def test_annotations_from_bounding_box_predictions():
bbox_1 = BoundingBoxPrediction(0, 0, 10, 100, 0.99)
bbox_2 = BoundingBoxPrediction(500, 500, 100, 10, 0.99)
annotations = Annotations.from_bounding_boxes_predictions(
MUSEUM_NUMBER, [bbox_1, bbox_2], 1000, 1000)
assert annotations.annotations[0].geometry == Geometry(0.0, 0.0, 1.0, 10.0)
assert annotations.annotations[1].geometry == Geometry(
50.0, 50.0, 10.0, 1.0)
def generate_annotations(self,
number: MuseumNumber,
fragment_image: File,
threshold: float = 0.3) -> Annotations:
image_bytes = fragment_image.read()
buf = BytesIO(image_bytes)
width, height = Image.open(buf).size
bounding_boxes_predictions = self._request_generate_annotations(
buf.getvalue())
bounding_boxes_predictions = list(
filter(lambda bbox: bbox.probability >= threshold,
bounding_boxes_predictions))
return Annotations.from_bounding_boxes_predictions(
number, bounding_boxes_predictions, height, width)