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eynollah
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rename: image_{dir,filename}, {f_name,image_filename_stem}

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pull/19/head
Konstantin Baierer 4 years ago
parent 2bef2d4c04
commit 19895b0194
1 changed files with 41 additions and 41 deletions
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sbb_newspapers_org_image/eynollah.py
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@ -123,8 +123,8 @@ SLOPE_THRESHOLD = 0.13
class eynollah:
def __init__(
self,
image_dir,
f_name,
image_filename,
image_filename_stem,
dir_out,
dir_models,
dir_of_cropped_images=None,
@ -137,9 +137,9 @@ class eynollah:
allow_scaling=False,
headers_off=False
):
self.image_dir = image_dir # XXX This does not seem to be a directory as the name suggests, but a file
self.image_filename = image_filename # XXX This does not seem to be a directory as the name suggests, but a file
self.dir_out = dir_out
self.f_name = f_name
self.image_filename_stem = image_filename_stem
self.dir_of_cropped_images = dir_of_cropped_images
self.allow_enhancement = allow_enhancement
self.curved_line = curved_line
@ -149,8 +149,8 @@ class eynollah:
self.headers_off = headers_off
self.dir_of_deskewed = dir_of_deskewed
self.dir_of_all = dir_of_all
if not self.f_name:
self.f_name = Path(Path(image_dir).name).stem
if not self.image_filename_stem:
self.image_filename_stem = Path(Path(image_filename).name).stem
self.dir_models = dir_models
self.kernel = np.ones((5, 5), np.uint8)
@ -291,18 +291,18 @@ class eynollah:
return prediction_true
def check_dpi(self):
dpi = os.popen('identify -format "%x " ' + self.image_dir).read()
dpi = os.popen('identify -format "%x " ' + self.image_filename).read()
return int(float(dpi))
def resize_image_with_column_classifier(self, is_image_enhanced):
dpi = self.check_dpi()
img = cv2.imread(self.image_dir)
img = cv2.imread(self.image_filename)
img = img.astype(np.uint8)
_, page_coord = self.early_page_for_num_of_column_classification()
model_num_classifier, session_col_classifier = self.start_new_session_and_model(self.model_dir_of_col_classifier)
img_1ch = cv2.imread(self.image_dir, 0)
img_1ch = cv2.imread(self.image_filename, 0)
width_early = img_1ch.shape[1]
@ -414,14 +414,14 @@ class eynollah:
def resize_and_enhance_image_with_column_classifier(self, is_image_enhanced):
dpi = self.check_dpi()
img = cv2.imread(self.image_dir)
img = cv2.imread(self.image_filename)
img = img.astype(np.uint8)
_, page_coord = self.early_page_for_num_of_column_classification()
model_num_classifier, session_col_classifier = self.start_new_session_and_model(self.model_dir_of_col_classifier)
img_1ch = cv2.imread(self.image_dir, 0)
img_1ch = cv2.imread(self.image_filename, 0)
img_1ch = img_1ch.astype(np.uint8)
width_early = img_1ch.shape[1]
@ -538,7 +538,7 @@ class eynollah:
# img_new=resize_image(img,img_h_new,img_w_new)
image_res = self.predict_enhancement(img_new)
# cv2.imwrite(os.path.join(self.dir_out, self.f_name) + ".tif",self.image)
# cv2.imwrite(os.path.join(self.dir_out, self.image_filename_stem) + ".tif",self.image)
# self.image=self.image.astype(np.uint16)
# self.scale_x=1
@ -553,7 +553,7 @@ class eynollah:
img_w_new=int(img.shape[1]/float(img.shape[0]) * 3000)
img_new=resize_image(img,img_h_new,img_w_new)
image_res=self.predict_enhancement(img_new)
#cv2.imwrite(os.path.join(self.dir_out, self.f_name) + ".tif",self.image)
#cv2.imwrite(os.path.join(self.dir_out, self.image_filename_stem) + ".tif",self.image)
#self.image=self.image.astype(np.uint16)
