from LIBS.ImgPreprocess.my_labelme import convert_json_mask convert_json_mask( '/media/ubuntu/data1/公开数据集/OpticDiscDetection/ROP/original/images', '/media/ubuntu/data1/公开数据集/OpticDiscDetection/ROP/original/masks') from LIBS.ImgPreprocess.my_rop import resize_rop_dir # (640,480)->(640,512), (1600,1200)->(640,512) resize_rop_dir('/media/ubuntu/data1/公开数据集/OpticDiscDetection/ROP/original', '/media/ubuntu/data1/公开数据集/OpticDiscDetection/ROP/preprocess') from LIBS.ImgPreprocess.my_image_helper import resize_images_dir resize_images_dir( source_dir='/media/ubuntu/data1/公开数据集/OpticDiscDetection/ROP/preprocess', dest_dir='/media/ubuntu/data1/公开数据集/OpticDiscDetection/ROP/preprocess384', convert_image_to_square=True, image_size=384) import os from LIBS.DataPreprocess.my_data import write_csv_img_seg filename_csv = os.path.abspath('ROP.csv') write_csv_img_seg( filename_csv, '/media/ubuntu/data1/公开数据集/OpticDiscDetection/ROP/preprocess384/images') print('OK')
import os import math import json import csv from LIBS.ImgPreprocess.my_image_helper import resize_images_dir do_preprocess = True dir_original = '/media/ubuntu/data2/Fover_center/ROP/2020_11_4_patient_based/original/' preprocess_image_size = 384 dir_preprocess = '/media/ubuntu/data2/Fover_center/ROP/2020_11_4_patient_based/preprocess384/' dir_tmp = '/tmp2/ROP_dataset2/' if do_preprocess: resize_images_dir(dir_original, dir_preprocess, convert_image_to_square=True, image_size=preprocess_image_size) filename_csv = os.path.join(os.path.abspath('.'), 'fovea_ROP_patient_based.csv') if os.path.exists(filename_csv): os.remove(filename_csv) with open(filename_csv, 'w', newline='') as csvfile: csv_writer = csv.writer(csvfile, delimiter=',') csv_writer.writerow(['images', 'x', 'y']) for dir_path, subpaths, files in os.walk(dir_original, False): for f in files: full_filename = os.path.join(dir_path, f) file_base, file_ext = os.path.splitext(full_filename)
'.BMP', '.PNG', '.JPEG', '.JPG', '.TIFF', '.TIF' ]: continue image_file_mask = image_file.replace('.png', '_mask.png') csv_writer.writerow([image_file, image_file_mask]) if __name__ == '__main__': convert_image_mask_name( '/media/ubuntu/data2/BloodVesselsSegment_2020_1_20/original', '/media/ubuntu/data2/BloodVesselsSegment_2020_1_20/preprocess') from LIBS.ImgPreprocess.my_image_helper import resize_images_dir resize_images_dir( '/media/ubuntu/data2/BloodVesselsSegment_2020_1_20/preprocess', '/media/ubuntu/data2/BloodVesselsSegment_2020_1_20/preprocess512', image_size=512) resize_images_dir( '/media/ubuntu/data2/BloodVesselsSegment_2020_1_20/preprocess', '/media/ubuntu/data2/BloodVesselsSegment_2020_1_20/preprocess384', image_size=384) dir_preprocess = '/media/ubuntu/data2/BloodVesselsSegment_2020_1_20/preprocess512' csv_file = os.path.abspath(os.path.join(sys.path[0], 'BloodVessel.csv')) gen_csv(csv_file, dir_preprocess) from LIBS.DataPreprocess.my_data import split_csv_img_seg split_csv_img_seg(file_csv='BloodVessel.csv', file_csv_train='BloodVessel_train.csv', file_csv_valid='BloodVessel_valid.csv')
GEN_CSV = True TRAIN_TYPE = 'ocular_surface' from LIBS.ImgPreprocess.my_image_helper import resize_images_dir dir_original = '/media/ubuntu/data1/眼底眼表其他' dir_preprocess = '/media/ubuntu/data1/眼底眼表其他' # dir_original ='/media/ubuntu/data1/眼底眼表其他/tmp/original' # dir_preprocess ='/media/ubuntu/data1/眼底眼表其他/tmp/preprocess' # dir_original = '/media/ubuntu/data2/无法归类/original' # dir_preprocess = '/media/ubuntu/data2/无法归类/preprocess' if DO_PREPROCESS: resize_images_dir(dir_original, dir_preprocess, imgsize=299) if GEN_CSV: filename_csv = os.path.abspath(os.path.join(sys.path[0], "..", 'datafiles', TRAIN_TYPE + '.csv')) dict_mapping = {'0.fundus': 0, '1.ocular_surface': 1, '2.other_images': 2} # 读取目录,根据目录名提取类别,生成.csv文件 if os.path.exists(filename_csv): os.remove(filename_csv) my_data.write_csv_based_on_dir(filename_csv, dir_preprocess, dict_mapping, match_type='header') train_files, train_labels, valid_files, valid_labels = my_data.split_dataset(
center_x = df.at[i, 'X-Coordinate'] center_y = df.at[i, 'Y-Coordinate'] img_fover = create_img_fover(filename_fover, center_x, center_y) filename_dest = filename_fover.replace(fover_dir, dest_dir) if not os.path.exists(os.path.dirname(filename_dest)): os.makedirs(os.path.dirname(filename_dest)) print(filename_dest) cv2.imwrite(filename_dest, img_fover) resize_images_dir('/home/ubuntu/Fover_center/DR0_4黄斑不准重新标注400/512', imgsize=512) exit(0) base_dir = '/home/ubuntu/Fover_center/DR0_4黄斑不准重新标注400/preprocess/original' for dir_path, subpaths, files in os.walk(base_dir, False): for f in files: img_file_source = os.path.join(dir_path, f) filename, file_extension = os.path.splitext(img_file_source) if file_extension.upper() not in ['.BMP', '.PNG', '.JPG', '.JPEG', '.TIFF', '.TIF']: print('file ext name:', f) continue