InvokeAI/backend/invoke_ai_web_server.py
2022-11-30 15:39:40 -08:00

1628 lines
59 KiB
Python

import base64
import glob
import io
import json
import math
import mimetypes
import os
import shutil
import traceback
from threading import Event
from uuid import uuid4
import eventlet
from PIL import Image
from PIL.Image import Image as ImageType
from flask import Flask, redirect, send_from_directory, request, make_response
from flask_socketio import SocketIO
from werkzeug.utils import secure_filename
from backend.modules.get_canvas_generation_mode import (
get_canvas_generation_mode,
)
from backend.modules.parameters import parameters_to_command
from ldm.invoke.args import Args, APP_ID, APP_VERSION, calculate_init_img_hash
from ldm.invoke.generator.diffusers_pipeline import PipelineIntermediateState
from ldm.invoke.generator.inpaint import infill_methods
from ldm.invoke.pngwriter import PngWriter, retrieve_metadata
from ldm.invoke.prompt_parser import split_weighted_subprompts
# Loading Arguments
opt = Args()
args = opt.parse_args()
# Set the root directory for static files and relative paths
args.root_dir = os.path.expanduser(args.root_dir or "..")
if not os.path.isabs(args.outdir):
args.outdir = os.path.join(args.root_dir, args.outdir)
class InvokeAIWebServer:
def __init__(self, generate, gfpgan, codeformer, esrgan) -> None:
self.host = args.host
self.port = args.port
self.generate = generate
self.gfpgan = gfpgan
self.codeformer = codeformer
self.esrgan = esrgan
self.canceled = Event()
self.ALLOWED_EXTENSIONS = {"png", "jpg", "jpeg"}
def allowed_file(self, filename: str) -> bool:
return (
"." in filename
and filename.rsplit(".", 1)[1].lower() in self.ALLOWED_EXTENSIONS
)
def run(self):
self.setup_app()
self.setup_flask()
def setup_flask(self):
# Fix missing mimetypes on Windows
mimetypes.add_type("application/javascript", ".js")
mimetypes.add_type("text/css", ".css")
# Socket IO
logger = True if args.web_verbose else False
engineio_logger = True if args.web_verbose else False
max_http_buffer_size = 10000000
socketio_args = {
"logger": logger,
"engineio_logger": engineio_logger,
"max_http_buffer_size": max_http_buffer_size,
"ping_interval": (50, 50),
"ping_timeout": 60,
}
if opt.cors:
socketio_args["cors_allowed_origins"] = opt.cors
frontend_path = self.find_frontend()
self.app = Flask(
__name__, static_url_path="", static_folder=frontend_path
)
self.socketio = SocketIO(self.app, **socketio_args)
# Keep Server Alive Route
@self.app.route("/flaskwebgui-keep-server-alive")
def keep_alive():
return {"message": "Server Running"}
# Outputs Route
self.app.config["OUTPUTS_FOLDER"] = os.path.abspath(args.outdir)
@self.app.route("/outputs/<path:file_path>")
def outputs(file_path):
return send_from_directory(self.app.config["OUTPUTS_FOLDER"], file_path)
# Base Route
@self.app.route("/")
def serve():
if args.web_develop:
return redirect("http://127.0.0.1:5173")
else:
return send_from_directory(self.app.static_folder, "index.html")
@self.app.route("/upload", methods=["POST"])
def upload():
try:
data = json.loads(request.form["data"])
filename = ""
# check if the post request has the file part
if "file" in request.files:
file = request.files["file"]
# If the user does not select a file, the browser submits an
# empty file without a filename.
if file.filename == "":
return make_response("No file selected", 400)
filename = file.filename
elif "dataURL" in data:
file = dataURL_to_bytes(data["dataURL"])
if "filename" not in data or data["filename"] == "":
return make_response("No filename provided", 400)
filename = data["filename"]
else:
return make_response("No file or dataURL", 400)
kind = data["kind"]
if kind == "init":
path = self.init_image_path
elif kind == "temp":
path = self.temp_image_path
elif kind == "result":
path = self.result_path
elif kind == "mask":
path = self.mask_image_path
else:
return make_response(f"Invalid upload kind: {kind}", 400)
if not self.allowed_file(filename):
return make_response(
f'Invalid file type, must be one of: {", ".join(self.ALLOWED_EXTENSIONS)}',
400,
)
secured_filename = secure_filename(filename)
uuid = uuid4().hex
truncated_uuid = uuid[:8]
split = os.path.splitext(secured_filename)
name = f"{split[0]}.{truncated_uuid}{split[1]}"
file_path = os.path.join(path, name)
if "dataURL" in data:
with open(file_path, "wb") as f:
f.write(file)
else:
file.save(file_path)
mtime = os.path.getmtime(file_path)
pil_image = Image.open(file_path)
if "cropVisible" in data and data["cropVisible"] == True:
visible_image_bbox = pil_image.getbbox()
pil_image = pil_image.crop(visible_image_bbox)
pil_image.save(file_path)
(width, height) = pil_image.size
thumbnail_path = save_thumbnail(
pil_image, os.path.basename(file_path), self.thumbnail_image_path
)
response = {
"url": self.get_url_from_image_path(file_path),
"thumbnail": self.get_url_from_image_path(thumbnail_path),
"mtime": mtime,
"width": width,
"height": height,
}
return make_response(response, 200)
except Exception as e:
self.socketio.emit("error", {"message": (str(e))})
print("\n")
traceback.print_exc()
print("\n")
return make_response("Error uploading file", 500)
self.load_socketio_listeners(self.socketio)
if args.gui:
print(">> Launching Invoke AI GUI")
try:
from flaskwebgui import FlaskUI
FlaskUI(
app=self.app,
socketio=self.socketio,
server="flask_socketio",
width=1600,
height=1000,
port=self.port
).run()
except KeyboardInterrupt:
import sys
sys.exit(0)
else:
useSSL = args.certfile or args.keyfile
print(">> Started Invoke AI Web Server!")
