def static_pixel_num(image_dir, target_phase='PV'):
# {0: 217784361, 1: 1392043, 2: 209128, 3: 1486676, 4: 458278, 5: 705482}
# {0: 1.0, 156, 1041, 146, 475, 308}
static_res = {0: 0, 1: 0, 2: 0, 3: 0, 4: 0, 5: 0}
from convert2jpg import extract_bboxs_mask_from_mask
from config import pixel2type, type2pixel
for sub_name in ['train', 'val', 'test']:
names = os.listdir(os.path.join(image_dir, sub_name))
for name in names:
cur_slice_dir = os.path.join(image_dir, sub_name, name)
mhd_mask_path = glob(
os.path.join(cur_slice_dir, 'Mask_%s*.mhd' % target_phase))[0]
mask_image = read_mhd_image(mhd_mask_path)
min_xs, min_ys, max_xs, max_ys, names, mask = extract_bboxs_mask_from_mask(
mask_image, os.path.join(cur_slice_dir, 'tumor_types'))
for key in pixel2type.keys():
mask[mask == key] = type2pixel[pixel2type[key]][0]
pixel_value_set = np.unique(mask)
print(pixel_value_set)
for value in list(pixel_value_set):
static_res[value] += np.sum(mask == value)
print(static_res)
def dicom2jpg_multiphase_tripleslice_mask(slice_dir, save_dir, phase_names, target_phase_name):
'''
前置条件：已经将dicom格式的数据转为成MHD格式，并且已经提出了slice，一个mhd文件只包含了三个slice
针对每个phase提取三个slice(all), 但是mask还是只提取一个
保存的格式是name_nc.jpg, name_art.jpg, name_pv.jpg
:param slice_dir:
:param save_dir:
:param phase_names:
:param target_phase_name:
:return:
'''
total_phase_name = ''.join(phase_names)
total_phase_name += '_tripleslice_mask'
target_phase_mask = None
mhd_images = []
for phase_name in phase_names:
mhd_image_path = os.path.join(slice_dir, 'Image_' + phase_name + '.mhd')
mhd_mask_path = os.path.join(slice_dir, 'Mask_' + phase_name + '.mhd')
mhd_image = read_mhd_image(mhd_image_path)
mask_image = read_mhd_image(mhd_mask_path)
mhd_image = np.asarray(np.squeeze(mhd_image), np.float32)
mhd_image = np.transpose(mhd_image, axes=[1, 2, 0])
if phase_name == target_phase_name:
target_phase_mask = mask_image
_, _, depth_image = np.shape(mhd_image)
if depth_image == 2:
mhd_image = np.concatenate(
[mhd_image,
np.expand_dims(mhd_image[:, :, np.argmax(np.sum(np.sum(mask_image, axis=1), axis=1))], axis=2)],
axis=2
)
print('Error')
mhd_images.append(mhd_image)
# mhd_image = np.expand_dims(mhd_image, axis=2)
# mhd_image = np.concatenate([mhd_image, mhd_image, mhd_image], axis=2)
mhd_image = np.concatenate(mhd_images, axis=-1)
mask_image = target_phase_mask
mask_image = np.asarray(np.squeeze(mask_image), np.uint8)
max_v = 300.
min_v = -350.
mhd_image[mhd_image > max_v] = max_v
mhd_image[mhd_image < min_v] = min_v
print(np.mean(mhd_image, dtype=np.float32))
mhd_image -= np.mean(mhd_image)
min_v = np.min(mhd_image)
max_v = np.max(mhd_image)
interv = max_v - min_v
mhd_image = (mhd_image - min_v) / interv
file_name = os.path.basename(slice_dir)
dataset_name = os.path.basename(os.path.dirname(slice_dir))
print('the shape of mhd_image is ', np.shape(mhd_image), np.min(mhd_image), np.max(mhd_image))
print('the shape of mask_image is ', np.shape(mask_image))
for phase_idx, phase_name in enumerate(['NNC', 'ART', 'PPV']):
save_path = os.path.join(save_dir, total_phase_name, dataset_name,
file_name + '_%s.%s' % (phase_name, image_suffix_name))
if not os.path.exists(os.path.dirname(save_path)):
os.makedirs(os.path.dirname(save_path))
if image_suffix_name == 'jpg':
cv2.imwrite(save_path, mhd_image[:, :, phase_idx * 3: (phase_idx + 1) * 3] * 255)
else:
cv2.imwrite(save_path, np.asarray(mhd_image[:, :, phase_idx * 3: (phase_idx + 1) * 3] * 255, np.int32))
if not os.path.exists(os.path.join(save_dir, total_phase_name, dataset_name + '_mask')):
os.mkdir(os.path.join(save_dir, total_phase_name, dataset_name + '_mask'))
if not os.path.exists(os.path.join(save_dir, total_phase_name, dataset_name + '_mask_vis')):
