Public/automatic
1
0
Fork 0
mirror of https://github.com/vladmandic/automatic synced 2026-09-18 16:54:33 +02:00
Code Issues Packages Projects Releases Wiki Activity

merge detailer annotations

Browse Source 
Signed-off-by: Vladimir Mandic <mandic00@live.com>
This commit is contained in:
Vladimir Mandic
2025-11-03 13:50:38 -05:00
parent 00666ef68c
commit dcdb8d3a29
1 changed files with 16 additions and 9 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/postprocess/yolo.py
+16 -9
View File
@@ -38,7 +38,7 @@ class YoloResult:
self.height = height
self.args = args
def __str__(self):
def __repl__(self):
return f'cls={self.cls} label={self.label} score={self.score} box={self.box} mask={self.mask} item={self.item} size={self.width}x{self.height} args={self.args}'
@@ -217,14 +217,18 @@ class YoloRestorer(Detailer):
return [merged]
def draw_boxes(self, image: Image.Image, items: list[YoloResult]) -> Image.Image:
annotated = image.copy()
draw = ImageDraw.Draw(annotated)
if isinstance(image, Image.Image):
draw = ImageDraw.Draw(image)
else:
image = Image.fromarray(image)
draw = ImageDraw.Draw(image)
font = images.get_font(16)
shared.log.debug(f'Detailer: draw={items}')
for i, item in enumerate(items):
draw.rectangle(item.box, outline="#00C8C8", width=3)
draw.text((item.box[0]+4, item.box[1]+4), f'{i+1} {item.label} {item.score:.2f}', fill="black", font=font)
draw.text((item.box[0]+2, item.box[1]+2), f'{i+1} {item.label} {item.score:.2f}', fill="white", font=font)
return np.array(annotated)
return np.array(image)
def restore(self, np_image, p: processing.StableDiffusionProcessing = None):
if shared.state.interrupted or shared.state.skipped:
@@ -252,6 +256,7 @@ class YoloRestorer(Detailer):
orig_cls = p.__class__
models_used = []
np_images = []
annotated = Image.fromarray(np_image)
for i, model_val in enumerate(models):
if ':' in model_val:
@@ -339,8 +344,8 @@ class YoloRestorer(Detailer):
if p.steps < 1:
p.steps = orig_p.get('steps', 0)
report = [{'label': i.label, 'score': i.score, 'size': f'{i.width}x{i.height}' } for i in items]
shared.log.info(f'Detailer: model="{name}" items={report} args={args}')
# report = [{'label': i.label, 'score': i.score, 'size': f'{i.width}x{i.height}' } for i in items]
# shared.log.info(f'Detailer: model="{name}" items={report} args={args}')
models_used.append(name)
mask_all = []
@@ -356,7 +361,7 @@ class YoloRestorer(Detailer):
if shared.opts.detailer_sort:
items = sorted(items, key=lambda x: x.box[0]) # sort items left-to-right to improve consistency
if shared.opts.detailer_save:
np_images.append(self.draw_boxes(image, items)) # save debug image with boxes
annotated = self.draw_boxes(annotated, items)
for j, item in enumerate(items):
if item.mask is None:
@@ -364,7 +369,7 @@ class YoloRestorer(Detailer):
pc.keep_prompts = True
pc.prompts = [prompt_lines[(i*len(items)+j) % len(prompt_lines)]]
pc.negative_prompts = [negative_lines[(i*len(items)+j) % len(negative_lines)]]
shared.log.debug(f'Detail: model="{i+1}:{name}" item={j+1}/{len(items)} box={item.box} score={item.score:.2f} prompt="{pc.prompt}"')
shared.log.debug(f'Detail: model="{i+1}:{name}" item={j+1}/{len(items)} box={item.box} label="{item.label} score={item.score:.2f} prompt="{pc.prompt}"')
pc.init_images = [image]
pc.image_mask = [item.mask]
pc.overlay_images = []
@@ -392,13 +397,15 @@ class YoloRestorer(Detailer):
p.state = orig_p.get('state', None)
p.ops = orig_p.get('ops', [])
shared.opts.data['mask_apply_overlay'] = orig_apply_overlay
np_images.append(np.array(image))
if len(mask_all) > 0 and shared.opts.include_mask:
from modules.control.util import blend
p.image_mask = blend([np.array(m) for m in mask_all])
p.image_mask = Image.fromarray(p.image_mask)
np_images.append(np.array(image))
if shared.opts.detailer_save and annotated is not None:
np_images.append(annotated) # save debug image with boxes
return np_images
def change_mode(self, dropdown, text):