if self.host == "0.0.0.0":
print(
f"Point your browser at http{'s' if useSSL else ''}://localhost:{self.port} or use the host's DNS name or IP address."
)
else:
print(
">> Default host address now 127.0.0.1 (localhost). Use --host 0.0.0.0 to bind any address."
)
print(
f">> Point your browser at http{'s' if useSSL else ''}://{self.host}:{self.port}"
)
if not useSSL:
self.socketio.run(app=self.app, host=self.host, port=self.port)
else:
self.socketio.run(
app=self.app,
host=self.host,
port=self.port,
certfile=args.certfile,
keyfile=args.keyfile,
)
def find_frontend(self):
my_dir = os.path.dirname(__file__)
for candidate in (os.path.join(my_dir,'..','frontend','dist'), # pip install -e .
os.path.join(my_dir,'../../../../frontend','dist') # pip install .
):
if os.path.exists(candidate):
return candidate
assert "Frontend files cannot be found. Cannot continue"
def setup_app(self):
self.result_url = "outputs/"
self.init_image_url = "outputs/init-images/"
self.mask_image_url = "outputs/mask-images/"
self.intermediate_url = "outputs/intermediates/"
self.temp_image_url = "outputs/temp-images/"
self.thumbnail_image_url = "outputs/thumbnails/"
# location for "finished" images
self.result_path = args.outdir
# temporary path for intermediates
self.intermediate_path = os.path.join(self.result_path, "intermediates/")
# path for user-uploaded init images and masks
self.init_image_path = os.path.join(self.result_path, "init-images/")
self.mask_image_path = os.path.join(self.result_path, "mask-images/")
# path for temp images e.g. gallery generations which are not committed
self.temp_image_path = os.path.join(self.result_path, "temp-images/")
# path for thumbnail images
self.thumbnail_image_path = os.path.join(self.result_path, "thumbnails/")
# txt log
self.log_path = os.path.join(self.result_path, "invoke_log.txt")
# make all output paths
[
os.makedirs(path, exist_ok=True)
for path in [
self.result_path,
self.intermediate_path,
self.init_image_path,
self.mask_image_path,
self.temp_image_path,
self.thumbnail_image_path,
]
]
def load_socketio_listeners(self, socketio):
@socketio.on("requestSystemConfig")
def handle_request_capabilities():
print(f">> System config requested")
config = self.get_system_config()
config["model_list"] = self.generate.model_cache.list_models()
config["infill_methods"] = infill_methods
socketio.emit("systemConfig", config)
@socketio.on("requestModelChange")
def handle_set_model(model_name: str):
try:
print(f">> Model change requested: {model_name}")
model = self.generate.set_model(model_name)
model_list = self.generate.model_cache.list_models()
if model is None:
socketio.emit(
"modelChangeFailed",
{"model_name": model_name, "model_list": model_list},
)
else:
socketio.emit(
"modelChanged",
{"model_name": model_name, "model_list": model_list},
)
except Exception as e:
self.socketio.emit("error", {"message": (str(e))})
print("\n")
traceback.print_exc()
print("\n")
@socketio.on("requestEmptyTempFolder")
def empty_temp_folder():
try:
temp_files = glob.glob(os.path.join(self.temp_image_path, "*"))
for f in temp_files:
try:
os.remove(f)
thumbnail_path = os.path.join(
self.thumbnail_image_path,
os.path.splitext(os.path.basename(f))[0] + ".webp",
)
os.remove(thumbnail_path)
except Exception as e:
socketio.emit("error", {"message": f"Unable to delete {f}: {str(e)}"})
pass
socketio.emit("tempFolderEmptied")
except Exception as e:
self.socketio.emit("error", {"message": (str(e))})
print("\n")
traceback.print_exc()
print("\n")
@socketio.on("requestSaveStagingAreaImageToGallery")
def save_temp_image_to_gallery(url):
try:
image_path = self.get_image_path_from_url(url)
new_path = os.path.join(self.result_path, os.path.basename(image_path))
shutil.copy2(image_path, new_path)
if os.path.splitext(new_path)[1] == ".png":
metadata = retrieve_metadata(new_path)
else:
metadata = {}
pil_image = Image.open(new_path)
(width, height) = pil_image.size
thumbnail_path = save_thumbnail(
