Loading modules/textdetector/panel_finder.py 0 → 100644 +254 −0 Original line number Diff line number Diff line """ Finds panel order for manga page. >> python .\modules\textdetector\panel_finder.py <path-to-images> """ from pathlib import Path import sys import cv2 as cv import numpy as np from PIL import Image KERNEL_SIZE = 7 BORDER_SIZE = 10 def panel_process_image(img: Image.Image): """Preprocesses an image to make it easier to find panels. Args: img: The image to preprocess. Returns: The preprocessed image. """ img_gray = cv.cvtColor(np.array(img), cv.COLOR_BGR2GRAY) img_gray = cv.GaussianBlur(img_gray, (KERNEL_SIZE, KERNEL_SIZE), 0) img_gray = cv.threshold(img_gray, 200, 255, cv.THRESH_BINARY)[1] # Add black border to image, to help with finding contours img_gray = cv.copyMakeBorder( img_gray, BORDER_SIZE, BORDER_SIZE, BORDER_SIZE, BORDER_SIZE, cv.BORDER_CONSTANT, value=255, ) # Invert image img_gray = cv.bitwise_not(img_gray) return img_gray def remove_contained_contours(polygons): """Removes polygons from a list if any completely contain the other. Args: polygons: A list of polygons. Returns: A list of polygons with any contained polygons removed. """ # Create a new list to store the filtered polygons. filtered_polygons = [] # Iterate over the polygons. for polygon in polygons: # Check if the polygon contains any of the other polygons. contains = False for other_polygon in polygons: # Check if the polygon contains the other polygon and that the polygons if np.array_equal(other_polygon, polygon): continue rect1 = cv.boundingRect(other_polygon) rect2 = cv.boundingRect(polygon) # Check if rect2 is completely within rect1 if ( rect2[0] >= rect1[0] and rect2[1] >= rect1[1] and rect2[0] + rect2[2] <= rect1[0] + rect1[2] and rect2[1] + rect2[3] <= rect1[1] + rect1[3] ): contains = True break # If the polygon does not contain any of the other polygons, add it to the # filtered list. if not contains: filtered_polygons.append(polygon) return filtered_polygons def calc_panel_contours(im: Image.Image): img_gray = panel_process_image(im) contours_raw, hierarchy = cv.findContours( img_gray, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE ) contours = contours_raw min_area = 10000 contours = [i for i in contours if cv.contourArea(i) > min_area] contours = [cv.convexHull(i) for i in contours] contours = remove_contained_contours(contours) # Remap the contours to the original image contours = [i + np.array([[-BORDER_SIZE, -BORDER_SIZE]]) for i in contours] # Sort the contours by their y-coordinate. contours = order_panels(contours, img_gray) return contours def determine_panel_order_from_contours(contours): """ build a tree of regions that are determined vertically order by an n like pattern """ def draw_contours(im, contours): """Debugging, draws the contours on the image.""" colors = [ (255, 0, 0), (0, 255, 0), (0, 0, 255), ] im_contour = np.array(im) for i, contour in enumerate(range(len(contours))): color = colors[i % len(colors)] im_contour = cv.drawContours(im_contour, contours, i, color, 4, cv.LINE_AA) # Draw a number at the top left of contour x, y, _, _ = cv.boundingRect(contours[i]) cv.putText( im_contour, str(i), (x + 50, y + 50), cv.FONT_HERSHEY_SIMPLEX, 1, color, 2, cv.LINE_AA, ) img = Image.fromarray(im_contour) return img def save_draw_contours(pth: Path | str): if str: pth = Path(pth) pth_out = pth.parent / (pth.stem + "-contours") if not pth_out.exists(): pth_out.mkdir() # Glob get all images in folder pths = [i for i in pth.iterdir() if i.suffix in [".png", ".jpg", ".jpeg"]] for t in pths: print(t) im = Image.open(t) contours = calc_panel_contours(im) img_panels = draw_contours(im, contours) f_name = t.stem + t.suffix img_panels.save(pth_out / f_name) def order_panels(contours, img_gray): """Orders the panels in a comic book page. Args: contours: A list of contours, where each contour is a list of points. Returns: A list of contours, where each contour is a list of points, ordered by their vertical position. """ # Get the bounding