qurator-spk/eynollah
1
0
Fork 0
mirror of https://github.com/qurator-spk/eynollah.git synced 2026-04-30 19:22:03 +02:00
Code Issues Projects Releases Wiki Activity

rotate: rm unused failed variants, add new rotate_image_enlarge…

Browse source 
(correct version that enlarges canvas instead of clipping corners,
 using only OpenCV)
This commit is contained in:
Robert Sachunsky 2026-04-23 20:46:05 +02:00
parent d257869d83
commit dbdb6d0d53
1 changed files with 16 additions and 62 deletions
Download patch file Download diff file Expand all files Collapse all files

78
src/eynollah/utils/rotate.py
View file

@ -1,36 +1,6 @@
import math
import cv2
def rotatedRectWithMaxArea(w, h, angle):
if w <= 0 or h <= 0:
return 0, 0
width_is_longer = w >= h
side_long, side_short = (w, h) if width_is_longer else (h, w)
# since the solutions for angle, -angle and 180-angle are all the same,
# if suffices to look at the first quadrant and the absolute values of sin,cos:
sin_a, cos_a = abs(math.sin(angle)), abs(math.cos(angle))
if side_short <= 2.0 * sin_a * cos_a * side_long or abs(sin_a - cos_a) < 1e-10:
# half constrained case: two crop corners touch the longer side,
# the other two corners are on the mid-line parallel to the longer line
x = 0.5 * side_short
wr, hr = (x / sin_a, x / cos_a) if width_is_longer else (x / cos_a, x / sin_a)
else:
# fully constrained case: crop touches all 4 sides
cos_2a = cos_a * cos_a - sin_a * sin_a
wr, hr = (w * cos_a - h * sin_a) / cos_2a, (h * cos_a - w * sin_a) / cos_2a
return wr, hr
def rotate_max_area_new(image, rotated, angle):
wr, hr = rotatedRectWithMaxArea(image.shape[1], image.shape[0], math.radians(angle))
h, w, _ = rotated.shape
y1 = h // 2 - int(hr / 2)
y2 = y1 + int(hr)
x1 = w // 2 - int(wr / 2)
x2 = x1 + int(wr)
return rotated[y1:y2, x1:x2]
def rotation_image_new(img, thetha):
rotated = rotate_image(img, thetha)
@ -50,35 +20,19 @@ def rotate_image_different( img, slope):
img_rotation = cv2.warpAffine(img, rotation_matrix, (num_cols, num_rows))
return img_rotation
def rotate_max_area(image, rotated, rotated_textline, rotated_layout, rotated_table_prediction, angle):
wr, hr = rotatedRectWithMaxArea(image.shape[1], image.shape[0], math.radians(angle))
h, w, _ = rotated.shape
y1 = h // 2 - int(hr / 2)
y2 = y1 + int(hr)
x1 = w // 2 - int(wr / 2)
x2 = x1 + int(wr)
return rotated[y1:y2, x1:x2], rotated_textline[y1:y2, x1:x2], rotated_layout[y1:y2, x1:x2], rotated_table_prediction[y1:y2, x1:x2]
def rotation_not_90_func(img, textline, text_regions_p_1, table_prediction, thetha):
rotated = rotate_image(img, thetha)
rotated_textline = rotate_image(textline, thetha)
rotated_layout = rotate_image(text_regions_p_1, thetha)
rotated_table_prediction = rotate_image(table_prediction, thetha)
return rotate_max_area(img, rotated, rotated_textline, rotated_layout, rotated_table_prediction, thetha)
def rotation_not_90_func_full_layout(img, textline, text_regions_p_1, text_regions_p_fully, thetha):
rotated = rotate_image(img, thetha)
rotated_textline = rotate_image(textline, thetha)
rotated_layout = rotate_image(text_regions_p_1, thetha)
rotated_layout_full = rotate_image(text_regions_p_fully, thetha)
return rotate_max_area_full_layout(img, rotated, rotated_textline, rotated_layout, rotated_layout_full, thetha)
def rotate_max_area_full_layout(image, rotated, rotated_textline, rotated_layout, rotated_layout_full, angle):
wr, hr = rotatedRectWithMaxArea(image.shape[1], image.shape[0], math.radians(angle))
h, w, _ = rotated.shape
y1 = h // 2 - int(hr / 2)
y2 = y1 + int(hr)
x1 = w // 2 - int(wr / 2)
x2 = x1 + int(wr)
return rotated[y1:y2, x1:x2], rotated_textline[y1:y2, x1:x2], rotated_layout[y1:y2, x1:x2], rotated_layout_full[y1:y2, x1:x2]
def rotate_image_enlarge(img, angle):
h, w = img.shape[:2]
cx, cy = 0.5 * w, 0.5 * h
matrix = cv2.getRotationMatrix2D((cx, cy), angle, 1.0)
radian = angle / 180 * math.pi
cos = abs(math.cos(radian))
sin = abs(math.sin(radian))
new_w, new_h = (w * cos + h * sin,
w * sin + h * cos)
# box is larger after resize, so instead of shifting
# back from center, shift from new center
matrix[0, 2] += 0.5 * new_w - cx
matrix[1, 2] += 0.5 * new_h - cy
return cv2.warpAffine(img, matrix, (int(new_w + 0.5),
int(new_h + 0.5)),
flags=cv2.INTER_CUBIC)