pil_image, os.path.basename(new_path), self.thumbnail_image_path
)
image_array = [
{
"url": self.get_url_from_image_path(new_path),
"thumbnail": self.get_url_from_image_path(thumbnail_path),
"mtime": os.path.getmtime(new_path),
"metadata": metadata,
"width": width,
"height": height,
"category": "result",
}
]
socketio.emit(
"galleryImages",
{"images": image_array, "category": "result"},
)
except Exception as e:
self.socketio.emit("error", {"message": (str(e))})
print("\n")
traceback.print_exc()
print("\n")
@socketio.on("requestLatestImages")
def handle_request_latest_images(category, latest_mtime):
try:
base_path = (
self.result_path if category == "result" else self.init_image_path
)
paths = []
for ext in ("*.png", "*.jpg", "*.jpeg"):
paths.extend(glob.glob(os.path.join(base_path, ext)))
image_paths = sorted(
paths, key=lambda x: os.path.getmtime(x), reverse=True
)
image_paths = list(
filter(
lambda x: os.path.getmtime(x) > latest_mtime,
image_paths,
)
)
image_array = []
for path in image_paths:
try:
if os.path.splitext(path)[1] == ".png":
metadata = retrieve_metadata(path)
else:
metadata = {}
pil_image = Image.open(path)
(width, height) = pil_image.size
thumbnail_path = save_thumbnail(
pil_image, os.path.basename(path), self.thumbnail_image_path
)
image_array.append(
{
"url": self.get_url_from_image_path(path),
"thumbnail": self.get_url_from_image_path(
thumbnail_path
),
"mtime": os.path.getmtime(path),
"metadata": metadata.get("sd-metadata"),
"dreamPrompt": metadata.get("Dream"),
"width": width,
"height": height,
"category": category,
}
)
except Exception as e:
socketio.emit("error", {"message": f"Unable to load {path}: {str(e)}"})
pass
socketio.emit(
"galleryImages",
{"images": image_array, "category": category},
)
except Exception as e:
self.socketio.emit("error", {"message": (str(e))})
print("\n")
traceback.print_exc()
print("\n")
@socketio.on("requestImages")
def handle_request_images(category, earliest_mtime=None):
try:
page_size = 50
base_path = (
self.result_path if category == "result" else self.init_image_path
)
paths = []
for ext in ("*.png", "*.jpg", "*.jpeg"):
paths.extend(glob.glob(os.path.join(base_path, ext)))
image_paths = sorted(
paths, key=lambda x: os.path.getmtime(x), reverse=True
)
if earliest_mtime:
image_paths = list(
filter(
lambda x: os.path.getmtime(x) < earliest_mtime,
image_paths,
)
)
areMoreImagesAvailable = len(image_paths) >= page_size
image_paths = image_paths[slice(0, page_size)]
image_array = []
for path in image_paths:
try:
if os.path.splitext(path)[1] == ".png":
metadata = retrieve_metadata(path)
else:
metadata = {}
pil_image = Image.open(path)
(width, height) = pil_image.size
thumbnail_path = save_thumbnail(
pil_image, os.path.basename(path), self.thumbnail_image_path
)
image_array.append(
{
"url": self.get_url_from_image_path(path),
"thumbnail": self.get_url_from_image_path(
thumbnail_path
),
"mtime": os.path.getmtime(path),
"metadata": metadata.get("sd-metadata"),
"dreamPrompt": metadata.get("Dream"),
"width": width,
"height": height,
"category": category,
}
)
except Exception as e:
print(f">> Unable to load {path}")
socketio.emit("error", {"message": f"Unable to load {path}: {str(e)}"})
pass
socketio.emit(
"galleryImages",
{
"images": image_array,
"areMoreImagesAvailable": areMoreImagesAvailable,
"category": category,
},
)
except Exception as e:
self.socketio.emit("error", {"message": (str(e))})
print("\n")
traceback.print_exc()
print("\n")
@socketio.on("generateImage")
def handle_generate_image_event(
generation_parameters, esrgan_parameters, facetool_parameters
):
try:
# truncate long init_mask/init_img base64 if needed
printable_parameters = {
**generation_parameters,
}
if "init_img" in generation_parameters:
printable_parameters["init_img"] = (
printable_parameters["init_img"][:64] + "..."
)
if "init_mask" in generation_parameters:
printable_parameters["init_mask"] = (
printable_parameters["init_mask"][:64] + "..."
