mirror of
https://github.com/qurator-spk/sbb_pixelwise_segmentation.git
synced 2025-07-04 16:10:02 +02:00
addinh shifting augmentation
This commit is contained in:
parent
4150675621
commit
3ef865e0b5
2 changed files with 58 additions and 4 deletions
7
train.py
7
train.py
|
@ -50,6 +50,7 @@ def config_params():
|
||||||
padding_white = False # If true, white padding will be applied to the image.
|
padding_white = False # If true, white padding will be applied to the image.
|
||||||
padding_black = False # If true, black padding will be applied to the image.
|
padding_black = False # If true, black padding will be applied to the image.
|
||||||
scaling = False # If true, scaling will be applied to the image. The amount of scaling is defined with "scales" in config_params.json.
|
scaling = False # If true, scaling will be applied to the image. The amount of scaling is defined with "scales" in config_params.json.
|
||||||
|
shifting = False
|
||||||
degrading = False # If true, degrading will be applied to the image. The amount of degrading is defined with "degrade_scales" in config_params.json.
|
degrading = False # If true, degrading will be applied to the image. The amount of degrading is defined with "degrade_scales" in config_params.json.
|
||||||
brightening = False # If true, brightening will be applied to the image. The amount of brightening is defined with "brightness" in config_params.json.
|
brightening = False # If true, brightening will be applied to the image. The amount of brightening is defined with "brightness" in config_params.json.
|
||||||
binarization = False # If true, Otsu thresholding will be applied to augment the input with binarized images.
|
binarization = False # If true, Otsu thresholding will be applied to augment the input with binarized images.
|
||||||
|
@ -104,7 +105,7 @@ def run(_config, n_classes, n_epochs, input_height,
|
||||||
input_width, weight_decay, weighted_loss,
|
input_width, weight_decay, weighted_loss,
|
||||||
index_start, dir_of_start_model, is_loss_soft_dice,
|
index_start, dir_of_start_model, is_loss_soft_dice,
|
||||||
n_batch, patches, augmentation, flip_aug,
|
n_batch, patches, augmentation, flip_aug,
|
||||||
blur_aug, padding_white, padding_black, scaling, degrading,channels_shuffling,
|
blur_aug, padding_white, padding_black, scaling, shifting, degrading,channels_shuffling,
|
||||||
brightening, binarization, adding_rgb_background, adding_rgb_foreground, add_red_textlines, blur_k, scales, degrade_scales,shuffle_indexes,
|
brightening, binarization, adding_rgb_background, adding_rgb_foreground, add_red_textlines, blur_k, scales, degrade_scales,shuffle_indexes,
|
||||||
brightness, dir_train, data_is_provided, scaling_bluring,
|
brightness, dir_train, data_is_provided, scaling_bluring,
|
||||||
scaling_brightness, scaling_binarization, rotation, rotation_not_90,
|
scaling_brightness, scaling_binarization, rotation, rotation_not_90,
|
||||||
|
@ -183,7 +184,7 @@ def run(_config, n_classes, n_epochs, input_height,
|
||||||
provide_patches(imgs_list, segs_list, dir_img, dir_seg, dir_flow_train_imgs,
|
provide_patches(imgs_list, segs_list, dir_img, dir_seg, dir_flow_train_imgs,
|
||||||
dir_flow_train_labels, input_height, input_width, blur_k,
|
dir_flow_train_labels, input_height, input_width, blur_k,
|
||||||
blur_aug, padding_white, padding_black, flip_aug, binarization, adding_rgb_background,adding_rgb_foreground, add_red_textlines, channels_shuffling,
|
blur_aug, padding_white, padding_black, flip_aug, binarization, adding_rgb_background,adding_rgb_foreground, add_red_textlines, channels_shuffling,
|
||||||
scaling, degrading, brightening, scales, degrade_scales, brightness,
|
