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Commit ccef6c78 authored by Nuno Pimpão Santos Martins's avatar Nuno Pimpão Santos Martins
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new script to restore mask of a single folder

parent 003268ae
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import os
import numpy as np
import matplotlib.pyplot as plt
import tifffile
from utils import *
from segmentation import *
import time
import datetime
from tqdm import tqdm
# ---
# Load threshold data
# ---
table_path = 'w:\\NPC_adult_new\\quantification_data\\iou_quantification\\iou_quantification_dlwithbiasx3_2023-07-20\\'
table_list = os.listdir(table_path)
table_list.sort()
table_list = [x for x in table_list if x.find('.csv') > 0]
# ---
# Data Import
# ---
# results paths
results_path = 'w:\\NPC_adult_new\\dl_training\\results\\contrastenhance_128x128px_maeloss_20pxblurrad_poissonnoise_adaptive0p6to0p5_unet5\\'
pred1_mask_path = results_path+'results_20230129_x3\\'
pred1_suffix_substring = '.tif'
pred1_save_path = os.path.join(pred1_mask_path, 'masks')
if not os.path.exists(pred1_save_path):
os.mkdir(pred1_save_path)
# pred2_mask_path = results_path+'results_x2\\'
# pred2_suffix_substring = '_x2.tif'
# pred2_save_path = os.path.join(pred2_mask_path, 'masks')
# if not os.path.exists(pred2_save_path):
# os.mkdir(pred2_save_path)
# pred3_mask_path = results_path+'results_x3\\'
# pred3_suffix_substring = '_x3.tif'
# pred3_save_path = os.path.join(pred3_mask_path, 'masks')
# if not os.path.exists(pred3_save_path):
# os.mkdir(pred3_save_path)
time_start_script = time.time()
for table_name in tqdm(table_list, total=len(table_list)):
data_table = []
with open(os.path.join(table_path, table_name), "r") as file:
for line in file:
line_proc = line.split(',')
try:
test = float(line_proc[0])
except:
continue
parsed_line = []
for i in range(len(line_proc)):
try:
item = float(line_proc[i])
except:
continue
parsed_line.append(item)
data_table.append(parsed_line)
data_table = np.asarray(data_table, dtype='float32')
# print('data len: ', data_table.shape)
# print('line len: ', data_table[0].shape)
table_name_noext = table_name[12:table_name.index('_mask')]
print(table_name_noext)
time_image = time.time()
# to check if loaded images are the same
print('Loading image: ', table_name_noext)
print('Loading pred1 image name: ')
table_1 = data_table[:, 2]
image_pred = tifffile.imread(os.path.join(pred1_mask_path, table_name_noext+pred1_suffix_substring)).astype('float32')
pred1_mask = make_mask_from_values(image_pred, table_1)
tifffile.imwrite(os.path.join(pred1_save_path, table_name_noext+pred1_suffix_substring), pred1_mask)
# print('Loading pred2 image name: ')
# table_2 = data_table[:, 4]
# # print(table_2.shape)
# # print(table_2[:10])
# # stop
# image_pred2 = tifffile.imread(os.path.join(pred2_mask_path, table_name_noext+pred2_suffix_substring)).astype('float32')
# pred2_mask = make_mask_from_values(image_pred2, table_2)
# tifffile.imwrite(os.path.join(pred2_save_path, table_name_noext+pred2_suffix_substring), pred2_mask)
# print('Loading pred3 image name: ')
# table_3 = data_table[:, 6]
# image_pred3 = tifffile.imread(os.path.join(pred3_mask_path, table_name_noext+pred3_suffix_substring)).astype('float32')
# pred3_mask = make_mask_from_values(image_pred3, table_3)
# tifffile.imwrite(os.path.join(pred3_save_path, table_name_noext+pred3_suffix_substring), pred3_mask)
print('Time per image: ', time.time() - time_image)
print('Time: ', time.time() - time_start_script)
print('Done')
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