WebUI/modules/progress.py

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import base64
import io
import time
import gradio as gr
from pydantic import BaseModel, Field
from modules.shared import opts
import modules.shared as shared
current_task = None
pending_tasks = {}
finished_tasks = []
recorded_results = []
recorded_results_limit = 2
def start_task(id_task):
global current_task
current_task = id_task
pending_tasks.pop(id_task, None)
def finish_task(id_task):
global current_task
if current_task == id_task:
current_task = None
finished_tasks.append(id_task)
if len(finished_tasks) > 16:
finished_tasks.pop(0)
def record_results(id_task, res):
recorded_results.append((id_task, res))
if len(recorded_results) > recorded_results_limit:
recorded_results.pop(0)
def add_task_to_queue(id_job):
pending_tasks[id_job] = time.time()
class ProgressRequest(BaseModel):
id_task: str = Field(default=None, title="Task ID", description="id of the task to get progress for")
id_live_preview: int = Field(default=-1, title="Live preview image ID", description="id of last received last preview image")
class ProgressResponse(BaseModel):
active: bool = Field(title="Whether the task is being worked on right now")
queued: bool = Field(title="Whether the task is in queue")
completed: bool = Field(title="Whether the task has already finished")
progress: float = Field(default=None, title="Progress", description="The progress with a range of 0 to 1")
eta: float = Field(default=None, title="ETA in secs")
live_preview: str = Field(default=None, title="Live preview image", description="Current live preview; a data: uri")
id_live_preview: int = Field(default=None, title="Live preview image ID", description="Send this together with next request to prevent receiving same image")
textinfo: str = Field(default=None, title="Info text", description="Info text used by WebUI.")
def setup_progress_api(app):
return app.add_api_route("/internal/progress", progressapi, methods=["POST"], response_model=ProgressResponse)
def progressapi(req: ProgressRequest):
active = req.id_task == current_task
queued = req.id_task in pending_tasks
completed = req.id_task in finished_tasks
if not active:
return ProgressResponse(active=active, queued=queued, completed=completed, id_live_preview=-1, textinfo="In queue..." if queued else "Waiting...")
progress = 0
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job_count, job_no = shared.state.job_count, shared.state.job_no
sampling_steps, sampling_step = shared.state.sampling_steps, shared.state.sampling_step
if job_count > 0:
progress += job_no / job_count
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if sampling_steps > 0 and job_count > 0:
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progress += 1 / job_count * sampling_step / sampling_steps
progress = min(progress, 1)
elapsed_since_start = time.time() - shared.state.time_start
predicted_duration = elapsed_since_start / progress if progress > 0 else None
eta = predicted_duration - elapsed_since_start if predicted_duration is not None else None
id_live_preview = req.id_live_preview
shared.state.set_current_image()
if opts.live_previews_enable and shared.state.id_live_preview != req.id_live_preview:
image = shared.state.current_image
if image is not None:
buffered = io.BytesIO()
if opts.live_previews_image_format == "png":
# using optimize for large images takes an enormous amount of time
if max(*image.size) <= 256:
save_kwargs = {"optimize": True}
else:
save_kwargs = {"optimize": False, "compress_level": 1}
else:
save_kwargs = {}
image.save(buffered, format=opts.live_previews_image_format, **save_kwargs)
base64_image = base64.b64encode(buffered.getvalue()).decode('ascii')
live_preview = f"data:image/{opts.live_previews_image_format};base64,{base64_image}"
id_live_preview = shared.state.id_live_preview
else:
live_preview = None
else:
live_preview = None
return ProgressResponse(active=active, queued=queued, completed=completed, progress=progress, eta=eta, live_preview=live_preview, id_live_preview=id_live_preview, textinfo=shared.state.textinfo)
def restore_progress(id_task):
while id_task == current_task or id_task in pending_tasks:
time.sleep(0.1)
res = next(iter([x[1] for x in recorded_results if id_task == x[0]]), None)
if res is not None:
return res
return gr.update(), gr.update(), gr.update(), f"Couldn't restore progress for {id_task}: results either have been discarded or never were obtained"