boxes for each contour. bounding_boxes = [cv.boundingRect(contour) for contour in contours] # Generate groups of vertically overlapping bounding boxes. groups_indices = generate_vertical_bounding_box_groups_indices(bounding_boxes) c = [] for group in groups_indices: # Reorder contours based on reverse z-order, cs = [bounding_boxes[i] for i in group] ymax, xmax = img_gray.shape order_scores = [1 * (ymax - i[1]) + i[0] * 1 for i in cs] # Sort the list based on the location score value combined_list = list(zip(group, order_scores)) sorted_list = sorted(combined_list, key=lambda x: x[1], reverse=True) c.extend(sorted_list) ordered_contours = [contours[i[0]] for i in c] return ordered_contours def generate_vertical_bounding_box_groups_indices(bounding_boxes): """Generates groups of vertically overlapping bounding boxes. Args: bounding_boxes: A list of bounding boxes, where each bounding box is a tuple of (x, y, width, height). Returns: A list of groups, where each group is a list of bounding boxes that overlap vertically. """ # Operate on indices Sort the bounding boxes by their y-coordinate. bbox_inds = np.argsort([i[1] for i in bounding_boxes]) # generate groups of vertically overlapping bounding boxes groups = [[bbox_inds[0]]] for i in bbox_inds[1:]: is_old_group = False bbox = bounding_boxes[i] start1 = bbox[1] end1 = bbox[1] + bbox[3] for n, group in enumerate(groups): for ind in group: _bbox = bounding_boxes[ind] start2 = _bbox[1] end2 = _bbox[1] + _bbox[3] # Check for any partial overlapping if check_overlap((start1, end1), (start2, end2)): groups[n] = group + [i] is_old_group = True break if is_old_group: break else: groups.append([i]) return groups def check_overlap(range1, range2): # Check if range1 is before range2 if range1[1] < range2[0]: return False # Check if range1 is after range2 elif range1[0] > range2[1]: return False # If neither of the above conditions are met, the ranges must overlap else: return True if __name__ == "__main__": save_draw_contours(sys.argv[1]) Loading
modules/textdetector/panel_finder.py 0 → 100644 +254 −0 Original line number Diff line number Diff line """ Finds panel order for manga page. >> python .\modules\textdetector\panel_finder.py <path-to-images> """ from pathlib import Path import sys import cv2 as cv import numpy as np from PIL import Image KERNEL_SIZE = 7 BORDER_SIZE = 10 def panel_process_image(img: Image.Image): """Preprocesses an image to make it easier to find panels. Args: img: The image to preprocess. Returns: The preprocessed image. """ img_gray = cv.cvtColor(np.array(img), cv.COLOR_BGR2GRAY) img_gray = cv.GaussianBlur(img_gray, (KERNEL_SIZE, KERNEL_SIZE), 0) img_gray = cv.threshold(img_gray, 200, 255, cv.THRESH_BINARY)[1] # Add black border to image, to help with finding contours img_gray = cv.copyMakeBorder( img_gray, BORDER_SIZE, BORDER_SIZE, BORDER_SIZE, BORDER_SIZE, cv.BORDER_CONSTANT, value=255, ) # Invert image img_gray = cv.bitwise_not(img_gray) return img_gray def remove_contained_contours(polygons): """Removes polygons from a list if any completely contain the other. Args: polygons: A list of polygons. Returns: A list of polygons with any contained polygons removed. """ # Create a new list to store the filtered polygons. filtered_polygons = [] # Iterate over the polygons. for polygon in polygons: # Check if the polygon contains any of the other polygons. contains = False for other_polygon in polygons: # Check if the polygon contains the other polygon and that the polygons if np.array_equal(other_polygon, polygon): continue rect1 = cv.boundingRect(other_polygon) rect2 = cv.boundingRect(polygon) # Check if rect2 is completely within rect1 if ( rect2[0] >= rect1[0] and rect2[1] >= rect1[1] and rect2[0] + rect2[2] <= rect1[0] + rect1[2] and rect2[1] + rect2[3] <= rect1[1] + rect1[3] ): contains = True break # If the polygon does not contain any of the other polygons, add it to the # filtered list. if not contains: filtered_polygons.append(polygon) return filtered_polygons def calc_panel_contours(im: