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https://www.pyimagesearch.com/2015/04/06/zero-parameter-automatic-canny-edge-detection-with-python-and-opencv/
"""
import cv2
import numpy as np
from src.logger import logger
from src.processors.interfaces.ImagePreprocessor import ImagePreprocessor
from src.utils.image import ImageUtils
from src.utils.interaction import InteractionUtils
MIN_PAGE_AREA = 80000
def normalize(image):
return cv2.normalize(image, 0, 255, norm_type=cv2.NORM_MINMAX)
def check_max_cosine(approx):
# assumes 4 pts present
max_cosine = 0
min_cosine = 1.5
for i in range(2, 5):
cosine = abs(angle(approx[i % 4], approx[i - 2], approx[i - 1]))
max_cosine = max(cosine, max_cosine)
min_cosine = min(cosine, min_cosine)
if max_cosine >= 0.35:
logger.warning("Quadrilateral is not a rectangle.")
return False
return True
def validate_rect(approx):
return len(approx) == 4 and check_max_cosine(approx.reshape(4, 2))
def angle(p_1, p_2, p_0):
dx1 = float(p_1[0] - p_0[0])
dy1 = float(p_1[1] - p_0[1])
dx2 = float(p_2[0] - p_0[0])
dy2 = float(p_2[1] - p_0[1])
return (dx1 * dx2 + dy1 * dy2) / np.sqrt(
(dx1 * dx1 + dy1 * dy1) * (dx2 * dx2 + dy2 * dy2) + 1e-10
)
class CropPage(ImagePreprocessor):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
cropping_ops = self.options
self.morph_kernel = tuple(
int(x) for x in cropping_ops.get("morphKernel", [10, 10])
)
def apply_filter(self, image, file_path):
image = normalize(cv2.GaussianBlur(image, (3, 3), 0))
# Resize should be done with another preprocessor is needed
sheet = self.find_page(image, file_path)
if len(sheet) == 0:
logger.error(
f"\tError: Paper boundary not found for: '{file_path}'\nHave you accidentally included CropPage preprocessor?"
)
return None
logger.info(f"Found page corners: \t {sheet.tolist()}")
# Warp layer 1
image = ImageUtils.four_point_transform(image, sheet)
# Return preprocessed image
return image
def find_page(self, image, file_path):
config = self.tuning_config
image = normalize(image)
_ret, image = cv2.threshold(image, 200, 255, cv2.THRESH_TRUNC)
image = normalize(image)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, self.morph_kernel)
# Close the small holes, i.e. Complete the edges on canny image
closed = cv2.morphologyEx(image, cv2.MORPH_CLOSE, kernel)
edge = cv2.Canny(closed, 185, 55)
if config.outputs.show_image_level >= 5:
InteractionUtils.show("edge", edge, config=config)
# findContours returns outer boundaries in CW and inner ones, ACW.
cnts = ImageUtils.grab_contours(
cv2.findContours(edge, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
)
# convexHull to resolve disordered curves due to noise
cnts = [cv2.convexHull(c) for c in cnts]
cnts = sorted(cnts, key=cv2.contourArea, reverse=True)[:5]
sheet = []
for c in cnts:
if cv2.contourArea(c) < MIN_PAGE_AREA:
continue
peri = cv2.arcLength(c, True)
approx = cv2.approxPolyDP(c, epsilon=0.025 * peri, closed=True)
if validate_rect(approx):
sheet = np.reshape(approx, (4, -1))
cv2.drawContours(image, [approx], -1, (0, 255, 0), 2)
cv2.drawContours(edge, [approx], -1, (255, 255, 255), 10)
break
return sheet
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