##self.scale_x=1
##self.scale_y=1
@ -588,7 +588,7 @@ class eynollah:
def get_image_and_scales_after_enhancing(self, img_org, img_res):
# self.image = cv2.imread(self.image_dir)
# self.image = cv2.imread(self.image_filename)
self.image = np.copy(img_res)
self.image = self.image.astype(np.uint8)
@ -783,7 +783,7 @@ class eynollah:
return prediction_true
def early_page_for_num_of_column_classification(self):
img = cv2.imread(self.image_dir)
img = cv2.imread(self.image_filename)
img = img.astype(np.uint8)
patches = False
model_page, session_page = self.start_new_session_and_model(self.model_page_dir)
@ -1166,7 +1166,7 @@ class eynollah:
img_int_p[img_int_p > 0] = 1
# slope_for_all=self.return_deskew_slope_new(img_int_p,sigma_des)
slope_for_all = return_deskew_slop(img_int_p, sigma_des, dir_of_all=self.dir_of_all, f_name=self.f_name)
slope_for_all = return_deskew_slop(img_int_p, sigma_des, dir_of_all=self.dir_of_all, image_filename_stem=self.image_filename_stem)
if abs(slope_for_all) < 0.5:
slope_for_all = [slope_deskew][0]
@ -1177,7 +1177,7 @@ class eynollah:
except:
slope_for_all = 999
##slope_for_all=return_deskew_slop(img_int_p,sigma_des, dir_of_all=self.dir_of_all, f_name=self.f_name)
##slope_for_all=return_deskew_slop(img_int_p,sigma_des, dir_of_all=self.dir_of_all, image_filename_stem=self.image_filename_stem)
if slope_for_all == 999:
slope_for_all = [slope_deskew][0]
@ -1207,7 +1207,7 @@ class eynollah:
textline_biggest_region = mask_biggest * textline_mask_tot_ea
# print(slope_for_all,'slope_for_all')
textline_rotated_seperated = seperate_lines_new2(textline_biggest_region[y : y + h, x : x + w], 0, num_col, slope_for_all, self.dir_of_all, self.f_name)
textline_rotated_seperated = seperate_lines_new2(textline_biggest_region[y : y + h, x : x + w], 0, num_col, slope_for_all, self.dir_of_all, self.image_filename_stem)
# new line added
##print(np.shape(textline_rotated_seperated),np.shape(mask_biggest))
@ -1329,7 +1329,7 @@ class eynollah:
img_int_p[img_int_p > 0] = 1
# slope_for_all=self.return_deskew_slope_new(img_int_p,sigma_des)
slope_for_all = return_deskew_slop(img_int_p, sigma_des, dir_of_all=self.dir_of_all, f_name=self.f_name)
slope_for_all = return_deskew_slop(img_int_p, sigma_des, dir_of_all=self.dir_of_all, image_filename_stem=self.image_filename_stem)
if abs(slope_for_all) <= 0.5:
slope_for_all = [slope_deskew][0]
@ -1337,7 +1337,7 @@ class eynollah:
except:
slope_for_all = 999
##slope_for_all=return_deskew_slop(img_int_p,sigma_des, dir_of_all=self.dir_of_all, f_name=self.f_name)
##slope_for_all=return_deskew_slop(img_int_p,sigma_des, dir_of_all=self.dir_of_all, image_filename_stem=self.image_filename_stem)
if slope_for_all == 999:
slope_for_all = [slope_deskew][0]
@ -1450,7 +1450,7 @@ class eynollah:
sigma_des = 1
crop_img[crop_img > 0] = 1
slope_corresponding_textregion = return_deskew_slop(crop_img, sigma_des, dir_of_all=self.dir_of_all, f_name=self.f_name)
slope_corresponding_textregion = return_deskew_slop(crop_img, sigma_des, dir_of_all=self.dir_of_all, image_filename_stem=self.image_filename_stem)
except:
slope_corresponding_textregion = 999
@ -1478,7 +1478,7 @@ class eynollah:
found_polygons_text_region_h = contours_h
# create the file structure
pcgts, page = create_page_xml(self.image_dir, self.height_org, self.width_org)
pcgts, page = create_page_xml(self.image_filename, self.height_org, self.width_org)
page_print_sub = ET.SubElement(page, "PrintSpace")
coord_page = ET.SubElement(page_print_sub, "Coords")
@ -1995,7 +1995,7 @@ class eynollah:
print(self.f_name)