scaling, shifting, degrading, brightening, scales, degrade_scales, brightness,
|
||||||
flip_index,shuffle_indexes, scaling_bluring, scaling_brightness, scaling_binarization,
|
flip_index,shuffle_indexes, scaling_bluring, scaling_brightness, scaling_binarization,
|
||||||
rotation, rotation_not_90, thetha, scaling_flip, task, augmentation=augmentation,
|
rotation, rotation_not_90, thetha, scaling_flip, task, augmentation=augmentation,
|
||||||
patches=patches, dir_img_bin=dir_img_bin,number_of_backgrounds_per_image=number_of_backgrounds_per_image,list_all_possible_background_images=list_all_possible_background_images, dir_rgb_backgrounds=dir_rgb_backgrounds, dir_rgb_foregrounds=dir_rgb_foregrounds,list_all_possible_foreground_rgbs=list_all_possible_foreground_rgbs)
|
patches=patches, dir_img_bin=dir_img_bin,number_of_backgrounds_per_image=number_of_backgrounds_per_image,list_all_possible_background_images=list_all_possible_background_images, dir_rgb_backgrounds=dir_rgb_backgrounds, dir_rgb_foregrounds=dir_rgb_foregrounds,list_all_possible_foreground_rgbs=list_all_possible_foreground_rgbs)
|
||||||
|
@ -191,7 +192,7 @@ def run(_config, n_classes, n_epochs, input_height,
|
||||||
provide_patches(imgs_list_test, segs_list_test, dir_img_val, dir_seg_val,
|
provide_patches(imgs_list_test, segs_list_test, dir_img_val, dir_seg_val,
|
||||||
dir_flow_eval_imgs, dir_flow_eval_labels, input_height, input_width,
|
dir_flow_eval_imgs, dir_flow_eval_labels, input_height, input_width,
|
||||||
blur_k, blur_aug, padding_white, padding_black, flip_aug, binarization, adding_rgb_background, adding_rgb_foreground, add_red_textlines, channels_shuffling,
|
blur_k, blur_aug, padding_white, padding_black, flip_aug, binarization, adding_rgb_background, adding_rgb_foreground, add_red_textlines, channels_shuffling,
|
||||||
scaling, degrading, brightening, scales, degrade_scales, brightness,
|
scaling, shifting, degrading, brightening, scales, degrade_scales, brightness,
|
||||||
flip_index, shuffle_indexes, scaling_bluring, scaling_brightness, scaling_binarization,
|
flip_index, shuffle_indexes, scaling_bluring, scaling_brightness, scaling_binarization,
|
||||||
rotation, rotation_not_90, thetha, scaling_flip, task, augmentation=False, patches=patches,dir_img_bin=dir_img_bin,number_of_backgrounds_per_image=number_of_backgrounds_per_image,list_all_possible_background_images=list_all_possible_background_images, dir_rgb_backgrounds=dir_rgb_backgrounds,dir_rgb_foregrounds=dir_rgb_foregrounds,list_all_possible_foreground_rgbs=list_all_possible_foreground_rgbs )
|
rotation, rotation_not_90, thetha, scaling_flip, task, augmentation=False, patches=patches,dir_img_bin=dir_img_bin,number_of_backgrounds_per_image=number_of_backgrounds_per_image,list_all_possible_background_images=list_all_possible_background_images, dir_rgb_backgrounds=dir_rgb_backgrounds,dir_rgb_foregrounds=dir_rgb_foregrounds,list_all_possible_foreground_rgbs=list_all_possible_foreground_rgbs )
|
||||||
|
|
||||||
|
|
55
utils.py
55
utils.py
|
@ -78,7 +78,50 @@ def return_image_with_red_elements(img, img_bin):
|
||||||
img_final[:,:,2][img_bin[:,:,0]==0] = 255
|
img_final[:,:,2][img_bin[:,:,0]==0] = 255
|
||||||
return img_final
|
return img_final
|
||||||
|
|
||||||
|
def shift_image_and_label(img, label, type_shift):
|
||||||
|
h_n = int(img.shape[0]*1.06)
|
||||||
|
w_n = int(img.shape[1]*1.06)
|
||||||
|
|
||||||
|
channel0_avg = int( np.mean(img[:,:,0]) )
|
||||||
|
channel1_avg = int( np.mean(img[:,:,1]) )
|
||||||
|
channel2_avg = int( np.mean(img[:,:,2]) )
|
||||||
|
|
||||||
|
h_diff = abs( img.shape[0] - h_n )
|
||||||
|
w_diff = abs( img.shape[1] - w_n )
|
||||||
|
|
||||||
|
h_start = int(h_diff / 2.)
