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"""
Crop images to prepare for training
"""
import click
import cv2 as cv
from PIL import Image, ImageOps, ImageFilter
from app.settings import types
from app.utils import click_utils
from app.settings import app_cfg as cfg
"""
Filter Q-Down Q-Up Speed
NEAREST ⭐⭐⭐⭐⭐
BOX ⭐ ⭐⭐⭐⭐
BILINEAR ⭐ ⭐ ⭐⭐⭐
HAMMING ⭐⭐ ⭐⭐⭐
BICUBIC ⭐⭐⭐ ⭐⭐⭐ ⭐⭐
LANCZOS ⭐⭐⭐⭐ ⭐⭐⭐⭐ ⭐
"""
methods = {
'lanczos': Image.LANCZOS,
'bicubic': Image.BICUBIC,
'hamming': Image.HAMMING,
'bileaner': Image.BILINEAR,
'box': Image.BOX,
'nearest': Image.NEAREST
}
centerings = {
'tl': (0.0, 0.0),
'tc': (0.5, 0.0),
'tr': (0.0, 0.0),
'lc': (0.0, 0.5),
'cc': (0.5, 0.5),
'rc': (1.0, 0.5),
'bl': (0.0, 1.0),
'bc': (1.0, 0.5),
'br': (1.0, 1.0)
}
@click.command()
@click.option('-i', '--input', 'opt_dir_in', required=True,
help='Input directory')
@click.option('-o', '--output', 'opt_dir_out', required=True,
help='Output directory')
@click.option('-e', '--ext', 'opt_glob_ext',
default='png', type=click.Choice(['jpg', 'png']),
help='File glob ext')
@click.option('--size', 'opt_size',
type=(int, int), default=(256, 256),
help='Max output size')
@click.option('--method', 'opt_scale_method',
type=click.Choice(methods.keys()),
default='lanczos',
help='Scaling method to use')
@click.option('--equalize', 'opt_equalize', is_flag=True,
help='Equalize historgram')
@click.option('--sharpen', 'opt_sharpen', is_flag=True,
help='Unsharp mask')
@click.option('--center', 'opt_center', default='cc', type=click.Choice(centerings.keys()),
help='Crop focal point')
@click.option('--slice', 'opt_slice', type=(int, int), default=(None, None),
help='Slice the input list')
@click.option('-t', '--threads', 'opt_threads', default=8,
help='Number of threads')
@click.pass_context
def cli(ctx, opt_dir_in, opt_dir_out, opt_glob_ext, opt_size, opt_scale_method,
opt_equalize, opt_sharpen, opt_center, opt_slice, opt_threads):
"""Crop, mirror images"""
import os
from os.path import join
from pathlib import Path
from glob import glob
from tqdm import tqdm
from multiprocessing.dummy import Pool as ThreadPool
from functools import partial
from app.utils import logger_utils, file_utils, im_utils
# -------------------------------------------------
# init
log = logger_utils.Logger.getLogger()
# -------------------------------------------------
# process here
def pool_resize(fp_im, opt_size, scale_method):
# Threaded image resize function
try:
pbar.update(1)
try:
im = Image.open(fp_im).convert('RGB')
im.verify()
except Exception as e:
log.warn('Could not open: {}'.format(fp_im))
log.error(e)
return False
#im = ImageOps.fit(im, opt_size, method=scale_method, centering=centering)
if opt_equalize:
im_np = im_utils.pil2np(im)
im_np_eq = eq_hist_yuv(im_np)
im_np = cv.addWeighted(im_np_eq, 0.35, im_np, 0.65, 0)
im = im_utils.np2pil(im_np)
if opt_sharpen:
im = im.filter(ImageFilter.UnsharpMask)
fp_out = join(opt_dir_out, Path(fp_im).name)
im.save(fp_out)
return True
except:
return False
#centering = centerings[opt_center]
#scale_method = methods[opt_scale_method]
# get list of files to process
fp_ims = glob(join(opt_dir_in, '*.{}'.format(opt_glob_ext)))
if opt_slice:
fp_ims = fp_ims[opt_slice[0]:opt_slice[1]]
log.info('processing {:,} files'.format(len(fp_ims)))
# ensure output dir exists
file_utils.mkdirs(opt_dir_out)
# setup multithreading
pbar = tqdm(total=len(fp_ims))
#pool_resize = partial(pool_resize, opt_size=opt_size, scale_method=scale_method, centering=centering)
pool_resize = partial(pool_resize, opt_size=opt_size)
#result_list = pool.map(prod_x, data_list)
pool = ThreadPool(opt_threads)
with tqdm(total=len(fp_ims)) as pbar:
results = pool.map(pool_resize, fp_ims)
pbar.close()
log.info('Resized: {} / {} images'.format(results.count(True), len(fp_ims)))
def eq_hist_yuv(im):
im_yuv = cv.cvtColor(im, cv.COLOR_BGR2YUV)
im_yuv[:,:,0] = cv.equalizeHist(im_yuv[:,:,0])
return cv.cvtColor(im_yuv, cv.COLOR_YUV2BGR)
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