os.mkdir(os.path.join(save_dir, total_phase_name, dataset_name + '_mask_vis'))
real_mask_save_path = os.path.join(save_dir, total_phase_name, dataset_name + '_mask', file_name + '.' + image_suffix_name)
vis_mask_save_path = os.path.join(save_dir, total_phase_name, dataset_name + '_mask_vis', file_name + '.' + image_suffix_name)
xml_save_dir = os.path.join(save_dir, total_phase_name, dataset_name+'_xml')
if not os.path.exists(xml_save_dir):
os.makedirs(xml_save_dir)
evulate_gt_dir = os.path.join(save_dir, total_phase_name, dataset_name+'_gt')
if not os.path.exists(evulate_gt_dir):
os.makedirs(evulate_gt_dir)
xml_save_path = os.path.join(xml_save_dir, file_name + '.xml')
gt_save_path = os.path.join(evulate_gt_dir, file_name + '.txt') # for evulate
doc = Document()
root_node = doc.createElement('annotation')
doc.appendChild(root_node)
folder_name = os.path.basename(save_dir) + '/' + total_phase_name
folder_node = doc.createElement('folder')
root_node.appendChild(folder_node)
folder_txt_node = doc.createTextNode(folder_name)
folder_node.appendChild(folder_txt_node)
file_name = file_name + '.jpg'
filename_node = doc.createElement('filename')
root_node.appendChild(filename_node)
filename_txt_node = doc.createTextNode(file_name)
filename_node.appendChild(filename_txt_node)
shape = list(np.shape(mhd_image))
size_node = doc.createElement('size')
root_node.appendChild(size_node)
width_node = doc.createElement('width')
width_node.appendChild(doc.createTextNode(str(shape[0])))
height_node = doc.createElement('height')
height_node.appendChild(doc.createTextNode(str(shape[1])))
depth_node = doc.createElement('depth')
depth_node.appendChild(doc.createTextNode(str(3)))
size_node.appendChild(width_node)
size_node.appendChild(height_node)
size_node.appendChild(depth_node)
# mask_image[mask_image != 1] = 0
# xs, ys = np.where(mask_image == 1)
# min_x = np.min(xs)
# min_y = np.min(ys)
# max_x = np.max(xs)
# max_y = np.max(ys)
min_xs, min_ys, max_xs, max_ys, names, mask = extract_bboxs_mask_from_mask(mask_image,
os.path.join(slice_dir, 'tumor_types'))
cv2.imwrite(vis_mask_save_path, np.asarray(mask, np.int32))
for key in pixel2type.keys():
mask[mask == key] = type2pixel[pixel2type[key]][0]
cv2.imwrite(real_mask_save_path, np.asarray(mask, np.int32))
lines = []
for min_x, min_y, max_x, max_y, name in zip(min_xs, min_ys, max_xs, max_ys, names):
object_node = doc.createElement('object')
root_node.appendChild(object_node)
name_node = doc.createElement('name')
name_node.appendChild(doc.createTextNode(name))
object_node.appendChild(name_node)
truncated_node = doc.createElement('truncated')
object_node.appendChild(truncated_node)
truncated_node.appendChild(doc.createTextNode('0'))
difficult_node = doc.createElement('difficult')
object_node.appendChild(difficult_node)
difficult_node.appendChild(doc.createTextNode('0'))
bndbox_node = doc.createElement('bndbox')
object_node.appendChild(bndbox_node)
xmin_node = doc.createElement('xmin')
xmin_node.appendChild(doc.createTextNode(str(min_y)))
bndbox_node.appendChild(xmin_node)
ymin_node = doc.createElement('ymin')
ymin_node.appendChild(doc.createTextNode(str(min_x)))
bndbox_node.appendChild(ymin_node)
xmax_node = doc.createElement('xmax')
xmax_node.appendChild(doc.createTextNode(str(max_y)))
bndbox_node.appendChild(xmax_node)
ymax_node = doc.createElement('ymax')
ymax_node.appendChild(doc.createTextNode(str(max_x)))
bndbox_node.appendChild(ymax_node)
line = '%s %d %d %d %d\n' % (name, min_y, min_x, max_y, max_x)
print(line)
lines.append(line)
with open(xml_save_path, 'wb') as f:
f.write(doc.toprettyxml(indent='\t', encoding='utf-8'))
with open(gt_save_path, 'w') as f:
f.writelines(lines)
f.close()