# -*- coding: utf-8 -*-
"""
Created on Wed Sep 21 08:17:42 2022

----------------------------------------------------------------------------------
 This script split the rellis 3D dataset into train val and test folders
----------------------------------------------------------------------------------

1. Create train, val and test folders in data/rellis folder
2. Create a new empty folder named as images and masks_id in train and val folders.
3. Create a new empty foldr named as images inside test folder.
4. Execute this script to copy images and masks_id to train folder.
5. Execute this script to copy images and masks_id to val folder.
6. Execute this script to copy images to test folder.


Output:
    Coping images, please wait...
    Total number of copied images:  3302
    Images stored saved in:  ./train//images
    Coping masks_id, please wait...
    Total number of copied masks:  3302
    Images stored saved in:  ./train/masks_id
    
    Coping images, please wait...
    Total number of copied images:  983
    Images stored saved in:  ./val//images
    Coping masks_id, please wait...
    Total number of copied masks:  983
    Images stored saved in:  ./val/masks_id
    
    Coping images, please wait...
    Total number of copied images:  1672
    Images stored saved in:  ./test//images

_-----------------------------------------------------------------------------
Mask_color images to instance segmentation

1. Create train, val and test folders in data/rellis folder
2. Create a new empty folder named as images and masks_color in train and val folders.
3. Create a new empty foldr named as images inside test folder.
4. Execute this script to copy masks_colors to train folder.
5. Execute this script to copy masks_colors to val folder.
6. Execute this script to copy masks_colors to test folder.
 
   Output:
       Coping images, please wait...
       Total number of copied images:  3302
       Images stored saved in:  ./train//masks_colors
       
       Coping images, please wait...
       Total number of copied images:  983
       Images stored saved in:  ./val//masks_colors

'''

"""

import os
import pandas as pd
from shutil import copy

def search_image(count, imagename, path, DEST_PATH):
    error=0
    for filename in os.listdir(path):    
        if (filename.endswith(".bmp")) and (filename.startswith(imagename)): 
            copy(path +'/'+ filename, DEST_PATH+'/'+filename)
            count+=1
            error=0
            #print(count)
            break
        else:
            error=1
    return count, error


DEST_PATH='train'
#DEST_PATH='val'
#DEST_PATH='test'

# Rellis 5 categories
pd_card_images = pd.read_csv('train5.csv',sep=";", names=['images','masks_id'], encoding ='latin1', low_memory=False)
#pd_card_images = pd.read_csv('val5.csv',sep=";", names=['images','masks_id'], encoding ='latin1', low_memory=False)
#pd_card_images = pd.read_csv('test5.csv',sep=";", names=['images','masks_id'], encoding ='latin1', low_memory=False)

# Rellis 6 categories
#pd_card_images = pd.read_csv('train.csv',sep=";", names=['images','masks_id'], encoding ='latin1', low_memory=False)
#pd_card_images = pd.read_csv('val.csv',sep=";", names=['images','masks_id'], encoding ='latin1', low_memory=False)
#pd_card_images = pd.read_csv('test.csv',sep=";", names=['images','masks_id'], encoding ='latin1', low_memory=False)

# Rellis 20 labels
#pd_card_images = pd.read_csv('train20.csv',sep=";", names=['images','masks_id'], encoding ='latin1', low_memory=False)
#pd_card_images = pd.read_csv('val20.csv',sep=";", names=['images','masks_id'], encoding ='latin1', low_memory=False)
#pd_card_images = pd.read_csv('test20.csv',sep=";", names=['images','masks_id'], encoding ='latin1', low_memory=False)
#pd_card_images = pd.read_csv('test_maskcolors.csv',sep=";", names=['maskcolors'], encoding ='latin1', low_memory=False)

# Rellis 20 masks_colors for instance segmentation
#pd_card_images = pd.read_csv('train_color20.csv',sep=";", names=['images', 'masks_colors'], encoding ='latin1', low_memory=False)
#¶pd_card_images = pd.read_csv('val_color20.csv',sep=";", names=['images', 'masks_colors'], encoding ='latin1', low_memory=False)
#pd_card_images = pd.read_csv('test_color20.csv',sep=";", names=['images', 'masks_colors'], encoding ='latin1', low_memory=False)


pd_card_images = pd_card_images.drop(labels=0, axis=0)
rpd_card_images=pd_card_images.reset_index(drop=True)

image_path=rpd_card_images['images']
mask_path=rpd_card_images['masks_id']
#maskcolors_path=rpd_card_images['masks_colors']

print('Coping images, please wait...')
count=0

for im in image_path: 
    filename = str(im).split("/") 
    txt_filename=str(filename[1])
    #print(im)
    copy('images/'+ im, DEST_PATH +'/images/'+txt_filename)
    count+=1
    
print('Total number of copied images: ', count)               
print('Images stored saved in: ', DEST_PATH+'/images')

# for idx, im in enumerate(maskcolors_path):
#     filename = str(im).split("/") 
#     txt_filename=str(filename[1])
#     orig_image = image_path[idx]

#     copy('./maskscolors/' + orig_image, DEST_PATH +txt_filename)
        
#     count+=1

# print('Total number of copied images: ', count)               
# print('Images stored saved in: ', DEST_PATH+'/masks_colors')


## Only for train and val **************************************
print('Coping masks_id, please wait...')
count=0
for mask in mask_path:    
    filename = str(mask).split("/") 
    txt_filename=str(filename[1])
    #print(mask)
    copy('masks_id/'+ mask, DEST_PATH+'/masks_id/'+txt_filename)
    count+=1

print('Total number of copied masks: ', count)               
print('Images stored saved in: ', DEST_PATH+'masks_id')