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from time import perf_counter
from typing import Any, Iterator
import gradio as gr
from modules import scripts, shared as webui_shared
from modules.options import Options
from modules.processing import Processed, StableDiffusionProcessingImg2Img, fix_seed
from modules.shared_state import State
from modules.styles import StyleDatabase
from temporal.interop import EXTENSION_DIR, get_cn_units
from temporal.pipeline_modules.measuring import MeasuringModule
from temporal.preset import Preset
from temporal.project import Project
from temporal.shared import shared
from temporal.ui import CallbackInputs, CallbackOutputs, UI
from temporal.ui.fs_store_list import FSStoreList, FSStoreListEntry
from temporal.ui.gradio_widget import GradioWidget
from temporal.ui.options_editor import OptionsEditor
from temporal.ui.paginator import Paginator
from temporal.ui.project_editor import ProjectEditor
from temporal.ui.video_renderer_editor import VideoRendererEditor
from temporal.utils import logging
from temporal.utils.fs import load_text
from temporal.utils.image import PILImage, ensure_image_dims, np_to_pil, pil_to_np
from temporal.utils.object import copy_with_overrides
from temporal.utils.time import wait_until
from temporal.video_renderer import video_render_queue
from temporal.web_ui import process_images
# FIXME: To shut up the type checker
opts: Options = getattr(webui_shared, "opts")
prompt_styles: StyleDatabase = getattr(webui_shared, "prompt_styles")
state: State = getattr(webui_shared, "state")
class TemporalScript(scripts.Script):
def __init__(self, *args: Any, **kwargs: Any) -> None:
super().__init__(*args, **kwargs)
shared.init(EXTENSION_DIR / "settings", EXTENSION_DIR / "presets")
def title(self) -> str:
return "Temporal"
def show(self, is_img2img: bool) -> Any:
return is_img2img
def ui(self, is_img2img: bool) -> Any:
self._ui = UI()
stored_preset = FSStoreList(label = "Preset", store = shared.preset_store, features = ["load", "save", "rename", "delete"])
stored_project = FSStoreList(label = "Project", store = shared.project_store, features = ["load", "rename", "delete"])
with GradioWidget(gr.Tab, label = "General"):
load_parameters = GradioWidget(gr.Checkbox, label = "Load parameters", value = True)
continue_from_last_frame = GradioWidget(gr.Checkbox, label = "Continue from last frame", value = True)
iter_count = GradioWidget(gr.Number, label = "Iteration count", precision = 0, minimum = 1, step = 1, value = 100)
with GradioWidget(gr.Tab, label = "Information"):
description = GradioWidget(gr.Textbox, label = "Description", lines = 5, max_lines = 5, interactive = False)
gallery = GradioWidget(gr.Gallery, label = "Gallery", columns = 4, object_fit = "contain", preview = True)
gallery_page = Paginator(label = "Page", minimum = 1, value = 1)
gallery_parallel = Paginator(label = "Parallel", minimum = 1, value = 1)
with GradioWidget(gr.Tab, label = "Pipeline"):
project = ProjectEditor()
with GradioWidget(gr.Tab, label = "Video Rendering"):
video_renderer = VideoRendererEditor(value = shared.video_renderer)
video_parallel_index = GradioWidget(gr.Number, label = "Parallel index", precision = 0, minimum = 1, step = 1, value = 1)
with GradioWidget(gr.Row):
render_draft = GradioWidget(gr.Button, value = "Render draft")
render_final = GradioWidget(gr.Button, value = "Render final")
video_preview = GradioWidget(gr.Video, label = "Preview", format = "mp4", interactive = False)
with GradioWidget(gr.Tab, label = "Measuring"):
measuring_parallel_index = GradioWidget(gr.Number, label = "Parallel index", precision = 0, minimum = 1, step = 1, value = 1)
render_graphs = GradioWidget(gr.Button, value = "Render graphs")
graph_gallery = GradioWidget(gr.Gallery, label = "Graphs", columns = 4, object_fit = "contain", preview = True)
with GradioWidget(gr.Tab, label = "Tools"):