print(os.path.join(dir_of_image, self.f_name) + ".xml")
tree = ET.ElementTree(pcgts)
tree.write(os.path.join(dir_of_image, self.f_name) + ".xml")
tree.write(os.path.join(dir_of_image, self.image_filename_stem) + ".xml")
def write_into_page_xml(self, contours, page_coord, dir_of_image, order_of_texts, id_of_texts, all_found_texline_polygons, all_box_coord, found_polygons_text_region_img, found_polygons_marginals, all_found_texline_polygons_marginals, all_box_coord_marginals, curved_line, slopes, slopes_marginals):
@ -2004,7 +2004,7 @@ class eynollah:
##found_polygons_text_region_h=contours_h
# create the file structure
pcgts, page = create_page_xml(self.image_dir, self.height_org, self.width_org)
pcgts, page = create_page_xml(self.image_filename, self.height_org, self.width_org)
page_print_sub = ET.SubElement(page, "PrintSpace")
coord_page = ET.SubElement(page_print_sub, "Coords")
points_page_print = ""
@ -2310,11 +2310,11 @@ class eynollah:
pass
print(self.f_name)
# print(os.path.join(dir_of_image, self.f_name) + ".xml")
print(self.image_filename_stem)
# print(os.path.join(dir_of_image, self.image_filename_stem) + ".xml")
tree = ET.ElementTree(pcgts)
tree.write(os.path.join(dir_of_image, self.f_name) + ".xml")
# cv2.imwrite(os.path.join(dir_of_image, self.f_name) + ".tif",self.image_org)
tree.write(os.path.join(dir_of_image, self.image_filename_stem) + ".xml")
# cv2.imwrite(os.path.join(dir_of_image, self.image_filename_stem) + ".tif",self.image_org)
def get_regions_from_xy_2models(self,img,is_image_enhanced):
img_org=np.copy(img)
@ -2597,7 +2597,7 @@ class eynollah:
croped_page = resize_image(croped_page, int(croped_page.shape[0] / self.scale_y), int(croped_page.shape[1] / self.scale_x))
path = os.path.join(dir_of_cropped_imgs, self.f_name + "_" + str(index) + ".jpg")
path = os.path.join(dir_of_cropped_imgs, self.image_filename_stem + "_" + str(index) + ".jpg")
cv2.imwrite(path, croped_page)
index += 1
@ -2898,7 +2898,7 @@ class eynollah:
colors = [im.cmap(im.norm(value)) for value in values]
patches = [mpatches.Patch(color=colors[np.where(values == i)[0][0]], label="{l}".format(l=pixels[int(np.where(values_indexes == i)[0][0])])) for i in values]
plt.legend(handles=patches, bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.0, fontsize=40)
plt.savefig(os.path.join(self.dir_of_layout, self.f_name + "_layout_main.png"))
plt.savefig(os.path.join(self.dir_of_layout, self.image_filename_stem + "_layout_main.png"))
def save_plot_of_layout_main_all(self, text_regions_p, image_page):
values = np.unique(text_regions_p[:, :])
@ -2918,7 +2918,7 @@ class eynollah:
patches = [mpatches.Patch(color=colors[np.where(values == i)[0][0]], label="{l}".format(l=pixels[int(np.where(values_indexes == i)[0][0])])) for i in values]
plt.legend(handles=patches, bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.0, fontsize=60)
plt.savefig(os.path.join(self.dir_of_all, self.f_name + "_layout_main_and_page.png"))
plt.savefig(os.path.join(self.dir_of_all, self.image_filename_stem + "_layout_main_and_page.png"))
def save_plot_of_layout(self, text_regions_p, image_page):
values = np.unique(text_regions_p[:, :])
@ -2933,7 +2933,7 @@ class eynollah:
colors = [im.cmap(im.norm(value)) for value in values]
patches = [mpatches.Patch(color=colors[np.where(values == i)[0][0]], label="{l}".format(l=pixels[int(np.where(values_indexes == i)[0][0])])) for i in values]
plt.legend(handles=patches, bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.0, fontsize=40)
plt.savefig(os.path.join(self.dir_of_layout, self.f_name + "_layout.png"))
