|
|
import numpy as np |
|
|
from os import listdir |
|
|
from os.path import isfile, isdir, join |
|
|
import os |
|
|
|
|
|
import random |
|
|
from subprocess import call |
|
|
|
|
|
cwd = '/home/yuqian_fu/Data/CDFSL/Plantae' |
|
|
source_path = cwd |
|
|
data_path = join(cwd,'images') |
|
|
if not os.path.exists(data_path): |
|
|
os.makedirs(data_path) |
|
|
savedir = './' |
|
|
dataset_list = ['base','val','novel'] |
|
|
|
|
|
|
|
|
folder_list = [f for f in listdir(source_path) if isdir(join(source_path, f))] |
|
|
|
|
|
folder_list_count = np.array([len(listdir(join(source_path, f))) for f in folder_list]) |
|
|
folder_list_idx = np.argsort(folder_list_count) |
|
|
folder_list = np.array(folder_list)[folder_list_idx[-200:]].tolist() |
|
|
label_dict = dict(zip(folder_list,range(0,len(folder_list)))) |
|
|
|
|
|
classfile_list_all = [] |
|
|
|
|
|
for i, folder in enumerate(folder_list): |
|
|
source_folder_path = join(source_path, folder) |
|
|
folder_path = join(data_path, folder) |
|
|
classfile_list_all.append( [ cf for cf in listdir(source_folder_path) if (isfile(join(source_folder_path,cf)) and cf[0] != '.')]) |
|
|
random.shuffle(classfile_list_all[i]) |
|
|
classfile_list_all[i] = classfile_list_all[i][:min(len(classfile_list_all[i]), 600)] |
|
|
|
|
|
call('mkdir ' + folder_path, shell=True) |
|
|
for cf in classfile_list_all[i]: |
|
|
call('cp ' + join(source_folder_path, cf) + ' ' + join(folder_path, cf), shell=True) |
|
|
classfile_list_all[i] = [join(folder_path, cf) for cf in classfile_list_all[i]] |
|
|
|
|
|
for dataset in dataset_list: |
|
|
file_list = [] |
|
|
label_list = [] |
|
|
for i, classfile_list in enumerate(classfile_list_all): |
|
|
if 'base' in dataset: |
|
|
if (i%2 == 0): |
|
|
file_list = file_list + classfile_list |
|
|
label_list = label_list + np.repeat(i, len(classfile_list)).tolist() |
|
|
if 'val' in dataset: |
|
|
if (i%4 == 1): |
|
|
file_list = file_list + classfile_list |
|
|
label_list = label_list + np.repeat(i, len(classfile_list)).tolist() |
|
|
if 'novel' in dataset: |
|
|
if (i%4 == 3): |
|
|
file_list = file_list + classfile_list |
|
|
label_list = label_list + np.repeat(i, len(classfile_list)).tolist() |
|
|
|
|
|
fo = open(savedir + dataset + ".json", "w") |
|
|
fo.write('{"label_names": [') |
|
|
fo.writelines(['"%s",' % item for item in folder_list]) |
|
|
fo.seek(0, os.SEEK_END) |
|
|
fo.seek(fo.tell()-1, os.SEEK_SET) |
|
|
fo.write('],') |
|
|
|
|
|
fo.write('"image_names": [') |
|
|
fo.writelines(['"%s",' % item for item in file_list]) |
|
|
fo.seek(0, os.SEEK_END) |
|
|
fo.seek(fo.tell()-1, os.SEEK_SET) |
|
|
fo.write('],') |
|
|
|
|
|
fo.write('"image_labels": [') |
|
|
fo.writelines(['%d,' % item for item in label_list]) |
|
|
fo.seek(0, os.SEEK_END) |
|
|
fo.seek(fo.tell()-1, os.SEEK_SET) |
|
|
fo.write(']}') |
|
|
|
|
|
fo.close() |
|
|
print("%s -OK" %dataset) |