qurator-spk
/
sbb_textline_detection
mirror of https://github.com/qurator-spk/sbb_textline_detection.git
1
0
Fork 0
Code Issues Releases Wiki Activity

Merge pull request #5 from cneud/cneud-fix-typos

Browse Source 
Fix typos
pull/2/head^2
Clemens Neudecker 5 years ago committed by GitHub
parent 12c07f389d 6c0bfba686
commit 51e241fd84
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 7 additions and 7 deletions
Show Stats Download Patch File Download Diff File

14
qurator/sbb_textline_detector/main.py
Unescape Escape View File

@ -70,7 +70,7 @@ class textlineerkenner:
np.array([point for point in polygon.exterior.coords], dtype=np.uint)) np.array([point for point in polygon.exterior.coords], dtype=np.uint))
return found_polygons_early return found_polygons_early
def filter_contours_area_of_image(self, image, contours, hirarchy, max_area, min_area): def filter_contours_area_of_image(self, image, contours, hierarchy, max_area, min_area):
found_polygons_early = list() found_polygons_early = list()
jv = 0 jv = 0
@ -81,13 +81,13 @@ class textlineerkenner:
polygon = geometry.Polygon([point[0] for point in c]) polygon = geometry.Polygon([point[0] for point in c])
area = polygon.area area = polygon.area
if area >= min_area * np.prod(image.shape[:2]) and area <= max_area * np.prod( if area >= min_area * np.prod(image.shape[:2]) and area <= max_area * np.prod(
image.shape[:2]) and hirarchy[0][jv][3] == -1 : # and hirarchy[0][jv][3]==-1 : image.shape[:2]) and hierarchy[0][jv][3] == -1 : # and hierarchy[0][jv][3]==-1 :
found_polygons_early.append( found_polygons_early.append(
np.array([ [point] for point in polygon.exterior.coords], dtype=np.uint)) np.array([ [point] for point in polygon.exterior.coords], dtype=np.uint))
jv += 1 jv += 1
return found_polygons_early return found_polygons_early
def filter_contours_area_of_image_interiors(self, image, contours, hirarchy, max_area, min_area): def filter_contours_area_of_image_interiors(self, image, contours, hierarchy, max_area, min_area):
found_polygons_early = list() found_polygons_early = list()
jv = 0 jv = 0
@ -98,7 +98,7 @@ class textlineerkenner:
polygon = geometry.Polygon([point[0] for point in c]) polygon = geometry.Polygon([point[0] for point in c])
area = polygon.area area = polygon.area
if area >= min_area * np.prod(image.shape[:2]) and area <= max_area * np.prod(image.shape[:2]) and \ if area >= min_area * np.prod(image.shape[:2]) and area <= max_area * np.prod(image.shape[:2]) and \
hirarchy[0][jv][3] != -1: hierarchy[0][jv][3] != -1:
# print(c[0][0][1]) # print(c[0][0][1])
found_polygons_early.append( found_polygons_early.append(
np.array([point for point in polygon.exterior.coords], dtype=np.uint)) np.array([point for point in polygon.exterior.coords], dtype=np.uint))
@ -486,9 +486,9 @@ class textlineerkenner:
_, thresh = cv2.threshold(imgray, 0, 255, 0) _, thresh = cv2.threshold(imgray, 0, 255, 0)
contours, hirarchy = cv2.findContours(thresh.copy(), cv2.cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) contours, hierarchy = cv2.findContours(thresh.copy(), cv2.cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
main_contours = self.filter_contours_area_of_image(thresh, contours, hirarchy, max_area=1, min_area=0.00001) main_contours = self.filter_contours_area_of_image(thresh, contours, hierarchy, max_area=1, min_area=0.00001)
self.boxes = [] self.boxes = []
for jj in range(len(main_contours)): for jj in range(len(main_contours)):
@ -1378,7 +1378,7 @@ class textlineerkenner:
def run(self): def run(self):
#get image and sclaes, then extract the page of scanned image #get image and scales, then extract the page of scanned image
t1=time.time() t1=time.time()
self.get_image_and_scales() self.get_image_and_scales()
image_page,page_coord=self.extract_page() image_page,page_coord=self.extract_page()

Write Preview
Loading…
Cancel
Save