plt.savefig(os.path.join(self.dir_of_layout, self.image_filename_stem + "_layout.png"))
def save_plot_of_layout_all(self, text_regions_p, image_page):
values = np.unique(text_regions_p[:, :])
@ -2953,15 +2953,15 @@ class eynollah:
patches = [mpatches.Patch(color=colors[np.where(values == i)[0][0]], label="{l}".format(l=pixels[int(np.where(values_indexes == i)[0][0])])) for i in values]
plt.legend(handles=patches, bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.0, fontsize=60)
plt.savefig(os.path.join(self.dir_of_all, self.f_name + "_layout_and_page.png"))
plt.savefig(os.path.join(self.dir_of_all, self.image_filename_stem + "_layout_and_page.png"))
def save_deskewed_image(self, slope_deskew):
img_rotated = rotyate_image_different(self.image_org, slope_deskew)
if self.dir_of_all is not None:
cv2.imwrite(os.path.join(self.dir_of_all, self.f_name + "_org.png"), self.image_org)
cv2.imwrite(os.path.join(self.dir_of_all, self.image_filename_stem + "_org.png"), self.image_org)
cv2.imwrite(os.path.join(self.dir_of_deskewed, self.f_name + "_deskewed.png"), img_rotated)
cv2.imwrite(os.path.join(self.dir_of_deskewed, self.image_filename_stem + "_deskewed.png"), img_rotated)
del img_rotated
def run(self):
@ -2978,7 +2978,7 @@ class eynollah:
K.clear_session()
scale = 1
if (self.allow_enhancement) and is_image_enhanced:
cv2.imwrite(os.path.join(self.dir_out, self.f_name) + ".tif", img_res)
cv2.imwrite(os.path.join(self.dir_out, self.image_filename_stem) + ".tif", img_res)
img_res = img_res.astype(np.uint8)
self.get_image_and_scales(img_org, img_res, scale)
@ -3004,7 +3004,7 @@ class eynollah:
print("textregion: " + str(time.time() - t1))
img_g = cv2.imread(self.image_dir, 0)
img_g = cv2.imread(self.image_filename, 0)
img_g = img_g.astype(np.uint8)
img_g3 = np.zeros((img_g.shape[0], img_g.shape[1], 3))
@ -3021,7 +3021,7 @@ class eynollah:
# print(image_page.shape,'page')
if self.dir_of_all is not None:
cv2.imwrite(os.path.join(self.dir_of_all, self.f_name + "_page.png"), image_page)
cv2.imwrite(os.path.join(self.dir_of_all, self.image_filename_stem + "_page.png"), image_page)
##########
K.clear_session()
gc.collect()
@ -3094,7 +3094,7 @@ class eynollah:
patches = [mpatches.Patch(color=colors[np.where(values == i)[0][0]], label="{l}".format(l=pixels[int(np.where(values_indexes == i)[0][0])])) for i in values]
plt.legend(handles=patches, bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.0, fontsize=60)
plt.savefig(os.path.join(self.dir_of_all, self.f_name + "_textline_and_page.png"))
plt.savefig(os.path.join(self.dir_of_all, self.image_filename_stem + "_textline_and_page.png"))
print("textline: " + str(time.time() - t1))
# plt.imshow(textline_mask_tot_ea)
# plt.show()
@ -3102,8 +3102,8 @@ class eynollah:
sigma = 2
main_page_deskew = True
slope_deskew = return_deskew_slop(cv2.erode(textline_mask_tot_ea, self.kernel, iterations=2), sigma, main_page_deskew, dir_of_all=self.dir_of_all, f_name=self.f_name)
slope_first = 0 # return_deskew_slop(cv2.erode(textline_mask_tot_ea, self.kernel, iterations=2),sigma, dir_of_all=self.dir_of_all, f_name=self.f_name)
slope_deskew = return_deskew_slop(cv2.erode(textline_mask_tot_ea, self.kernel, iterations=2), sigma, main_page_deskew, dir_of_all=self.dir_of_all, image_filename_stem=self.image_filename_stem)
slope_first = 0 # return_deskew_slop(cv2.erode(textline_mask_tot_ea, self.kernel, iterations=2),sigma, dir_of_all=self.dir_of_all, image_filename_stem=self.image_filename_stem)
if self.dir_of_deskewed is not None:
self.save_deskewed_image(slope_deskew)

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