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:
"""Execute chain of optimizations.
Arguments:
AbstractHandler {class} -- self
request {NormcapData} -- NormCap's session data
Returns:
NormcapData -- NormCap's session data with optimized image
"""
self._logger.info("Applying enhancements to image...")
# Currently, the image is only enlarged
# for other strategies see: https://stackoverflow.com/a/50762612
if request.image:
request.image = self._enlarge_dpi(request.image)
# request.image = self._grayscale(request.image)
# request.image = self._denoise(request.image)
# request.image = self._threshold(request.image)
# request.image = self._add_padding(request.image)
# request.image = self._strech_contrast(request.image)
if self._next_handler:
return super().handle(request)
else:
return request
def _crop_image(request: NormcapData) -> NormcapData:
"""Crop monitor's image and append to session data.
Arguments:
request {NormcapData} -- NormCap's session data
Returns:
NormcapData -- Enriched NormCap's session data
"""
img = request.shots[request.monitor]
cropped_img = img["image"].crop(
(request.left, request.top, request.right, request.bottom))
request.image = cropped_img
return request