|
||||||
|
w_start = int(w_diff / 2.)
|
||||||
|
|
||||||
|
img_scaled_padded = np.zeros((h_n, w_n, 3))
|
||||||
|
label_scaled_padded = np.zeros((h_n, w_n, 3))
|
||||||
|
|
||||||
|
img_scaled_padded[:,:,0] = channel0_avg
|
||||||
|
img_scaled_padded[:,:,1] = channel1_avg
|
||||||
|
img_scaled_padded[:,:,2] = channel2_avg
|
||||||
|
|
||||||
|
img_scaled_padded[h_start:h_start+img.shape[0], w_start:w_start+img.shape[1],:] = img[:,:,:]
|
||||||
|
label_scaled_padded[h_start:h_start+img.shape[0], w_start:w_start+img.shape[1],:] = label[:,:,:]
|
||||||
|
|
||||||
|
|
||||||
|
if type_shift=="xpos":
|
||||||
|
img_dis = img_scaled_padded[h_start:h_start+img.shape[0],2*w_start:2*w_start+img.shape[1],:]
|
||||||
|
label_dis = label_scaled_padded[h_start:h_start+img.shape[0],2*w_start:2*w_start+img.shape[1],:]
|
||||||
|
elif type_shift=="xmin":
|
||||||
|
img_dis = img_scaled_padded[h_start:h_start+img.shape[0],:img.shape[1],:]
|
||||||
|
label_dis = label_scaled_padded[h_start:h_start+img.shape[0],:img.shape[1],:]
|
||||||
|
elif type_shift=="ypos":
|
||||||
|
img_dis = img_scaled_padded[2*h_start:2*h_start+img.shape[0],w_start:w_start+img.shape[1],:]
|
||||||
|
label_dis = label_scaled_padded[2*h_start:2*h_start+img.shape[0],w_start:w_start+img.shape[1],:]
|
||||||
|
elif type_shift=="ymin":
|
||||||
|
img_dis = img_scaled_padded[:img.shape[0],w_start:w_start+img.shape[1],:]
|
||||||
|
label_dis = label_scaled_padded[:img.shape[0],w_start:w_start+img.shape[1],:]
|
||||||
|
elif type_shift=="xypos":
|
||||||
|
img_dis = img_scaled_padded[2*h_start:2*h_start+img.shape[0],2*w_start:2*w_start+img.shape[1],:]
|
||||||
|
label_dis = label_scaled_padded[2*h_start:2*h_start+img.shape[0],2*w_start:2*w_start+img.shape[1],:]
|
||||||
|
elif type_shift=="xymin":
|
||||||
|
img_dis = img_scaled_padded[:img.shape[0],:img.shape[1],:]
|
||||||
|
label_dis = label_scaled_padded[:img.shape[0],:img.shape[1],:]
|
||||||
|
return img_dis, label_dis
|
||||||
|
|
||||||
def scale_image_for_no_patch(img, label, scale):
|
def scale_image_for_no_patch(img, label, scale):
|
||||||
h_n = int(img.shape[0]*scale)
|
h_n = int(img.shape[0]*scale)
|
||||||
|
@ -660,7 +703,7 @@ def get_patches_num_scale_new(dir_img_f, dir_seg_f, img, label, height, width, i
|
||||||
|
|
||||||
def provide_patches(imgs_list_train, segs_list_train, dir_img, dir_seg, dir_flow_train_imgs,
|
def provide_patches(imgs_list_train, segs_list_train, dir_img, dir_seg, dir_flow_train_imgs,
|
||||||
dir_flow_train_labels, input_height, input_width, blur_k, blur_aug,
|
dir_flow_train_labels, input_height, input_width, blur_k, blur_aug,
|
||||||
