stable-diffusion-webui/scripts/processing_autosized_crop.py

65 lines
3.1 KiB
Python

from PIL import Image
from modules import scripts_postprocessing, ui_components
import gradio as gr
def center_crop(image: Image, w: int, h: int):
iw, ih = image.size
if ih / h < iw / w:
sw = w * ih / h
box = (iw - sw) / 2, 0, iw - (iw - sw) / 2, ih
else:
sh = h * iw / w
box = 0, (ih - sh) / 2, iw, ih - (ih - sh) / 2
return image.resize((w, h), Image.Resampling.LANCZOS, box)
def multicrop_pic(image: Image, mindim, maxdim, minarea, maxarea, objective, threshold):
iw, ih = image.size
err = lambda w, h: 1 - (lambda x: x if x < 1 else 1 / x)(iw / ih / (w / h))
wh = max(((w, h) for w in range(mindim, maxdim + 1, 64) for h in range(mindim, maxdim + 1, 64)
if minarea <= w * h <= maxarea and err(w, h) <= threshold),
key=lambda wh: (wh[0] * wh[1], -err(*wh))[::1 if objective == 'Maximize area' else -1],
default=None
)
return wh and center_crop(image, *wh)
class ScriptPostprocessingAutosizedCrop(scripts_postprocessing.ScriptPostprocessing):
name = "Auto-sized crop"
order = 4020
def ui(self):
with ui_components.InputAccordion(False, label="Auto-sized crop") as enable:
gr.Markdown('Each image is center-cropped with an automatically chosen width and height.')
with gr.Row():
mindim = gr.Slider(minimum=64, maximum=2048, step=8, label="Dimension lower bound", value=384, elem_id="postprocess_multicrop_mindim")
maxdim = gr.Slider(minimum=64, maximum=2048, step=8, label="Dimension upper bound", value=768, elem_id="postprocess_multicrop_maxdim")
with gr.Row():
minarea = gr.Slider(minimum=64 * 64, maximum=2048 * 2048, step=1, label="Area lower bound", value=64 * 64, elem_id="postprocess_multicrop_minarea")
maxarea = gr.Slider(minimum=64 * 64, maximum=2048 * 2048, step=1, label="Area upper bound", value=640 * 640, elem_id="postprocess_multicrop_maxarea")
with gr.Row():
objective = gr.Radio(["Maximize area", "Minimize error"], value="Maximize area", label="Resizing objective", elem_id="postprocess_multicrop_objective")
threshold = gr.Slider(minimum=0, maximum=1, step=0.01, label="Error threshold", value=0.1, elem_id="postprocess_multicrop_threshold")
return {
"enable": enable,
"mindim": mindim,
"maxdim": maxdim,
"minarea": minarea,
"maxarea": maxarea,
"objective": objective,
"threshold": threshold,
}
def process(self, pp: scripts_postprocessing.PostprocessedImage, enable, mindim, maxdim, minarea, maxarea, objective, threshold):
if not enable:
return
cropped = multicrop_pic(pp.image, mindim, maxdim, minarea, maxarea, objective, threshold)
if cropped is not None:
pp.image = cropped
else:
print(f"skipped {pp.image.width}x{pp.image.height} image (can't find suitable size within error threshold)")