mirror of
https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
synced 2024-06-07 21:20:49 +00:00
91bfc71261
SD upscale moved to scripts Batch processing script removed Batch processing added to main img2img and now works with scripts img2img page UI reworked to use tabs
136 lines
5.0 KiB
Python
136 lines
5.0 KiB
Python
import os
|
|
|
|
import numpy as np
|
|
from PIL import Image
|
|
|
|
from modules import processing, shared, images, devices
|
|
from modules.shared import opts
|
|
import modules.gfpgan_model
|
|
from modules.ui import plaintext_to_html
|
|
import modules.codeformer_model
|
|
import piexif
|
|
import piexif.helper
|
|
|
|
|
|
cached_images = {}
|
|
|
|
|
|
def run_extras(extras_mode, image, image_folder, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility):
|
|
devices.torch_gc()
|
|
|
|
imageArr = []
|
|
# Also keep track of original file names
|
|
imageNameArr = []
|
|
|
|
if extras_mode == 1:
|
|
#convert file to pillow image
|
|
for img in image_folder:
|
|
image = Image.fromarray(np.array(Image.open(img)))
|
|
imageArr.append(image)
|
|
imageNameArr.append(os.path.splitext(img.orig_name)[0])
|
|
else:
|
|
imageArr.append(image)
|
|
imageNameArr.append(None)
|
|
|
|
outpath = opts.outdir_samples or opts.outdir_extras_samples
|
|
|
|
outputs = []
|
|
for image, image_name in zip(imageArr, imageNameArr):
|
|
existing_pnginfo = image.info or {}
|
|
|
|
image = image.convert("RGB")
|
|
info = ""
|
|
|
|
if gfpgan_visibility > 0:
|
|
restored_img = modules.gfpgan_model.gfpgan_fix_faces(np.array(image, dtype=np.uint8))
|
|
res = Image.fromarray(restored_img)
|
|
|
|
if gfpgan_visibility < 1.0:
|
|
res = Image.blend(image, res, gfpgan_visibility)
|
|
|
|
info += f"GFPGAN visibility:{round(gfpgan_visibility, 2)}\n"
|
|
image = res
|
|
|
|
if codeformer_visibility > 0:
|
|
restored_img = modules.codeformer_model.codeformer.restore(np.array(image, dtype=np.uint8), w=codeformer_weight)
|
|
res = Image.fromarray(restored_img)
|
|
|
|
if codeformer_visibility < 1.0:
|
|
res = Image.blend(image, res, codeformer_visibility)
|
|
|
|
info += f"CodeFormer w: {round(codeformer_weight, 2)}, CodeFormer visibility:{round(codeformer_visibility, 2)}\n"
|
|
image = res
|
|
|
|
if upscaling_resize != 1.0:
|
|
def upscale(image, scaler_index, resize):
|
|
small = image.crop((image.width // 2, image.height // 2, image.width // 2 + 10, image.height // 2 + 10))
|
|
pixels = tuple(np.array(small).flatten().tolist())
|
|
key = (resize, scaler_index, image.width, image.height, gfpgan_visibility, codeformer_visibility, codeformer_weight) + pixels
|
|
|
|
c = cached_images.get(key)
|
|
if c is None:
|
|
upscaler = shared.sd_upscalers[scaler_index]
|
|
c = upscaler.upscale(image, image.width * resize, image.height * resize)
|
|
cached_images[key] = c
|
|
|
|
return c
|
|
|
|
info += f"Upscale: {round(upscaling_resize, 3)}, model:{shared.sd_upscalers[extras_upscaler_1].name}\n"
|
|
res = upscale(image, extras_upscaler_1, upscaling_resize)
|
|
|
|
if extras_upscaler_2 != 0 and extras_upscaler_2_visibility > 0:
|
|
res2 = upscale(image, extras_upscaler_2, upscaling_resize)
|
|
info += f"Upscale: {round(upscaling_resize, 3)}, visibility: {round(extras_upscaler_2_visibility, 3)}, model:{shared.sd_upscalers[extras_upscaler_2].name}\n"
|
|
res = Image.blend(res, res2, extras_upscaler_2_visibility)
|
|
|
|
image = res
|
|
|
|
while len(cached_images) > 2:
|
|
del cached_images[next(iter(cached_images.keys()))]
|
|
|
|
images.save_image(image, path=outpath, basename="", seed=None, prompt=None, extension=opts.samples_format, info=info, short_filename=True,
|
|
no_prompt=True, grid=False, pnginfo_section_name="extras", existing_info=existing_pnginfo,
|
|
forced_filename=image_name if opts.use_original_name_batch else None)
|
|
|
|
outputs.append(image)
|
|
|
|
return outputs, plaintext_to_html(info), ''
|
|
|
|
|
|
def run_pnginfo(image):
|
|
if image is None:
|
|
return '', '', ''
|
|
|
|
items = image.info
|
|
|
|
if "exif" in image.info:
|
|
exif = piexif.load(image.info["exif"])
|
|
exif_comment = (exif or {}).get("Exif", {}).get(piexif.ExifIFD.UserComment, b'')
|
|
try:
|
|
exif_comment = piexif.helper.UserComment.load(exif_comment)
|
|
except ValueError:
|
|
exif_comment = exif_comment.decode('utf8', errors="ignore")
|
|
|
|
|
|
items['exif comment'] = exif_comment
|
|
|
|
for field in ['jfif', 'jfif_version', 'jfif_unit', 'jfif_density', 'dpi', 'exif',
|
|
'loop', 'background', 'timestamp', 'duration']:
|
|
items.pop(field, None)
|
|
|
|
|
|
info = ''
|
|
for key, text in items.items():
|
|
info += f"""
|
|
<div>
|
|
<p><b>{plaintext_to_html(str(key))}</b></p>
|
|
<p>{plaintext_to_html(str(text))}</p>
|
|
</div>
|
|
""".strip()+"\n"
|
|
|
|
if len(info) == 0:
|
|
message = "Nothing found in the image."
|
|
info = f"<div><p>{message}<p></div>"
|
|
|
|
return '', '', info
|