def _find_sift_in_predict_area(self, image, screen):
if not self.record_pos:
return None
# calc predict area in screen
image_wh, screen_resolution = aircv.get_resolution(
image), aircv.get_resolution(screen)
xmin, ymin, xmax, ymax = Predictor.get_predict_area(
self.record_pos, image_wh, self.resolution, screen_resolution)
# crop predict image from screen
predict_area = aircv.crop_image(screen, (xmin, ymin, xmax, ymax))
if not predict_area.any():
return None
# find sift in that image
ret_in_area = aircv.find_sift(predict_area,
image,
threshold=self.threshold,
rgb=self.rgb)
# calc cv ret if found
if not ret_in_area:
return None
ret = deepcopy(ret_in_area)
if "rectangle" in ret:
for idx, item in enumerate(ret["rectangle"]):
ret["rectangle"][idx] = (item[0] + xmin, item[1] + ymin)
ret["result"] = (ret_in_area["result"][0] + xmin,
ret_in_area["result"][1] + ymin)
return ret
def _find_sift_in_predict_area(self, image, screen):
if not self.record_pos:
return None
# calc predict area in screen
screen_resolution = aircv.get_resolution(screen)
xmin, ymin, xmax, ymax = Predictor.get_predict_area(self.record_pos, screen_resolution)
# crop predict image from screen
predict_area = aircv.crop_image(screen, (xmin, ymin, xmax, ymax))
# aircv.show(predict_area)
# find sift in that image
ret_in_area = aircv.find_sift(predict_area, image, threshold=self.threshold, rgb=self.rgb)
# calc cv ret if found
if not ret_in_area:
return None
ret = deepcopy(ret_in_area)
ret["result"] = (ret_in_area["result"][0] + xmin, ret_in_area["result"][1] + ymin)
return ret
def _find_sift(self, image, screen):
return aircv.find_sift(screen, image, threshold=self.threshold, rgb=self.rgb)