delete_intermediate_frames = GradioWidget(gr.Button, value = "Delete intermediate frames")
delete_session_data = GradioWidget(gr.Button, value = "Delete session data")
with GradioWidget(gr.Tab, label = "Settings"):
apply_settings = GradioWidget(gr.Button, value = "Apply")
options = OptionsEditor(value = shared.options)
with GradioWidget(gr.Tab, label = "Help"):
for file_name, title in [
("main.md", "Main"),
("tab_project.md", "Project tab"),
("tab_pipeline.md", "Pipeline tab"),
("tab_video_rendering.md", "Video Rendering tab"),
("tab_measuring.md", "Measuring tab"),
("tab_settings.md", "Settings tab"),
]:
with GradioWidget(gr.Accordion, label = title, open = False):
GradioWidget(gr.Markdown, value = load_text(EXTENSION_DIR / "docs" / "temporal" / file_name, ""))
@stored_preset.callback("load", [stored_preset], [stored_project, load_parameters, continue_from_last_frame, iter_count, project, video_renderer])
def _(inputs: CallbackInputs) -> CallbackOutputs:
data = inputs[stored_preset].data.data
return {
stored_project: {"value": data["stored_project"]},
load_parameters: {"value": data["load_parameters"]},
continue_from_last_frame: {"value": data["continue_from_last_frame"]},
iter_count: {"value": data["iter_count"]},
project: {"value": data["project"], "preview_states": data["preview_states"]},
video_renderer: {"value": data["video_renderer"]},
}
@stored_preset.callback("save", [stored_project, load_parameters, continue_from_last_frame, iter_count, project, video_renderer], [stored_preset])
def _(inputs: CallbackInputs) -> CallbackOutputs:
return {stored_preset: {"value": Preset({
"stored_project": inputs[stored_project].name,
"load_parameters": inputs[load_parameters],
"continue_from_last_frame": inputs[continue_from_last_frame],
"iter_count": inputs[iter_count],
"project": inputs[project],
"preview_states": shared.previewed_modules,
"video_renderer": inputs[video_renderer],
})}}
@stored_project.callback("change", [stored_project], [description, gallery, gallery_page, gallery_parallel])
def _(inputs: CallbackInputs) -> CallbackOutputs:
project_obj = inputs[stored_project].data
return {
description: {"value": project_obj.get_description()},
gallery: {"value": project_obj.list_all_frame_paths()[:shared.options.ui.gallery_size]},
gallery_page: {"value": 1},
gallery_parallel: {"value": 1},
}
@stored_project.callback("load", [stored_project], [project])
def _(inputs: CallbackInputs) -> CallbackOutputs:
return {project: {"value": inputs[stored_project].data}}
@gallery_page.callback("change", [stored_project, gallery_page, gallery_parallel], [gallery])
@gallery_parallel.callback("change", [stored_project, gallery_page, gallery_parallel], [gallery])
def _(inputs: CallbackInputs) -> CallbackOutputs:
project_obj = inputs[stored_project].data
page = inputs[gallery_page]
parallel = inputs[gallery_parallel]
gallery_size = shared.options.ui.gallery_size
return {gallery: {"value": project_obj.list_all_frame_paths(parallel)[(page - 1) * gallery_size:page * gallery_size]}}
def render_video(inputs: CallbackInputs, is_final: bool) -> Iterator[CallbackOutputs]:
yield {
render_draft: {"interactive": False},
render_final: {"interactive": False},
}
shared.video_renderer = inputs[video_renderer]
video_path = inputs[stored_project].data.render_video(shared.video_renderer, is_final, inputs[video_parallel_index])
wait_until(lambda: not video_render_queue.busy)
yield {
render_draft: {"interactive": True},
render_final: {"interactive": True},
video_preview: {"value": video_path.as_posix()},
}
@render_draft.callback("click", [stored_project, video_renderer, video_parallel_index], [render_draft, render_final, video_preview])
def _(inputs: CallbackInputs) -> Iterator[CallbackOutputs]:
yield from render_video(inputs, False)
@render_final.callback("click", [stored_project, video_renderer, video_parallel_index], [render_draft, render_final, video_preview])
def _(inputs: CallbackInputs) -> Iterator[CallbackOutputs]:
yield from render_video(inputs, True)
@render_graphs.callback("click", [stored_project, measuring_parallel_index], [graph_gallery])
def _(inputs: CallbackInputs) -> CallbackOutputs:
return {graph_gallery: {"value": [
x.plot(inputs[measuring_parallel_index] - 1)
for x in inputs[stored_project].data.pipeline.modules
if isinstance(x, MeasuringModule) and x.enabled
]}}
@delete_intermediate_frames.callback("click", [stored_project], [description, gallery])
def _(inputs: CallbackInputs) -> CallbackOutputs:
project_obj = inputs[stored_project].data
project_obj.delete_intermediate_frames()
return {
description: {"value": project_obj.get_description()},
gallery: {"value": project_obj.list_all_frame_paths()[:shared.options.ui.gallery_size]},
}
@delete_session_data.callback("click", [stored_project], [])
def _(inputs: CallbackInputs) -> CallbackOutputs:
project_obj = inputs[stored_project].data
project_obj.delete_session_data()
project_obj.save(project_obj.path)
return {}
@apply_settings.callback("click", [options], [])
def _(inputs: CallbackInputs) -> CallbackOutputs:
shared.options = inputs[options]
shared.options.save(EXTENSION_DIR / "settings")
return {}
return self._ui.finalize(stored_project, load_parameters, continue_from_last_frame, iter_count, project)
def run(self, p: StableDiffusionProcessingImg2Img, *args: Any) -> Any:
stored_project: FSStoreListEntry[Project]
load_parameters: bool
continue_from_last_frame: bool
iter_count: int
project: Project
stored_project, load_parameters, continue_from_last_frame, iter_count, project = self._ui.recombine(*args)
opts_backup = opts.data.copy()
opts.save_to_dirs = False
if shared.options.live_preview.show_only_finished_images:
opts.show_progress_every_n_steps = -1
p.prompt = prompt_styles.apply_styles_to_prompt(p.prompt, p.styles)
p.negative_prompt = prompt_styles.apply_negative_styles_to_prompt(p.negative_prompt, p.styles)
p.styles.clear()
fix_seed(p)
project.path = stored_project.data.path
project.options = opts
project.processing = p
project.controlnet_units = get_cn_units(p)
if load_parameters:
project.load(stored_project.data.path)
if not continue_from_last_frame:
project.delete_all_frames()
project.delete_session_data()
if not p.init_images or not isinstance(p.init_images[0], PILImage):
noises = [
project.initial_noise.noise.generate((p.height, p.width, 3), p.seed, i)
for i in range(project.pipeline.parallel)
]
if project.initial_noise.factor < 1.0:
if not (processed_images := process_images(
copy_with_overrides(p,
denoising_strength = 1.0 - project.initial_noise.factor,
do_not_save_samples = True,
do_not_save_grid = True,
),
[(np_to_pil(x), p.seed + i, 1) for i, x in enumerate(noises)],
shared.options.processing.pixels_per_batch,
True,
)):
opts.data.update(opts_backup)
return Processed(p, p.init_images)
p.init_images = [image_array[0] for image_array in processed_images]
else:
p.init_images = noises
elif len(p.init_images) != project.pipeline.parallel:
p.init_images = [p.init_images[0]] * project.pipeline.parallel
if not project.iteration.images:
project.iteration.images[:] = [pil_to_np(ensure_image_dims(x, "RGB", (p.width, p.height))) for x in p.init_images]
last_images = project.iteration.images.copy()
state.job_count = iter_count
for i in range(iter_count):
logging.info(f"Iteration {i + 1} / {iter_count}")
start_time = perf_counter()
state.job = "Temporal main loop"
state.job_no = i
if not project.pipeline.run(project):
break
last_images = project.iteration.images.copy()
if i % shared.options.output.autosave_every_n_iterations == 0:
project.save(project.path)
end_time = perf_counter()
logging.info(f"Iteration took {end_time - start_time:.6f} second(s)")
project.pipeline.finalize(project)
project.save(project.path)
state.end()
opts.data.update(opts_backup)
return Processed(p, [np_to_pil(x) for x in last_images])
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