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Parameter to enable return of corrected zbar polygons #33

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Parameter to enable return of corrected zbar polygons #33

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67c972f
update to return zbar scanned poly in qr tuple
AlexSkillman10 Jul 22, 2024
d9f2da5
update to correct polygon for perspective shifts
AlexSkillman10 Jul 22, 2024
153c2a1
Merge branch 'Eric-Canas:main' into zbar-poly-return
AlexSkillman10 Jul 22, 2024
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68 changes: 66 additions & 2 deletions qreader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -54,6 +54,10 @@ class DecodeQRResult:
image: np.ndarray
result: Decoded

cropped_bbox: np.ndarray | None = None
cropped_quad: np.ndarray | None = None
corrected_perspective_values: tuple[np.ndarray, np.ndarray] | None = None


def wrap(
scale_factor: float,
Expand All @@ -62,6 +66,10 @@ def wrap(
blur_kernel_sizes: tuple[tuple[int, int], ...] | None,
image: np.ndarray,
results: typing.List[Decoded],

cropped_bbox: np.ndarray | None = None,
cropped_quad: np.ndarray | None = None,
corrected_perspective_values: tuple[np.ndarray, np.ndarray] | None = None
) -> list[DecodeQRResult]:

return [
Expand All @@ -72,6 +80,10 @@ def wrap(
blur_kernel_sizes=blur_kernel_sizes,
image=image,
result=result,

cropped_bbox=cropped_bbox,
cropped_quad=cropped_quad,
corrected_perspective_values = corrected_perspective_values,
)
for result in results
]
Expand Down Expand Up @@ -147,6 +159,7 @@ def detect(
bounding box in absolute coordinates, while 'bbox_xyxyn' is the bounding box in normalized coordinates
(from 0. to 1.).
"""

return self.detector.detect(image=image, is_bgr=is_bgr)

def decode(
Expand All @@ -155,6 +168,7 @@ def decode(
detection_result: dict[
str, np.ndarray | float | tuple[float | int, float | int]
],
return_zbar_poly: bool = False,
) -> str | None:
"""
This method decodes a single QR code on the given image, described by a detection_result.
Expand Down Expand Up @@ -188,11 +202,41 @@ def decode(
f"Double decoding failed for {self.reencode_to}. Returning utf-8 decoded string."
)

if return_zbar_poly:
polygon = decodeQRResult.result.polygon
if decodeQRResult.corrections == "cropped_bbox":
bbox_xyxy = decodeQRResult.cropped_bbox
x_offset, y_offset = bbox_xyxy[0], bbox_xyxy[1]
scale_factor = decodeQRResult.scale_factor
corrected_polygon = [
(point.x / scale_factor + x_offset, point.y / scale_factor + y_offset)
for point in polygon
]
return decoded_str, corrected_polygon
elif decodeQRResult.corrections == "corrected_perspective":
padded_quad_xy, dst_pts = decodeQRResult.corrected_perspective_values
M_inv = cv2.getPerspectiveTransform(dst_pts, padded_quad_xy)
corrected_polygon = cv2.perspectiveTransform(np.array([[(point.x, point.y) for point in polygon]], dtype=np.float32), M_inv)[0]
scale_factor = decodeQRResult.scale_factor
corrected_polygon = [
(point[0] / scale_factor, point[1] / scale_factor) for point in corrected_polygon
]
return decoded_str, corrected_polygon

else:
return decoded_str, None

return decoded_str
if return_zbar_poly:
return None, None
return None

def detect_and_decode(
self, image: np.ndarray, return_detections: bool = False, is_bgr: bool = False
self,
image: np.ndarray,
return_detections: bool = False,
is_bgr: bool = False,
return_zbar_poly: bool = False,
) -> (
tuple[
dict[str, np.ndarray | float | tuple[float | int, float | int]], str | None
Expand All @@ -217,7 +261,7 @@ def detect_and_decode(
"""
detections = self.detect(image=image, is_bgr=is_bgr)
decoded_qrs = tuple(
self.decode(image=image, detection_result=detection)
self.decode(image=image, detection_result=detection, return_zbar_poly=return_zbar_poly)
for detection in detections
)

Expand Down Expand Up @@ -313,6 +357,7 @@ def _decode_qr_zbar(
):
continue


rescaled_image = cv2.resize(
src=image,
dsize=None,
Expand All @@ -329,7 +374,11 @@ def _decode_qr_zbar(
blur_kernel_sizes=None,
image=rescaled_image,
results=decodedQR,

cropped_bbox=detection_result[BBOX_XYXY] if label == "cropped_bbox" else None,
corrected_perspective_values=(detection_result[PADDED_QUAD_XY], self.__get_dst_pts(corrected_perspective)) if label == "corrected_perspective" else None,
)

# For QRs with black background and white foreground, try to invert the image
inverted_image = image = 255 - rescaled_image
decodedQR = decodeQR(inverted_image, symbols=[ZBarSymbol.QRCODE])
Expand All @@ -341,6 +390,9 @@ def _decode_qr_zbar(
blur_kernel_sizes=None,
image=inverted_image,
results=decodedQR,

cropped_bbox=detection_result[BBOX_XYXY] if label == "cropped_bbox" else None,
corrected_perspective_values=(detection_result[PADDED_QUAD_XY], self.__get_dst_pts(corrected_perspective)) if label == "corrected_perspective" else None,
)

# If it not works, try to parse to grayscale (if it is not already)
Expand All @@ -362,6 +414,9 @@ def _decode_qr_zbar(
blur_kernel_sizes=((5, 5), (7, 7)),
image=gray,
results=decodedQR,

cropped_bbox=detection_result[BBOX_XYXY] if label == "cropped_bbox" else None,
corrected_perspective_values=(detection_result[PADDED_QUAD_XY], self.__get_dst_pts(corrected_perspective)) if label == "corrected_perspective" else None,
)

if len(rescaled_image.shape) == 3:
Expand All @@ -387,6 +442,9 @@ def _decode_qr_zbar(
blur_kernel_sizes=((3, 3),),
image=sharpened_gray,
results=decodedQR,

cropped_bbox=detection_result[BBOX_XYXY] if label == "cropped_bbox" else None,
corrected_perspective_values=(detection_result[PADDED_QUAD_XY], self.__get_dst_pts(corrected_perspective)) if label == "corrected_perspective" else None,
)

return []
Expand Down Expand Up @@ -436,6 +494,12 @@ def __correct_perspective(
dst_img = cv2.warpPerspective(image, M, (N, N))

return dst_img

def __get_dst_pts(self, corrected_perspective: np.ndarray) -> np.ndarray:
N = corrected_perspective.shape[0]
return np.array(
[[0, 0], [N - 1, 0], [N - 1, N - 1], [0, N - 1]], dtype=np.float32
)

def __threshold_and_blur_decodings(
self,
Expand Down
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