)
print(
f">> Image generation requested: {printable_parameters}\nESRGAN parameters: {esrgan_parameters}\nFacetool parameters: {facetool_parameters}"
)
self.generate_images(
generation_parameters,
esrgan_parameters,
facetool_parameters,
)
except Exception as e:
self.socketio.emit("error", {"message": (str(e))})
print("\n")
traceback.print_exc()
print("\n")
@socketio.on("runPostprocessing")
def handle_run_postprocessing(original_image, postprocessing_parameters):
try:
print(
f'>> Postprocessing requested for "{original_image["url"]}": {postprocessing_parameters}'
)
progress = Progress()
socketio.emit("progressUpdate", progress.to_formatted_dict())
eventlet.sleep(0)
original_image_path = self.get_image_path_from_url(
original_image["url"]
)
image = Image.open(original_image_path)
try:
seed = original_image["metadata"]["image"]["seed"]
except (KeyError) as e:
seed = "unknown_seed"
pass
if postprocessing_parameters["type"] == "esrgan":
progress.set_current_status("Upscaling (ESRGAN)")
elif postprocessing_parameters["type"] == "gfpgan":
progress.set_current_status("Restoring Faces (GFPGAN)")
elif postprocessing_parameters["type"] == "codeformer":
progress.set_current_status("Restoring Faces (Codeformer)")
socketio.emit("progressUpdate", progress.to_formatted_dict())
eventlet.sleep(0)
if postprocessing_parameters["type"] == "esrgan":
image = self.esrgan.process(
image=image,
upsampler_scale=postprocessing_parameters["upscale"][0],
strength=postprocessing_parameters["upscale"][1],
seed=seed,
)
elif postprocessing_parameters["type"] == "gfpgan":
image = self.gfpgan.process(
image=image,
strength=postprocessing_parameters["facetool_strength"],
seed=seed,
)
elif postprocessing_parameters["type"] == "codeformer":
image = self.codeformer.process(
image=image,
strength=postprocessing_parameters["facetool_strength"],
fidelity=postprocessing_parameters["codeformer_fidelity"],
seed=seed,
device="cpu"
if str(self.generate.device) == "mps"
else self.generate.device,
)
else:
raise TypeError(
f'{postprocessing_parameters["type"]} is not a valid postprocessing type'
)
progress.set_current_status("Saving Image")
socketio.emit("progressUpdate", progress.to_formatted_dict())
eventlet.sleep(0)
postprocessing_parameters["seed"] = seed
metadata = self.parameters_to_post_processed_image_metadata(
parameters=postprocessing_parameters,
original_image_path=original_image_path,
)
command = parameters_to_command(postprocessing_parameters)
(width, height) = image.size
path = self.save_result_image(
image,
command,
metadata,
self.result_path,
postprocessing=postprocessing_parameters["type"],
)
thumbnail_path = save_thumbnail(
image, os.path.basename(path), self.thumbnail_image_path
)
self.write_log_message(
f'[Postprocessed] "{original_image_path}" > "{path}": {postprocessing_parameters}'
)
progress.mark_complete()
socketio.emit("progressUpdate", progress.to_formatted_dict())
eventlet.sleep(0)
socketio.emit(
"postprocessingResult",
{
"url": self.get_url_from_image_path(path),
"thumbnail": self.get_url_from_image_path(thumbnail_path),
"mtime": os.path.getmtime(path),
"metadata": metadata,
"dreamPrompt": command,
"width": width,
"height": height,
},
)
except Exception as e:
self.socketio.emit("error", {"message": (str(e))})
print("\n")
traceback.print_exc()
print("\n")
@socketio.on("cancel")
def handle_cancel():
print(f">> Cancel processing requested")
self.canceled.set()
# TODO: I think this needs a safety mechanism.
@socketio.on("deleteImage")
def handle_delete_image(url, thumbnail, uuid, category):
try:
print(f'>> Delete requested "{url}"')
from send2trash import send2trash
path = self.get_image_path_from_url(url)
thumbnail_path = self.get_image_path_from_url(thumbnail)
send2trash(path)
send2trash(thumbnail_path)
socketio.emit(
"imageDeleted",
{"url": url, "uuid": uuid, "category": category},
)
except Exception as e:
self.socketio.emit("error", {"message": (str(e))})
print("\n")
traceback.print_exc()
print("\n")
# App Functions
def get_system_config(self):
model_list: dict = self.generate.model_cache.list_models()
active_model_name = None
for model_name, model_dict in model_list.items():
if model_dict["status"] == "active":
active_model_name = model_name
return {
"model": "stable diffusion",
"model_weights": active_model_name,
"model_hash": self.generate.model_hash,
"app_id": APP_ID,
"app_version": APP_VERSION,
}
def generate_images(
self, generation_parameters, esrgan_parameters, facetool_parameters
):
try:
self.canceled.clear()
step_index = 1
prior_variations = (
generation_parameters["with_variations"]
if "with_variations" in generation_parameters
else []
)
actual_generation_mode = generation_parameters["generation_mode"]
original_bounding_box = None
progress = Progress(generation_parameters=generation_parameters)
self.socketio.emit("progressUpdate", progress.to_formatted_dict())
eventlet.sleep(0)
"""
TODO:
If a result image is used as an init image, and then deleted, we will want to be
able to use it as an init image in the future. Need to handle this case.
