=allowed_chars,
)
assert isinstance(text, six.text_type)
assert all(char in white_list_set for char in text if char != ' ')
def recognize_captcha_by_tesseract(img,
digits_only=False,
letters_only=False,
del_noise=False):
if digits_only:
whitelist = digits
elif letters_only:
whitelist = ascii_letters
else:
whitelist = all_chars
img = convert_img_2_baw(img)
if del_noise:
img = del_img_noise(img)
text = get_text_from_image(img, tessedit_char_whitelist=whitelist)
return blank_pattern.sub("", text)
def test_simple_sentence(self):
actual_text = "The quick brown fox jumps over the lazy dog"
quick_fox_image = get_test_image('quickfox.bmp')
text = get_text_from_image(quick_fox_image)
assert isinstance(text, six.text_type)
assert check_similarity_ratio(text, actual_text)
def test_blank_image(self):
blank_image = Image.new("RGB", (100, 100), color=(255, 255, 255))
text = get_text_from_image(blank_image)
assert isinstance(text, six.text_type)
assert len(text) == 0
def test_simple_sentence(self):
actual_text = "The quick brown fox jumps over the lazy dog"
quick_fox_image = get_test_image('quickfox.bmp')
text = get_text_from_image(quick_fox_image)
assert isinstance(text, six.text_type)
assert check_similarity_ratio(text, actual_text)
def test_blank_image(self):
blank_image = Image.new("RGB", (100,100), color=(255, 255, 255))
text = get_text_from_image(blank_image)
assert isinstance(text, six.text_type)
assert len(text) == 0
def extract_text_by_google(imagePath):
with Image.open(imagePath) as img:
return get_text_from_image(img)