def execute(self, template_object: np.ndarray, target_object: np.ndarray,
*_, **__) -> FindItEngineResponse:
resp = FindItEngineResponse()
resized_target = cv2.resize(target_object,
template_object.shape[::-1],
interpolation=cv2.INTER_CUBIC)
ssim = compare_ssim(resized_target, template_object)
resp.append("conf", self.__dict__)
resp.append("ssim", ssim, important=True)
resp.append("ok", True, important=True)
return resp
def execute(
self,
template_object: np.ndarray,
target_object: np.ndarray,
engine_ocr_offset: int = None,
engine_ocr_deep: bool = None,
*_,
**__,
) -> FindItEngineResponse:
resp = FindItEngineResponse()
if engine_ocr_offset:
self.engine_ocr_offset = engine_ocr_offset
if engine_ocr_deep:
self.engine_ocr_deep = engine_ocr_deep
# _ft is not JSON serializable
conf_dict = {k: _ for k, _ in self.__dict__.items() if k != "_ft"}
resp.append("conf", conf_dict, important=True)
# check language
for each_lang in self.engine_ocr_lang.split("+"):
if each_lang not in self.engine_ocr_available_lang_list:
resp.append("raw",
"this language not available",
important=True)
resp.append("ok", False, important=True)
return resp
word_block_list = self._ft.find_word(
image_object=target_object,
deep=self.engine_ocr_deep,
offset=self.engine_ocr_offset,
)
available_result_list = [i for i in word_block_list if i.content]
result_text = self._improve_text_result(
[i.content for i in available_result_list])
resp.append("content", result_text, important=True)
resp.append("raw", [i.__dict__ for i in word_block_list])
resp.append("ok", True, important=True)
return resp
def execute(
self,
template_object: np.ndarray,
target_object: np.ndarray,
engine_template_mask_pic_object: np.ndarray = None,
engine_template_mask_pic_path: str = None,
*_,
**__,
) -> FindItEngineResponse:
resp = FindItEngineResponse()
resp.append("conf", self.__dict__)
# mask
if (engine_template_mask_pic_path
is not None) or (engine_template_mask_pic_object is not None):
logger.info("mask detected")
engine_template_mask_pic_object = toolbox.pre_pic(
engine_template_mask_pic_path, engine_template_mask_pic_object)
# template matching
min_val, max_val, min_loc, max_loc, point_list = self._compare_template(
template_object,
target_object,
self.engine_template_scale,
engine_template_mask_pic_object,
)
# 'target_point' must existed
resp.append("target_point", max_loc, important=True)
resp.append("target_sim", max_val, important=True)
resp.append(
"raw",
{
"min_val": min_val,
"max_val": max_val,
"min_loc": min_loc,
"max_loc": max_loc,
"all": point_list,
},
)
resp.append("ok", True, important=True)
return resp
def execute(self, template_object: np.ndarray, target_object: np.ndarray,
*_, **__) -> FindItEngineResponse:
resp = FindItEngineResponse()
resp.append('conf', self.__dict__)
point_list = self.get_feature_point_list(template_object,
target_object)
# no point found
if not point_list:
resp.append('target_point', (-1, -1), important=True)
resp.append('raw', 'not found')
resp.append('ok', False, important=True)
return resp
center_point = self.calculate_center_point(point_list)
readable_center_point = list(center_point)
readable_point_list = [list(each) for each in point_list]
resp.append('target_point', readable_center_point, important=True)
resp.append('feature_point_num',
len(readable_point_list),
important=True)
resp.append('raw', readable_point_list)
resp.append('ok', True, important=True)
return resp
def execute(self,
template_object: np.ndarray,
target_object: np.ndarray,
engine_template_mask_pic_object: np.ndarray = None,
engine_template_mask_pic_path: str = None,
*_,
**__) -> FindItEngineResponse:
resp = FindItEngineResponse()
resp.append('conf', self.__dict__)
# mask
if (engine_template_mask_pic_path
is not None) or (engine_template_mask_pic_object is not None):
logger.info('mask detected')
engine_template_mask_pic_object = toolbox.pre_pic(
engine_template_mask_pic_path, engine_template_mask_pic_object)
# template matching
min_val, max_val, min_loc, max_loc, point_list = self._compare_template(
template_object, target_object, self.engine_template_scale,
engine_template_mask_pic_object)
# 'target_point' must existed
resp.append('target_point', max_loc, important=True)
resp.append('target_sim', max_val, important=True)
resp.append(
'raw', {
'min_val': min_val,
'max_val': max_val,
'min_loc': min_loc,
'max_loc': max_loc,
'all': point_list,
})
resp.append('ok', True, important=True)
return resp