"""
"""
Prepare for generation based on generation_mode
"""
if generation_parameters["generation_mode"] == "unifiedCanvas":
"""
generation_parameters["init_img"] is a base64 image
generation_parameters["init_mask"] is a base64 image
So we need to convert each into a PIL Image.
"""
truncated_outpaint_image_b64 = generation_parameters["init_img"][:64]
truncated_outpaint_mask_b64 = generation_parameters["init_mask"][:64]
init_img_url = generation_parameters["init_img"]
original_bounding_box = generation_parameters["bounding_box"].copy()
initial_image = dataURL_to_image(
generation_parameters["init_img"]
).convert("RGBA")
"""
The outpaint image and mask are pre-cropped by the UI, so the bounding box we pass
to the generator should be:
{
"x": 0,
"y": 0,
"width": original_bounding_box["width"],
"height": original_bounding_box["height"]
}
"""
generation_parameters["bounding_box"]["x"] = 0
generation_parameters["bounding_box"]["y"] = 0
# Convert mask dataURL to an image and convert to greyscale
mask_image = dataURL_to_image(
generation_parameters["init_mask"]
).convert("L")
actual_generation_mode = get_canvas_generation_mode(
initial_image, mask_image
)
"""
Apply the mask to the init image, creating a "mask" image with
transparency where inpainting should occur. This is the kind of
mask that prompt2image() needs.
"""
alpha_mask = initial_image.copy()
alpha_mask.putalpha(mask_image)
generation_parameters["init_img"] = initial_image
generation_parameters["init_mask"] = alpha_mask
# Remove the unneeded parameters for whichever mode we are doing
if actual_generation_mode == "inpainting":
generation_parameters.pop("seam_size", None)
generation_parameters.pop("seam_blur", None)
generation_parameters.pop("seam_strength", None)
generation_parameters.pop("seam_steps", None)
generation_parameters.pop("tile_size", None)
generation_parameters.pop("force_outpaint", None)
elif actual_generation_mode == "img2img":
generation_parameters["height"] = original_bounding_box["height"]
generation_parameters["width"] = original_bounding_box["width"]
generation_parameters.pop("init_mask", None)
generation_parameters.pop("seam_size", None)
generation_parameters.pop("seam_blur", None)
generation_parameters.pop("seam_strength", None)
generation_parameters.pop("seam_steps", None)
generation_parameters.pop("tile_size", None)
generation_parameters.pop("force_outpaint", None)
generation_parameters.pop("infill_method", None)
elif actual_generation_mode == "txt2img":
generation_parameters["height"] = original_bounding_box["height"]
generation_parameters["width"] = original_bounding_box["width"]
generation_parameters.pop("strength", None)
generation_parameters.pop("fit", None)
generation_parameters.pop("init_img", None)
generation_parameters.pop("init_mask", None)
generation_parameters.pop("seam_size", None)
generation_parameters.pop("seam_blur", None)
generation_parameters.pop("seam_strength", None)
generation_parameters.pop("seam_steps", None)
generation_parameters.pop("tile_size", None)
generation_parameters.pop("force_outpaint", None)
generation_parameters.pop("infill_method", None)
elif generation_parameters["generation_mode"] == "img2img":
init_img_url = generation_parameters["init_img"]
init_img_path = self.get_image_path_from_url(init_img_url)
generation_parameters["init_img"] = Image.open(init_img_path).convert('RGB')
def image_progress(progress_state: PipelineIntermediateState):
step = progress_state.step
sample = progress_state.latents
if self.canceled.is_set():
raise CanceledException
nonlocal step_index
nonlocal generation_parameters
nonlocal progress
generation_messages = {
"txt2img": "Text to Image",
"img2img": "Image to Image",
"inpainting": "Inpainting",
"outpainting": "Outpainting",
}
progress.set_current_step(step + 1)
progress.set_current_status(
f"Generating ({generation_messages[actual_generation_mode]})"
)
progress.set_current_status_has_steps(True)
if (
generation_parameters["progress_images"]
and step % generation_parameters["save_intermediates"] == 0
and step < generation_parameters["steps"] - 1
):
image = self.generate.sample_to_image(sample)
metadata = self.parameters_to_generated_image_metadata(
generation_parameters
)
command = parameters_to_command(generation_parameters)
(width, height) = image.size
path = self.save_result_image(
image,
command,
metadata,
self.intermediate_path,
step_index=step_index,
postprocessing=False,
)
step_index += 1
self.socketio.emit(
"intermediateResult",
{
"url": self.get_url_from_image_path(path),
"mtime": os.path.getmtime(path),
"metadata": metadata,
"width": width,