padding_white, padding_black, flip_aug, binarization, adding_rgb_background, adding_rgb_foreground, add_red_textlines, channels_shuffling, scaling, degrading,
|
padding_white, padding_black, flip_aug, binarization, adding_rgb_background, adding_rgb_foreground, add_red_textlines, channels_shuffling, scaling, shifting, degrading,
|
||||||
brightening, scales, degrade_scales, brightness, flip_index, shuffle_indexes,
|
brightening, scales, degrade_scales, brightness, flip_index, shuffle_indexes,
|
||||||
scaling_bluring, scaling_brightness, scaling_binarization, rotation,
|
scaling_bluring, scaling_brightness, scaling_binarization, rotation,
|
||||||
rotation_not_90, thetha, scaling_flip, task, augmentation=False, patches=False, dir_img_bin=None,number_of_backgrounds_per_image=None,list_all_possible_background_images=None, dir_rgb_backgrounds=None, dir_rgb_foregrounds=None, list_all_possible_foreground_rgbs=None):
|
rotation_not_90, thetha, scaling_flip, task, augmentation=False, patches=False, dir_img_bin=None,number_of_backgrounds_per_image=None,list_all_possible_background_images=None, dir_rgb_backgrounds=None, dir_rgb_foregrounds=None, list_all_possible_foreground_rgbs=None):
|
||||||
|
@ -759,6 +802,16 @@ def provide_patches(imgs_list_train, segs_list_train, dir_img, dir_seg, dir_flow
|
||||||
cv2.imwrite(dir_flow_train_imgs + '/img_' + str(indexer) + '.png', resize_image(img_scaled, input_height, input_width))
|
cv2.imwrite(dir_flow_train_imgs + '/img_' + str(indexer) + '.png', resize_image(img_scaled, input_height, input_width))
|
||||||
cv2.imwrite(dir_flow_train_labels + '/img_' + str(indexer) + '.png', resize_image(label_scaled, input_height, input_width))
|
cv2.imwrite(dir_flow_train_labels + '/img_' + str(indexer) + '.png', resize_image(label_scaled, input_height, input_width))
|
||||||
indexer += 1
|
indexer += 1
|
||||||
|
if shifting:
|
||||||
|
shift_types = ['xpos', 'xmin', 'ypos', 'ymin', 'xypos', 'xymin']
|
||||||
|
for st_ind in shift_types:
|
||||||
|
img_shifted, label_shifted = shift_image_and_label(cv2.imread(dir_img + '/'+im),
|
||||||
|
cv2.imread(dir_of_label_file), st_ind)
|
||||||
|
|
||||||
|
cv2.imwrite(dir_flow_train_imgs + '/img_' + str(indexer) + '.png', resize_image(img_shifted, input_height, input_width))
|
||||||
|
cv2.imwrite(dir_flow_train_labels + '/img_' + str(indexer) + '.png', resize_image(label_shifted, input_height, input_width))
|
||||||
|
indexer += 1
|
||||||
|
|
||||||
|
|
||||||
if adding_rgb_background:
|
if adding_rgb_background:
|
||||||
img_bin_corr = cv2.imread(dir_img_bin + '/' + img_name+'.png')
|
img_bin_corr = cv2.imread(dir_img_bin + '/' + img_name+'.png')
|
||||||
|
|
Loading…
Add table
Add a link
Reference in a new issue