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wip: add adetailer

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This commit is contained in:
Manuel Schmid
2024-06-08 23:30:45 +02:00
parent bb72938261
commit df70294a3e
8 changed files with 878 additions and 5 deletions
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modules/async_worker.py
+47 -4
View File
@@ -229,7 +229,7 @@ def worker():
def process_task(all_steps, async_task, callback, controlnet_canny_path, controlnet_cpds_path, current_task_id,
denoising_strength, final_scheduler_name, goals, initial_latent, switch, task, tasks,
tiled, use_expansion, width, height):
tiled, use_expansion, width, height, cleanup_conds=True):
if async_task.last_stop is not False:
ldm_patched.modules.model_management.interrupt_current_processing()
positive_cond, negative_cond = task['c'], task['uc']
@@ -260,7 +260,8 @@ def worker():
refiner_swap_method=async_task.refiner_swap_method,
disable_preview=async_task.disable_preview
)
del task['c'], task['uc'], positive_cond, negative_cond # Save memory
if cleanup_conds:
del task['c'], task['uc'], positive_cond, negative_cond # Save memory
if inpaint_worker.current_task is not None:
imgs = [inpaint_worker.current_task.post_process(x) for x in imgs]
current_progress = int(flags.preparation_step_count + (100 - flags.preparation_step_count) * float(
@@ -1007,9 +1008,51 @@ def worker():
execution_start_time = time.perf_counter()
try:
process_task(all_steps, async_task, callback, controlnet_canny_path, controlnet_cpds_path,
imgs, img_paths = process_task(all_steps, async_task, callback, controlnet_canny_path, controlnet_cpds_path,
current_task_id, denoising_strength, final_scheduler_name, goals, initial_latent,
switch, task, tasks, tiled, use_expansion, width, height)
switch, task, tasks, tiled, use_expansion, width, height, False)
# adetailer
for img in imgs:
from extras.adetailer.ultralytics_predict import ultralytics_predict
predictor = ultralytics_predict
from extras.adetailer.script import get_ad_model
ad_model = get_ad_model('face_yolov8n.pt')
kwargs = {}
kwargs["device"] = torch.device('cpu')
kwargs["classes"] = ""
from PIL import Image
img2 = Image.fromarray(img)
pred = predictor(ad_model, img2, **kwargs)
if pred.preview is None:
print(
f"[-] ADetailer: nothing detected on image"
)
return False
from extras.adetailer.args import ADetailerArgs
args = ADetailerArgs()
from extras.adetailer.script import pred_preprocessing
masks = pred_preprocessing(img, pred, args)
merged_masks = np.maximum(*[np.array(mask) for mask in masks])
async_task.yields.append(['preview', (100, '...', merged_masks)])
denoising_strength = 0.5
inpaint_head_model_path = None
inpaint_parameterized = False
denoising_strength, initial_latent, width, height = apply_inpaint(async_task, None,
inpaint_head_model_path, img,
merged_masks,
inpaint_parameterized,
denoising_strength, switch)
imgs, img_paths = process_task(all_steps, async_task, callback, controlnet_canny_path,
controlnet_cpds_path,
current_task_id, denoising_strength, final_scheduler_name, goals,
initial_latent,
switch, task, tasks, tiled, use_expansion, width, height)
except ldm_patched.modules.model_management.InterruptProcessingException:
if async_task.last_stop == 'skip':
print('User skipped')
modules/config.py
+1
View File
@@ -191,6 +191,7 @@ def get_dir_or_set_default(key, default_value, as_array=False, make_directory=Fa
paths_checkpoints = get_dir_or_set_default('path_checkpoints', ['../models/checkpoints/'], True)
paths_loras = get_dir_or_set_default('path_loras', ['../models/loras/'], True)
path_embeddings = get_dir_or_set_default('path_embeddings', '../models/embeddings/')
path_adetailer = get_dir_or_set_default('path_adetailer', '../models/adetailer/')
path_vae_approx = get_dir_or_set_default('path_vae_approx', '../models/vae_approx/')
path_vae = get_dir_or_set_default('path_vae', '../models/vae/')
path_upscale_models = get_dir_or_set_default('path_upscale_models', '../models/upscale_models/')