def cognitive_ocr_proc(bot, update):
user = update.message.from_user
photo_file = bot.get_file(update.message.photo[-1].file_id)
photo_file.download("test_photo.jpg")
#logger.info("Photo of %s: %s" % (user.first_name, 'test_photo.jpg'))
output = ocr.OCR('test_photo.jpg')
update.message.reply_text(output)
return ConversationHandler.END
def choosePreProcess(self, image):
o = ocr.OCR()
img = self.basicPreProcess(image)
score1 = o.getImageScore(img)
img = self.fullPreProcess(image)
score2 = o.getImageScore(img)
print('score1: ' + str(score1))
print('score2: ' + str(score2))
if score1>score2:
method = self.basicPreProcess
else:
method = self.fullPreProcess
return method
def main(imageName):
fsize = os.path.getsize(imageName)
fsize /= 1024 * 1024
print(fsize)
if fsize > 1.:
compressImage(imageName)
imgOCR = ocr.OCR(imageName)
print(type(imgOCR))
print(json.dumps(imgOCR, indent=2))
infoList = []
for line in imgOCR["data"]["block"][0]["line"]:
infoList.append(line["word"][0]["content"])
genExcel(infoList, "1.excel")
def identify_stake():
if request.method == 'POST':
if 'imgData' in request.values:
ocr_obj = ocr.OCR(request.values['imgData'])
data = ocr_obj.identify_stake()
print data
return jsonify(ocr=data)
else:
data = {'stake': ''}
return jsonify(ocr=data)
else:
#dummy data for dev
data = {'stake': '25.00'}
return jsonify(ocr=data)
def analyze_bet():
if request.method == 'POST':
if 'imgData' in request.values:
ocr_obj = ocr.OCR(request.values['imgData'])
data = ocr_obj.analyze_bet()
print data
return jsonify(ocr=data)
else:
data = {'time': '', 'selection': '', 'odds': ''}
return jsonify(ocr=data)
else:
#dummy data for dev
data = {'time': '14:35', 'selection': 'Kauto Star', 'odds': '21/20'}
return jsonify(ocr=data)
def __init__(self, rootPath):
self.__rootPath = rootPath
self.__heights = [364, 444, 524, 604, 684, 764, 844]
self.__widths = [4, 124, 244, 364, 484, 604]
self.__mid_h = [399, 479, 559, 639, 719, 799, 879]
self.__mid_w = [59, 179, 299, 419, 539, 659]
self.__round_h = 70
self.__round_w = 405
self.__widthSize = 115
self.__heightSize = 75
self.__OCR = ocr.OCR()
self.__state = np.zeros((7, 6), dtype=np.int)
self.__prevState = np.zeros((7, 6), dtype=np.int)
self.__gameRound = 0
self.__util = utils.Utils(rootPath)
def __init__(self):
self.logger = logging.getLogger(self.__class__.__name__)
self.ocr = ocr.OCR()
self.wb = query.WebQuery()
self.data = {}
self.running = False
self.exiting = False
signal.signal(signal.SIGINT, self.signal_handler)
signal.signal(signal.SIGTERM, self.signal_handler)
signal.signal(signal.SIGHUP, self.signal_handler)
self.t = threading.Thread(target=self.getInput)
self.t.setDaemon(True)
self.t.start()
# start main capture loop
self.run_loop()
def readFile(self):
# Files that we can't easily read are ignored
if (self.type == "archive" or self.type == "misc."
or self.type == "audio" or self.type == "video"
or self.type == "complicated"):
return None
# .pdf: use tika instead of Pandoc
elif (self.extension == "pdf"):
return parser.from_file(self.path)["content"]
# Python can read some files natively
elif (self.extension == "txt" or self.extension == "srt"
or self.type == "programming"):
with open(self.path) as f:
return f.read()
# Images: use OCR script
elif (self.type == "image"):
return ocr.OCR(self.path)
# Documents: use Pandoc
else:
output = pypandoc.convert_file(self.path, 'plain')
return output
def __init__(self, config_file):
self.logger = logging.getLogger(self.__class__.__name__)
self.ocr = ocr.OCR(config_file)
self.wb = query.WebQuery()
self.data = {}
self.running = False
self.exiting = False
# create working directories if they don't already exist
self.create_directory(kResultsFolder)
self.create_directory(kImagesFolder)
signal.signal(signal.SIGINT, self.signal_handler)
signal.signal(signal.SIGTERM, self.signal_handler)
signal.signal(signal.SIGHUP, self.signal_handler)
self.t = threading.Thread(target=self.getInput)
self.t.setDaemon(True)
self.t.start()
# start main capture loop
self.run_loop()
# while True:
# dcObj.Rectangle((int(left+first_art_x), int(top+first_art_y), int(left+first_art_x)+10, int(top+first_art_y)+10))
# dcObj.Rectangle((int(left+art_info_left), int(top+art_info_top), int(left+art_info_left)+10, int(top+art_info_top)+10))
# dcObj.Rectangle((int(left+art_info_left+art_info_width), int(top+art_info_top+art_info_height), int(left+art_info_left+art_info_width)+10, int(top+art_info_top+art_info_height)+10))
# dcObj.Rectangle((int(left+scroll_keypt_x), int(top+scroll_keypt_y), int(left+scroll_keypt_x)+10, int(top+scroll_keypt_y)+10))
# win32gui.InvalidateRect(hwnd, monitor, True)
# # star color=255,204,50
# scroll_fin_keypt_x = 358
# scroll_fin_keypt_y = 320
# margin near level number, color=233,229,220
# initialization
ocr_model = ocr.OCR(scale_ratio=game_info.scale_ratio,
model_weight=os.path.join(bundle_dir,
'mn_model_weight.h5'))
art_id = 0
saved = 0
skipped = 0
failed = 0
star_dist = [0, 0, 0, 0, 0]
star_dist_saved = [0, 0, 0, 0, 0]
os.makedirs('artifacts', exist_ok=True)
input('请打开圣遗物背包界面，最好翻到圣遗物列表最上面。按回车继续')
print('---------------------------------')
if game_info.incomplete_lastrow:
input(
f'检测到圣遗物背包有{game_info.art_rows}行{game_info.art_cols}列，但最后一行不完整可能会影响自动翻页效果，建议更改分辨率到16:9'
def readimage(self, address): # read character from image
self.ocr = ocr.OCR()
return self.ocr.readimage(address)
# plt.show()
# i+=1
# except tf.errors.OutOfRangeError:
# print('done!')
# finally:
# coord.request_stop()
# coord.join(threads)
# run_training()
# test('./test/30.png')
# tf.reset_default_graph()
# 测试准确率
# start = time.clock()
out = []
ocr = ocr.OCR()
i = 0
for image in image_list:
if (i == 7000):
break
out.append(ocr.test(image))
# tf.reset_default_graph()
i = i + 1
# print_time()
i = 0
j = 0
for i in range(len(label_list)):
if (i == 7000):
break
if (out[i] == label_list[i]):
j = j + 1