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unified logger

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Vladimir Mandic
2026-02-19 09:46:42 +01:00
parent bfe014f5da
commit a3074baf8b
315 changed files with 2507 additions and 2116 deletions
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scripts/image2video.py
+7 -6
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@@ -2,6 +2,7 @@ import torch
import gradio as gr
import diffusers
from modules import scripts_manager, processing, shared, images, sd_models, devices
from modules import logger
MODELS = [
@@ -58,16 +59,16 @@ class Script(scripts_manager.Script):
return None
model = [m for m in MODELS if m['name'] == model_name][0]
repo_id = model['url']
shared.log.debug(f'Image2Video: model={model_name} frames={num_frames}, video={video_type} duration={duration} loop={gif_loop} pad={mp4_pad} interpolate={mp4_interpolate}')
logger.log.debug(f'Image2Video: model={model_name} frames={num_frames}, video={video_type} duration={duration} loop={gif_loop} pad={mp4_pad} interpolate={mp4_interpolate}')
p.ops.append('video')
p.do_not_save_grid = True
orig_pipeline = shared.sd_model
if model_name == 'PIA':
if shared.sd_model_type != 'sd':
shared.log.error('Image2Video PIA: base model must be SD15')
logger.log.error('Image2Video PIA: base model must be SD15')
return None
shared.log.info(f'Image2Video PIA load: model={repo_id}')
logger.log.info(f'Image2Video PIA load: model={repo_id}')
motion_adapter = diffusers.MotionAdapter.from_pretrained(repo_id)
sd_models.move_model(motion_adapter, devices.device)
shared.sd_model = sd_models.switch_pipe(diffusers.PIAPipeline, shared.sd_model, { 'motion_adapter': motion_adapter })
@@ -84,14 +85,14 @@ class Script(scripts_manager.Script):
spatial_stop_frequency=fi_spatial,
temporal_stop_frequency=fi_temporal,
)
shared.log.debug(f'Image2Video PIA: args={p.task_args}')
logger.log.debug(f'Image2Video PIA: args={p.task_args}')
processed = processing.process_images(p)
shared.sd_model.motion_adapter = None
processed = None
if model_name == 'VGen':
if not isinstance(shared.sd_model, diffusers.I2VGenXLPipeline):
shared.log.info(f'Image2Video VGen load: model={repo_id}')
logger.log.info(f'Image2Video VGen load: model={repo_id}')
pipe = diffusers.I2VGenXLPipeline.from_pretrained(repo_id, torch_dtype=devices.dtype, cache_dir=shared.opts.diffusers_dir)
sd_models.copy_diffuser_options(pipe, shared.sd_model)
sd_models.set_diffuser_options(pipe)
@@ -104,7 +105,7 @@ class Script(scripts_manager.Script):
p.task_args['target_fps'] = max(1, int(num_frames * vg_fps))
p.task_args['decode_chunk_size'] = max(1, int(num_frames * vg_chunks))
p.task_args['output_type'] = 'pil'
shared.log.debug(f'Image2Video VGen: args={p.task_args}')
logger.log.debug(f'Image2Video VGen: args={p.task_args}')
processed = processing.process_images(p)
shared.sd_model = orig_pipeline