import os
import glob
import random
from processing_functions import misc as msc
from shutil import copyfile
# define the number of samples you want
n_samples = 50
imgsPath = os.environ['HOME'] + '/data/extracted_images/2019-07-11-16-21-46/ngr'
out_path = os.environ[
'HOME'] + '/data/extracted_images/samples/' + msc.find_datetime_String(
imgsPath)
# print(out_path)
msc.createDir(out_path)
imList = msc.orderedFileList(imgsPath)
n = len(imList)
print(n)
for i in range(n_samples):
imSample = imList[random.randint(0, n - 1)]
filename = msc.filenameFromPath(imSample)
# print(filename)
copyfile(imSample, os.path.join(out_path, filename))
print('fim')
"""
initially i've trated grass and soil vegtation as "vegetation", but now i will only use not grass vegetation
"""
classifiedPath = "/home/kaue/data/extracted_images/samples/2019-07-11-16-21-46/already_classified"
toClassifyFolder = "/home/kaue/data/extracted_images/samples/2019-07-11-16-21-46/reclassification"
originalsPath = "/home/kaue/data/extracted_images/2019-07-11-16-21-46/ngr"
classifiedList = misc.orderedFileList(classifiedPath,'*.png')
for path in classifiedList:
# print(path)
filename = misc.filenameFromPath(path)
originalImgPath = os.path.join(originalsPath,misc.modFilenameExt(filename,'.jpg'))
outPath = os.path.join(toClassifyFolder,filename)
print(originalImgPath)
classifiedImg = cv2.imread(path)
originalImg = cv2.imread(originalImgPath)
for i,column in enumerate(classifiedImg):
for j,pixel in enumerate(column):
# as there are only black or white pixels, we can test only a channel
# print(originalImg[i,j,0])
if pixel[0] == 255:
try:
pixel.itemset(0,originalImg[i,j,0])
strToContain = 'color'
pathlist = msc.getSubdirs(basedir)
# sizes = np.empty(len(pathlist), dtype=int)
# print(sizes)
# for i,path in enumerate(pathlist):
# sizes[i] = path.count('/')
# print(sizes)
# max_lvl = np.max(sizes)
# print(max_lvl)
for path in pathlist:
if msc.checkForImages(path,'*.png'):
parent = msc.get_parent_dir(path)S
imgList = msc.orderedFileList(path,'*.png')
for imgPath in imgList:
if strToContain in imgPath:
filename = msc.filenameFromPath(imgPath)
newfilename = filename.replace(strToReplace,strToAdd)
print(newfilename)
move(imgPath,os.path.join(parent,newfilename))
# os.removedirs(path)
msc.telegram_bot_sendtext("copying terminated")
from processing_functions import color_stuff as cs
from processing_functions import general_funcs as gf
import glob
import cv2
basedir = "/home/kauevestena/Dropbox/data/backup/temp/"
baseOutDir = "/home/kauevestena/Dropbox/data/gt/originals_complete_red/"
dirList = msc.getSubdirs(basedir)
subpaths = msc.subpathList(dirList,basedir)
msc.createDirStructure(baseOutDir,subpaths)
for folder in dirList:
if msc.checkForImages(folder,'*.png'):
print(folder)
subpath = msc.removeBasedir(folder,basedir)
outFolderPath = os.path.join(baseOutDir,subpath)
for filepath in glob.glob(folder+"/*.png"):
fileName = msc.filenameFromPath(filepath)
outPath = os.path.join(outFolderPath,fileName)
cs.save_one_band(filepath,outPath)
msc.telegram_bot_sendtext("band extraction terminated")
from processing_functions import misc as msc
from processing_functions import general_funcs as gf
import os
in_out_list = [("/home/kaue/Dropbox/data/gt/versions/only_trees",
"/home/kaue/Dropbox/data/gt_downsized/only_trees"),
("/home/kaue/Dropbox/data/gt/versions/with_terrain_veg",
"/home/kaue/Dropbox/data/gt_downsized/with_terrain_veg")]
for inoutpair in in_out_list:
try:
os.makedirs(inoutpair[1])
except:
pass
imgList = msc.orderedFileList(inoutpair[0], '*.png')
for imgpath in imgList:
imgname = msc.filenameFromPath(imgpath)
outpath = os.path.join(inoutpair[1], imgname)
# print(outpath)
gf.resize_and_save(imgpath, outpath)
#script to classify vegetation and no vegatation in a manualy classified in white for vegetation and anything to non-vegetation
from processing_functions import misc as msc
from processing_functions import color_stuff as cs
import datetime
import os
# import cv2
# inputpath = "/home/kaue/data/extracted_images/samples/2019-07-11-16-21-46/regular"
inputpath = "/home/kaue/data/extracted_images/samples/2019-07-11-16-21-46/reclassification"
# outpath = "/home/kaue/data/extracted_images/samples/2019-07-11-16-21-46/already_classified"
outpath = "/home/kaue/data/extracted_images/samples/2019-07-11-16-21-46/reclassification_blackwhite"
imagelist = msc.orderedFileList(inputpath, extension='*.png')
minDate = datetime.datetime(year=2019, day=17, month=7)
for imgpath in imagelist:
filedate = msc.getModTime(imgpath)
if filedate > minDate:
savepath = os.path.join(outpath, msc.filenameFromPath(imgpath))
# cs.remove_other_classes(imgpath,savepath,255,255,255)
cs.remove_other_classes(imgpath, savepath, 0, 0, 0, 255, 255, 255)
print(imgpath)
msc.telegram_bot_sendtext("GT classification ended")
def __init__(self, imgpath):
self.img_path = imgpath
self.img_name = msc.filenameFromPath(imgpath)
self.img_number = msc.fileNumberFromPathAsStr(imgpath)