"height": height,
"generationMode": generation_parameters["generation_mode"],
"boundingBox": original_bounding_box,
},
)
if generation_parameters["progress_latents"]:
image = self.generate.sample_to_lowres_estimated_image(sample)
(width, height) = image.size
width *= 8
height *= 8
buffered = io.BytesIO()
image.save(buffered, format="PNG")
img_base64 = "data:image/png;base64," + base64.b64encode(
buffered.getvalue()
).decode("UTF-8")
self.socketio.emit(
"intermediateResult",
{
"url": img_base64,
"isBase64": True,
"mtime": 0,
"metadata": {},
"width": width,
"height": height,
"generationMode": generation_parameters["generation_mode"],
"boundingBox": original_bounding_box,
},
)
self.socketio.emit("progressUpdate", progress.to_formatted_dict())
eventlet.sleep(0)
def image_done(image, seed, first_seed):
if self.canceled.is_set():
raise CanceledException
nonlocal generation_parameters
nonlocal esrgan_parameters
nonlocal facetool_parameters
nonlocal progress
step_index = 1
nonlocal prior_variations
"""
Tidy up after generation based on generation_mode
"""
# paste the inpainting image back onto the original
if generation_parameters["generation_mode"] == "inpainting":
image = paste_image_into_bounding_box(
Image.open(init_img_path),
image,
**generation_parameters["bounding_box"],
)
progress.set_current_status("Generation Complete")
self.socketio.emit("progressUpdate", progress.to_formatted_dict())
eventlet.sleep(0)
all_parameters = generation_parameters
postprocessing = False
if (
"variation_amount" in all_parameters
and all_parameters["variation_amount"] > 0
):
first_seed = first_seed or seed
this_variation = [[seed, all_parameters["variation_amount"]]]
all_parameters["with_variations"] = (
prior_variations + this_variation
)
all_parameters["seed"] = first_seed
elif "with_variations" in all_parameters:
all_parameters["seed"] = first_seed
else:
all_parameters["seed"] = seed
if self.canceled.is_set():
raise CanceledException
if esrgan_parameters:
progress.set_current_status("Upscaling")
progress.set_current_status_has_steps(False)
self.socketio.emit("progressUpdate", progress.to_formatted_dict())
eventlet.sleep(0)
image = self.esrgan.process(
image=image,
upsampler_scale=esrgan_parameters["level"],
strength=esrgan_parameters["strength"],
seed=seed,
)
postprocessing = True
all_parameters["upscale"] = [
esrgan_parameters["level"],
esrgan_parameters["strength"],
]
if self.canceled.is_set():
raise CanceledException
if facetool_parameters:
if facetool_parameters["type"] == "gfpgan":
progress.set_current_status("Restoring Faces (GFPGAN)")
elif facetool_parameters["type"] == "codeformer":
progress.set_current_status("Restoring Faces (Codeformer)")
progress.set_current_status_has_steps(False)
self.socketio.emit("progressUpdate", progress.to_formatted_dict())
eventlet.sleep(0)
if facetool_parameters["type"] == "gfpgan":
image = self.gfpgan.process(
image=image,
strength=facetool_parameters["strength"],
seed=seed,
)
elif facetool_parameters["type"] == "codeformer":
image = self.codeformer.process(
image=image,
strength=facetool_parameters["strength"],
fidelity=facetool_parameters["codeformer_fidelity"],
seed=seed,
device="cpu"
if str(self.generate.device) == "mps"
else self.generate.device,
)
all_parameters["codeformer_fidelity"] = facetool_parameters[
"codeformer_fidelity"
]
postprocessing = True
all_parameters["facetool_strength"] = facetool_parameters[
"strength"
]
all_parameters["facetool_type"] = facetool_parameters["type"]
progress.set_current_status("Saving Image")
self.socketio.emit("progressUpdate", progress.to_formatted_dict())
eventlet.sleep(0)
# restore the stashed URLS and discard the paths, we are about to send the result to client
all_parameters["init_img"] = (
init_img_url
if generation_parameters["generation_mode"] == "img2img"
else ""
)
if "init_mask" in all_parameters:
all_parameters["init_mask"] = "" # TODO: store the mask in metadata
if generation_parameters["generation_mode"] == "unifiedCanvas":
all_parameters["bounding_box"] = original_bounding_box
metadata = self.parameters_to_generated_image_metadata(all_parameters)
command = parameters_to_command(all_parameters)
(width, height) = image.size
generated_image_outdir = (
self.result_path
if generation_parameters["generation_mode"]
in ["txt2img", "img2img"]
else self.temp_image_path
)
path = self.save_result_image(
image,
command,
metadata,
generated_image_outdir,
postprocessing=postprocessing,
)
thumbnail_path = save_thumbnail(
image, os.path.basename(path), self.thumbnail_image_path
)
print(f'>> Image generated: "{path}"')
