Synchronizing and Making Data Ordered.py

df_imgs = df[~df['path'].str.contains("mask")]
df_masks = df[df['path'].str.contains("mask")]

# File path line length images for later sorting
BASE_LEN = 89 # len(/kaggle/input/lgg-mri-segmentation/kaggle_3m/TCGA_DU_6404_19850629/TCGA_DU_6404_19850629_ <-!!!43.tif)
END_IMG_LEN = 4 # len(/kaggle/input/lgg-mri-segmentation/kaggle_3m/TCGA_DU_6404_19850629/TCGA_DU_6404_19850629_43 !!!->.tif)
END_MASK_LEN = 9 # (/kaggle/input/lgg-mri-segmentation/kaggle_3m/TCGA_DU_6404_19850629/TCGA_DU_6404_19850629_43 !!!->_mask.tif)

# Data sorting
imgs = sorted(df_imgs["path"].values, key=lambda x : int(x[BASE_LEN:-END_IMG_LEN]))
masks = sorted(df_masks["path"].values, key=lambda x : int(x[BASE_LEN:-END_MASK_LEN]))

# Sorting check
idx = random.randint(0, len(imgs)-1)
print("Path to the Image:", imgs[idx], "\nPath to the Mask:", masks[idx])