mrq/DL-Art-School
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Enable chunk_with_reference to work without centers

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Moving away from this so it doesn't matter too much. Also fixes an issue
with the "ignore" flag.
This commit is contained in:
James Betker 2020-10-17 20:09:08 -06:00
parent b45e132a9d
commit c7f3fc4dd9
2 changed files with 11 additions and 6 deletions
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11
codes/data/chunk_with_reference.py
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@ -8,6 +8,7 @@ class ChunkWithReference:
def __init__(self, opt, path):
self.path = path.path
self.tiles, _ = util.get_image_paths('img', self.path)
self.strict = opt['strict'] if 'strict' in opt.keys() else True
if 'ignore_first' in opt.keys():
self.ignore = opt['ignore_first']
self.tiles = self.tiles[self.ignore:]
@ -22,11 +23,17 @@ class ChunkWithReference:
return img
def __getitem__(self, item):
centers = torch.load(osp.join(self.path, "centers.pt"))[self.ignore:]
centers = torch.load(osp.join(self.path, "centers.pt"))
ref = self.read_image_or_get_zero(osp.join(self.path, "ref.jpg"))
tile = self.read_image_or_get_zero(self.tiles[item])
tile_id = int(osp.splitext(osp.basename(self.tiles[item]))[0])
center, tile_width = centers[tile_id]
if tile_id in centers.keys():
center, tile_width = centers[tile_id]
elif self.strict:
raise FileNotFoundError(tile_id, self.tiles[item])
else:
center = torch.tensor([128,128], dtype=torch.long)
tile_width = 256
mask = np.full(tile.shape[:2] + (1,), fill_value=.1, dtype=tile.dtype)
mask[center[0] - tile_width // 2:center[0] + tile_width // 2, center[1] - tile_width // 2:center[1] + tile_width // 2] = 1

6
codes/scripts/extract_subimages_with_ref.py
View File

@ -5,8 +5,6 @@ import numpy as np
import cv2
from PIL import Image
import data.util as data_util # noqa: E402
import lmdb
import pyarrow
import torch.utils.data as data
from tqdm import tqdm
import torch
@ -16,7 +14,7 @@ def main():
mode = 'single' # single (one input folder) | pair (extract corresponding GT and LR pairs)
split_img = False
opt = {}
opt['n_thread'] = 0
opt['n_thread'] = 2
opt['compression_level'] = 90 # JPEG compression quality rating.
# CV_IMWRITE_PNG_COMPRESSION from 0 to 9. A higher value means a smaller size and longer
# compression time. If read raw images during training, use 0 for faster IO speed.
@ -244,7 +242,7 @@ class TiledDataset(data.Dataset):
h, w, c = img.shape
# Uncomment to filter any image that doesnt meet a threshold size.
if min(h,w) < 1024:
if min(h,w) < 512:
return None
left = 0
right = w