self.write_log_message(f'[Generated] "{path}": {command}')
if progress.total_iterations > progress.current_iteration:
progress.set_current_step(1)
progress.set_current_status("Iteration complete")
progress.set_current_status_has_steps(False)
else:
progress.mark_complete()
self.socketio.emit("progressUpdate", progress.to_formatted_dict())
eventlet.sleep(0)
self.socketio.emit(
"generationResult",
{
"url": self.get_url_from_image_path(path),
"thumbnail": self.get_url_from_image_path(thumbnail_path),
"mtime": os.path.getmtime(path),
"metadata": metadata,
"dreamPrompt": command,
"width": width,
"height": height,
"boundingBox": original_bounding_box,
"generationMode": generation_parameters["generation_mode"],
},
)
eventlet.sleep(0)
progress.set_current_iteration(progress.current_iteration + 1)
print(generation_parameters)
self.generate.prompt2image(
**generation_parameters,
step_callback=image_progress,
image_callback=image_done,
)
except KeyboardInterrupt:
self.socketio.emit("processingCanceled")
raise
except CanceledException:
self.socketio.emit("processingCanceled")
pass
except Exception as e:
print(e)
self.socketio.emit("error", {"message": (str(e))})
print("\n")
traceback.print_exc()
print("\n")
def parameters_to_generated_image_metadata(self, parameters):
try:
# top-level metadata minus `image` or `images`
metadata = self.get_system_config()
# remove any image keys not mentioned in RFC #266
rfc266_img_fields = [
"type",
"postprocessing",
"sampler",
"prompt",
"seed",
"variations",
"steps",
"cfg_scale",
"threshold",
"perlin",
"step_number",
"width",
"height",
"extra",
"seamless",
"hires_fix",
]
rfc_dict = {}
for item in parameters.items():
key, value = item
if key in rfc266_img_fields:
rfc_dict[key] = value
postprocessing = []
rfc_dict["type"] = parameters["generation_mode"]
# 'postprocessing' is either null or an
if "facetool_strength" in parameters:
facetool_parameters = {
"type": str(parameters["facetool_type"]),
"strength": float(parameters["facetool_strength"]),
}
if parameters["facetool_type"] == "codeformer":
facetool_parameters["fidelity"] = float(
parameters["codeformer_fidelity"]
)
postprocessing.append(facetool_parameters)
if "upscale" in parameters:
postprocessing.append(
{
"type": "esrgan",
"scale": int(parameters["upscale"][0]),
"strength": float(parameters["upscale"][1]),
}
)
rfc_dict["postprocessing"] = (
postprocessing if len(postprocessing) > 0 else None
)
# semantic drift
rfc_dict["sampler"] = parameters["sampler_name"]
# display weighted subprompts (liable to change)
subprompts = split_weighted_subprompts(
parameters["prompt"], skip_normalize=True
)
subprompts = [{"prompt": x[0], "weight": x[1]} for x in subprompts]
rfc_dict["prompt"] = subprompts
# 'variations' should always exist and be an array, empty or consisting of {'seed': seed, 'weight': weight} pairs
variations = []
if "with_variations" in parameters:
variations = [
{"seed": x[0], "weight": x[1]}
for x in parameters["with_variations"]
]
rfc_dict["variations"] = variations
print(parameters)
if rfc_dict["type"] == "img2img":
rfc_dict["strength"] = parameters["strength"]
rfc_dict["fit"] = parameters["fit"] # TODO: Noncompliant
rfc_dict["orig_hash"] = calculate_init_img_hash(
self.get_image_path_from_url(parameters["init_img"])
)
rfc_dict["init_image_path"] = parameters[
"init_img"
] # TODO: Noncompliant
metadata["image"] = rfc_dict
return metadata
except Exception as e:
self.socketio.emit("error", {"message": (str(e))})
print("\n")
traceback.print_exc()
print("\n")
def parameters_to_post_processed_image_metadata(
self, parameters, original_image_path
):
try:
current_metadata = retrieve_metadata(original_image_path)["sd-metadata"]
postprocessing_metadata = {}
"""
if we don't have an original image metadata to reconstruct,
need to record the original image and its hash
"""
if "image" not in current_metadata:
current_metadata["image"] = {}
orig_hash = calculate_init_img_hash(
self.get_image_path_from_url(original_image_path)
)
postprocessing_metadata["orig_path"] = (original_image_path,)
postprocessing_metadata["orig_hash"] = orig_hash
if parameters["type"] == "esrgan":
postprocessing_metadata["type"] = "esrgan"
postprocessing_metadata["scale"] = parameters["upscale"][0]
postprocessing_metadata["strength"] = parameters["upscale"][1]
elif parameters["type"] == "gfpgan":
postprocessing_metadata["type"] = "gfpgan"
postprocessing_metadata["strength"] = parameters["facetool_strength"]
elif parameters["type"] == "codeformer":
postprocessing_metadata["type"] = "codeformer"
postprocessing_metadata["strength"] = parameters["facetool_strength"]
