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"""
python generate_imagematte_with_background_image.py \
--imagematte-dir ../matting-data/Distinctions/test \
--background-dir ../matting-data/Backgrounds/valid \
--resolution 512 \
--out-dir ../matting-data/evaluation/distinction_static_sd/ \
--random-seed 10
Seed:
10 - distinction-static
11 - distinction-motion
12 - adobe-static
13 - adobe-motion
"""
import argparse
import os
import pims
import numpy as np
import random
from PIL import Image
from tqdm import tqdm
from tqdm.contrib.concurrent import process_map
from torchvision import transforms
from torchvision.transforms import functional as F
parser = argparse.ArgumentParser()
parser.add_argument('--imagematte-dir', type=str, required=True)
parser.add_argument('--background-dir', type=str, required=True)
parser.add_argument('--num-samples', type=int, default=20)
parser.add_argument('--num-frames', type=int, default=100)
parser.add_argument('--resolution', type=int, required=True)
parser.add_argument('--out-dir', type=str, required=True)
parser.add_argument('--random-seed', type=int)
parser.add_argument('--extension', type=str, default='.png')
args = parser.parse_args()
random.seed(args.random_seed)
imagematte_filenames = os.listdir(os.path.join(args.imagematte_dir, 'fgr'))
background_filenames = os.listdir(args.background_dir)
random.shuffle(imagematte_filenames)
random.shuffle(background_filenames)
def lerp(a, b, percentage):
return a * (1 - percentage) + b * percentage
def motion_affine(*imgs):
config = dict(degrees=(-10, 10), translate=(0.1, 0.1),
scale_ranges=(0.9, 1.1), shears=(-5, 5), img_size=imgs[0][0].size)
angleA, (transXA, transYA), scaleA, (shearXA, shearYA) = transforms.RandomAffine.get_params(**config)
angleB, (transXB, transYB), scaleB, (shearXB, shearYB) = transforms.RandomAffine.get_params(**config)
T = len(imgs[0])
variation_over_time = random.random()
for t in range(T):
percentage = (t / (T - 1)) * variation_over_time
angle = lerp(angleA, angleB, percentage)
transX = lerp(transXA, transXB, percentage)
transY = lerp(transYA, transYB, percentage)
scale = lerp(scaleA, scaleB, percentage)
shearX = lerp(shearXA, shearXB, percentage)
shearY = lerp(shearYA, shearYB, percentage)
for img in imgs:
img[t] = F.affine(img[t], angle, (transX, transY), scale, (shearX, shearY), F.InterpolationMode.BILINEAR)
return imgs
def process(i):
imagematte_filename = imagematte_filenames[i % len(imagematte_filenames)]
background_filename = background_filenames[i % len(background_filenames)]
out_path = os.path.join(args.out_dir, str(i).zfill(4))
os.makedirs(os.path.join(out_path, 'fgr'), exist_ok=True)
os.makedirs(os.path.join(out_path, 'pha'), exist_ok=True)
os.makedirs(os.path.join(out_path, 'com'), exist_ok=True)
os.makedirs(os.path.join(out_path, 'bgr'), exist_ok=True)
with Image.open(os.path.join(args.background_dir, background_filename)) as bgr:
bgr = bgr.convert('RGB')
w, h = bgr.size
scale = args.resolution / min(h, w)
w, h = int(w * scale), int(h * scale)
bgr = bgr.resize((w, h))
bgr = F.center_crop(bgr, (args.resolution, args.resolution))
with Image.open(os.path.join(args.imagematte_dir, 'fgr', imagematte_filename)) as fgr, \
Image.open(os.path.join(args.imagematte_dir, 'pha', imagematte_filename)) as pha:
fgr = fgr.convert('RGB')
pha = pha.convert('L')
fgrs = [fgr] * args.num_frames
phas = [pha] * args.num_frames
fgrs, phas = motion_affine(fgrs, phas)
for t in tqdm(range(args.num_frames), desc=str(i).zfill(4)):
fgr = fgrs[t]
pha = phas[t]
w, h = fgr.size
scale = args.resolution / max(h, w)
w, h = int(w * scale), int(h * scale)
fgr = fgr.resize((w, h))
pha = pha.resize((w, h))
if h < args.resolution:
pt = (args.resolution - h) // 2
pb = args.resolution - h - pt
else:
pt = 0
pb = 0
if w < args.resolution:
pl = (args.resolution - w) // 2
pr = args.resolution - w - pl
else:
pl = 0
pr = 0
fgr = F.pad(fgr, [pl, pt, pr, pb])
pha = F.pad(pha, [pl, pt, pr, pb])
if i // len(imagematte_filenames) % 2 == 1:
fgr = fgr.transpose(Image.FLIP_LEFT_RIGHT)
pha = pha.transpose(Image.FLIP_LEFT_RIGHT)
fgr.save(os.path.join(out_path, 'fgr', str(t).zfill(4) + args.extension))
pha.save(os.path.join(out_path, 'pha', str(t).zfill(4) + args.extension))
if t == 0:
bgr.save(os.path.join(out_path, 'bgr', str(t).zfill(4) + args.extension))
else:
os.symlink(str(0).zfill(4) + args.extension, os.path.join(out_path, 'bgr', str(t).zfill(4) + args.extension))
pha = np.asarray(pha).astype(float)[:, :, None] / 255
com = Image.fromarray(np.uint8(np.asarray(fgr) * pha + np.asarray(bgr) * (1 - pha)))
com.save(os.path.join(out_path, 'com', str(t).zfill(4) + args.extension))
if __name__ == '__main__':
r = process_map(process, range(args.num_samples), max_workers=32) |