move functions out of main body for image preprocessing for easier hijacking

This commit is contained in:
AUTOMATIC 2022-11-08 08:37:05 +03:00
parent c5334fc56b
commit 8011be33c3

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@ -35,6 +35,84 @@ def preprocess(process_src, process_dst, process_width, process_height, preproce
deepbooru.release_process()
def listfiles(dirname):
return os.listdir(dirname)
class PreprocessParams:
src = None
dstdir = None
subindex = 0
flip = False
process_caption = False
process_caption_deepbooru = False
preprocess_txt_action = None
def save_pic_with_caption(image, index, params: PreprocessParams, existing_caption=None):
caption = ""
if params.process_caption:
caption += shared.interrogator.generate_caption(image)
if params.process_caption_deepbooru:
if len(caption) > 0:
caption += ", "
caption += deepbooru.get_tags_from_process(image)
filename_part = params.src
filename_part = os.path.splitext(filename_part)[0]
filename_part = os.path.basename(filename_part)
basename = f"{index:05}-{params.subindex}-{filename_part}"
image.save(os.path.join(params.dstdir, f"{basename}.png"))
if params.preprocess_txt_action == 'prepend' and existing_caption:
caption = existing_caption + ' ' + caption
elif params.preprocess_txt_action == 'append' and existing_caption:
caption = caption + ' ' + existing_caption
elif params.preprocess_txt_action == 'copy' and existing_caption:
caption = existing_caption
caption = caption.strip()
if len(caption) > 0:
with open(os.path.join(params.dstdir, f"{basename}.txt"), "w", encoding="utf8") as file:
file.write(caption)
params.subindex += 1
def save_pic(image, index, params, existing_caption=None):
save_pic_with_caption(image, index, params, existing_caption=existing_caption)
if params.flip:
save_pic_with_caption(ImageOps.mirror(image), index, params, existing_caption=existing_caption)
def split_pic(image, inverse_xy, width, height, overlap_ratio):
if inverse_xy:
from_w, from_h = image.height, image.width
to_w, to_h = height, width
else:
from_w, from_h = image.width, image.height
to_w, to_h = width, height
h = from_h * to_w // from_w
if inverse_xy:
image = image.resize((h, to_w))
else:
image = image.resize((to_w, h))
split_count = math.ceil((h - to_h * overlap_ratio) / (to_h * (1.0 - overlap_ratio)))
y_step = (h - to_h) / (split_count - 1)
for i in range(split_count):
y = int(y_step * i)
if inverse_xy:
splitted = image.crop((y, 0, y + to_h, to_w))
else:
splitted = image.crop((0, y, to_w, y + to_h))
yield splitted
def preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False):
width = process_width
@ -48,82 +126,28 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre
os.makedirs(dst, exist_ok=True)
files = os.listdir(src)
files = listfiles(src)
shared.state.textinfo = "Preprocessing..."
shared.state.job_count = len(files)
def save_pic_with_caption(image, index, existing_caption=None):
caption = ""
if process_caption:
caption += shared.interrogator.generate_caption(image)
if process_caption_deepbooru:
if len(caption) > 0:
caption += ", "
caption += deepbooru.get_tags_from_process(image)
filename_part = filename
filename_part = os.path.splitext(filename_part)[0]
filename_part = os.path.basename(filename_part)
basename = f"{index:05}-{subindex[0]}-{filename_part}"
image.save(os.path.join(dst, f"{basename}.png"))
if preprocess_txt_action == 'prepend' and existing_caption:
caption = existing_caption + ' ' + caption
elif preprocess_txt_action == 'append' and existing_caption:
caption = caption + ' ' + existing_caption
elif preprocess_txt_action == 'copy' and existing_caption:
caption = existing_caption
caption = caption.strip()
if len(caption) > 0:
with open(os.path.join(dst, f"{basename}.txt"), "w", encoding="utf8") as file:
file.write(caption)
subindex[0] += 1
def save_pic(image, index, existing_caption=None):
save_pic_with_caption(image, index, existing_caption=existing_caption)
if process_flip:
save_pic_with_caption(ImageOps.mirror(image), index, existing_caption=existing_caption)
def split_pic(image, inverse_xy):
if inverse_xy:
from_w, from_h = image.height, image.width
to_w, to_h = height, width
else:
from_w, from_h = image.width, image.height
to_w, to_h = width, height
h = from_h * to_w // from_w
if inverse_xy:
image = image.resize((h, to_w))
else:
image = image.resize((to_w, h))
split_count = math.ceil((h - to_h * overlap_ratio) / (to_h * (1.0 - overlap_ratio)))
y_step = (h - to_h) / (split_count - 1)
for i in range(split_count):
y = int(y_step * i)
if inverse_xy:
splitted = image.crop((y, 0, y + to_h, to_w))
else:
splitted = image.crop((0, y, to_w, y + to_h))
yield splitted
params = PreprocessParams()
params.dstdir = dst
params.flip = process_flip
params.process_caption = process_caption
params.process_caption_deepbooru = process_caption_deepbooru
params.preprocess_txt_action = preprocess_txt_action
for index, imagefile in enumerate(tqdm.tqdm(files)):
subindex = [0]
params.subindex = 0
filename = os.path.join(src, imagefile)
try:
img = Image.open(filename).convert("RGB")
except Exception:
continue
params.src = filename
existing_caption = None
existing_caption_filename = os.path.splitext(filename)[0] + '.txt'
if os.path.exists(existing_caption_filename):
@ -143,8 +167,8 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre
process_default_resize = True
if process_split and ratio < 1.0 and ratio <= split_threshold:
for splitted in split_pic(img, inverse_xy):
save_pic(splitted, index, existing_caption=existing_caption)
for splitted in split_pic(img, inverse_xy, width, height, overlap_ratio):
save_pic(splitted, index, params, existing_caption=existing_caption)
process_default_resize = False
if process_focal_crop and img.height != img.width:
@ -165,11 +189,11 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre
dnn_model_path = dnn_model_path,
)
for focal in autocrop.crop_image(img, autocrop_settings):
save_pic(focal, index, existing_caption=existing_caption)
save_pic(focal, index, params, existing_caption=existing_caption)
process_default_resize = False
if process_default_resize:
img = images.resize_image(1, img, width, height)
save_pic(img, index, existing_caption=existing_caption)
save_pic(img, index, params, existing_caption=existing_caption)
shared.state.nextjob()
shared.state.nextjob()