def test_data():
"""Create NormcapData instance for testing."""
data = NormcapData()
data.top = 0
data.bottom = 10
data.left = 0
data.right = 20
data.words = [
{
"line_num": 1,
"block_num": 1,
"par_num": 1,
"text": "one"
},
{
"line_num": 2,
"block_num": 1,
"par_num": 1,
"text": "two"
},
{
"line_num": 2,
"block_num": 1,
"par_num": 2,
"text": "three"
},
{
"line_num": 3,
"block_num": 1,
"par_num": 2,
"text": "four"
},
]
return data
def test_data():
"""Create NormcapData instance for testing."""
data = NormcapData()
data.cli_args = {
"verbose": True,
"mode": "parse",
"lang": "eng+deu",
"color": "#FF0000",
"path": None,
}
data.test_mode = True
data.top = 0
data.bottom = 10
data.left = 0
data.right = 20
data.words = [
{"line_num": 1, "text": "one"},
{"line_num": 2, "text": "two"},
{"line_num": 2, "text": "three"},
{"line_num": 3, "text": "four"},
] # Space to check trimming
test_img_folder = os.path.dirname(os.path.abspath(__file__)) + "/images/"
img = Image.open(test_img_folder + "test_email_magic_1.jpg")
data.shots = [{"monitor": 0, "image": img}]
data.image = img
return data
def handle(self, request: NormcapData) -> NormcapData:
"""Apply OCR on selected image section.
Arguments:
AbstractHandler {class} -- self
request {NormcapData} -- NormCap's session data
Returns:
NormcapData -- Enriched NormCap's session data
"""
self._logger.info("Applying OCR...")
request.cli_args["lang"] = self.get_language(request.cli_args["lang"])
# Actual OCR & transformation
request.words = self.img_to_dict(request.image,
request.cli_args["lang"])
self._logger.debug("Dataclass after OCR:%s", request)
if self._next_handler:
return super().handle(request)
return request