Image.Image): img_gray = panel_process_image(im) contours_raw, hierarchy = cv.findContours( img_gray, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE ) contours = contours_raw min_area = 10000 contours = [i for i in contours if cv.contourArea(i) > min_area] contours = [cv.convexHull(i) for i in contours] contours = remove_contained_contours(contours) # Remap the contours to the original image contours = [i + np.array([[-BORDER_SIZE, -BORDER_SIZE]]) for i in contours] # Sort the contours by their y-coordinate. contours = order_panels(contours, img_gray) return contours def determine_panel_order_from_contours(contours): """ build a tree of regions that are determined vertically order by an n like pattern """ def draw_contours(im, contours): """Debugging, draws the contours on the image.""" colors = [ (255, 0, 0), (0, 255, 0), (0, 0, 255), ] im_contour = np.array(im) for i, contour in enumerate(range(len(contours))): color = colors[i % len(colors)] im_contour = cv.drawContours(im_contour, contours, i, color, 4, cv.LINE_AA) # Draw a number at the top left of contour x, y, _, _ = cv.boundingRect(contours[i]) cv.putText( im_contour, str(i), (x + 50, y + 50), cv.FONT_HERSHEY_SIMPLEX, 1, color, 2, cv.LINE_AA, ) img = Image.fromarray(im_contour) return img def save_draw_contours(pth: Path | str): if str: pth = Path(pth) pth_out = pth.parent / (pth.stem + "-contours") if not pth_out.exists(): pth_out.mkdir() # Glob get all images in folder pths = [i for i in pth.iterdir() if i.suffix in [".png", ".jpg", ".jpeg"]] for t in pths: print(t) im = Image.open(t) contours = calc_panel_contours(im) img_panels = draw_contours(im, contours) f_name = t.stem + t.suffix img_panels.save(pth_out / f_name) def order_panels(contours, img_gray): """Orders the panels in a comic book page. Args: contours: A list of contours, where each contour is a list of points. Returns: A list of contours, where each contour is a list of points, ordered by their vertical position. """ # Get the bounding boxes for each contour. bounding_boxes = [cv.boundingRect(contour) for contour in contours] # Generate groups of vertically overlapping bounding boxes. groups_indices = generate_vertical_bounding_box_groups_indices(bounding_boxes) c = [] for group in groups_indices: # Reorder contours based on reverse z-order, cs = [bounding_boxes[i] for i in group] ymax, xmax = img_gray.shape order_scores = [1 * (ymax - i[1]) + i[0] * 1 for i in cs] # Sort the list based on the location score value combined_list = list(zip(group, order_scores)) sorted_list = sorted(combined_list, key=lambda x: x[1], reverse=True) c.extend(sorted_list) ordered_contours = [contours[i[0]] for i in c] return ordered_contours def generate_vertical_bounding_box_groups_indices(bounding_boxes): """Generates groups of vertically overlapping bounding boxes. Args: bounding_boxes: A list of bounding boxes, where each bounding box is a tuple of (x, y, width, height). Returns: A list of groups, where each group is a list of bounding boxes that overlap vertically. """ # Operate on indices Sort the bounding boxes by their y-coordinate. bbox_inds = np.argsort([i[1] for i in bounding_boxes]) # generate groups of vertically overlapping bounding boxes groups = [[bbox_inds[0]]] for i in bbox_inds[1:]: is_old_group = False bbox = bounding_boxes[i] start1 = bbox[1] end1 = bbox[1] + bbox[3] for n, group in enumerate(groups): for ind in group: _bbox = bounding_boxes[ind] start2 = _bbox[1] end2 = _bbox[1] + _bbox[3] # Check for any partial overlapping if check_overlap((start1, end1), (start2, end2)): groups[n] = group + [i] is_old_group = True break if is_old_group: break else: groups.append([i]) return groups def check_overlap(range1, range2): # Check if range1 is before range2 if range1[1] < range2[0]: return False # Check if range1 is after range2 elif range1[0] > range2[1]: return False # If neither of the above conditions are met, the ranges must overlap else: return True if __name__ == "__main__": save_draw_contours(sys.argv[1])
