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import numpy as np
import torch
import shutil
import os
import matplotlib.pyplot as plt
import cv2
import json
from PIL import Image
import pickle
from skimage.transform import resize
from utils.dataset_prepare import split_data, save_fileLabel
def FGADR_split():
pkl_path = './files_split/fgadr_pkl_file.pkl' # change your path here
path = "./dataset_demo/FGADR"
f = open(pkl_path, 'rb')
a = pickle.load(f)
a_key = a.keys()
B = ["train", "test"]
C = ["Training", "Testing"]
for index, i in enumerate(B):
print(i)
print(len(a[i]))
folder_type = os.path.join(path, i)
if os.path.exists(folder_type.replace(i, C[index])):
shutil.rmtree(os.path.join(path, C[index]))
os.mkdir(os.path.join(path, C[index]))
for j in a[i]:
folder_class = os.path.join(folder_type, str(j[1]))
if not os.path.exists(folder_class.replace(i, C[index])):
os.mkdir(folder_class.replace(i, C[index]))
file = j[0].replace("/mnt/sda/haal02-data/FGADR-Seg-Set", "./dataset_demo/FGADR")
img = cv2.imread(file)
img = resize(img, (512, 512), order=0, preserve_range=True, anti_aliasing=False).astype('uint8')
#/home/caduser/Foundmed_Experiment/Classification/FGADR/Seg-set/Original_Images/0001_2.png
name_img = file.split("/")[-1]
#print(os.path.join(folder_class.replace(i, C[index])))
cv2.imwrite(os.path.join(folder_class.replace(i, C[index]), name_img), img) |