postprocessing_metadata["fidelity"] = parameters["codeformer_fidelity"]
else:
raise TypeError(f"Invalid type: {parameters['type']}")
if "postprocessing" in current_metadata["image"] and isinstance(
current_metadata["image"]["postprocessing"], list
):
current_metadata["image"]["postprocessing"].append(
postprocessing_metadata
)
else:
current_metadata["image"]["postprocessing"] = [postprocessing_metadata]
return current_metadata
except Exception as e:
self.socketio.emit("error", {"message": (str(e))})
print("\n")
traceback.print_exc()
print("\n")
def save_result_image(
self,
image,
command,
metadata,
output_dir,
step_index=None,
postprocessing=False,
):
try:
pngwriter = PngWriter(output_dir)
number_prefix = pngwriter.unique_prefix()
uuid = uuid4().hex
truncated_uuid = uuid[:8]
seed = "unknown_seed"
if "image" in metadata:
if "seed" in metadata["image"]:
seed = metadata["image"]["seed"]
filename = f"{number_prefix}.{truncated_uuid}.{seed}"
if step_index:
filename += f".{step_index}"
if postprocessing:
filename += f".postprocessed"
filename += ".png"
path = pngwriter.save_image_and_prompt_to_png(
image=image,
dream_prompt=command,
metadata=metadata,
name=filename,
)
return os.path.abspath(path)
except Exception as e:
self.socketio.emit("error", {"message": (str(e))})
print("\n")
traceback.print_exc()
print("\n")
def make_unique_init_image_filename(self, name):
try:
uuid = uuid4().hex
split = os.path.splitext(name)
name = f"{split[0]}.{uuid}{split[1]}"
return name
except Exception as e:
self.socketio.emit("error", {"message": (str(e))})
print("\n")
traceback.print_exc()
print("\n")
def calculate_real_steps(self, steps, strength, has_init_image):
import math
return math.floor(strength * steps) if has_init_image else steps
def write_log_message(self, message):
"""Logs the filename and parameters used to generate or process that image to log file"""
try:
message = f"{message}\n"
with open(self.log_path, "a", encoding="utf-8") as file:
file.writelines(message)
except Exception as e:
self.socketio.emit("error", {"message": (str(e))})
print("\n")
traceback.print_exc()
print("\n")
def get_image_path_from_url(self, url):
"""Given a url to an image used by the client, returns the absolute file path to that image"""
try:
if "init-images" in url:
return os.path.abspath(
os.path.join(self.init_image_path, os.path.basename(url))
)
elif "mask-images" in url:
return os.path.abspath(
os.path.join(self.mask_image_path, os.path.basename(url))
)
elif "intermediates" in url:
return os.path.abspath(
os.path.join(self.intermediate_path, os.path.basename(url))
)
elif "temp-images" in url:
return os.path.abspath(
os.path.join(self.temp_image_path, os.path.basename(url))
)
elif "thumbnails" in url:
return os.path.abspath(
os.path.join(self.thumbnail_image_path, os.path.basename(url))
)
else:
return os.path.abspath(
os.path.join(self.result_path, os.path.basename(url))
)
except Exception as e:
self.socketio.emit("error", {"message": (str(e))})
print("\n")
traceback.print_exc()
print("\n")
def get_url_from_image_path(self, path):
"""Given an absolute file path to an image, returns the URL that the client can use to load the image"""
try:
if "init-images" in path:
return os.path.join(self.init_image_url, os.path.basename(path))
elif "mask-images" in path:
return os.path.join(self.mask_image_url, os.path.basename(path))
elif "intermediates" in path:
return os.path.join(self.intermediate_url, os.path.basename(path))
elif "temp-images" in path:
return os.path.join(self.temp_image_url, os.path.basename(path))
elif "thumbnails" in path:
return os.path.join(self.thumbnail_image_url, os.path.basename(path))
else:
return os.path.join(self.result_url, os.path.basename(path))
except Exception as e:
self.socketio.emit("error", {"message": (str(e))})
print("\n")
traceback.print_exc()
print("\n")
def save_file_unique_uuid_name(self, bytes, name, path):
try:
uuid = uuid4().hex
truncated_uuid = uuid[:8]
split = os.path.splitext(name)
name = f"{split[0]}.{truncated_uuid}{split[1]}"
file_path = os.path.join(path, name)
os.makedirs(os.path.dirname(file_path), exist_ok=True)
newFile = open(file_path, "wb")
newFile.write(bytes)
return file_path
except Exception as e:
self.socketio.emit("error", {"message": (str(e))})
print("\n")
traceback.print_exc()
print("\n")
class Progress:
def __init__(self, generation_parameters=None):
self.current_step = 1
self.total_steps = (
self._calculate_real_steps(
steps=generation_parameters["steps"],
strength=generation_parameters["strength"]
if "strength" in generation_parameters
else None,
has_init_image="init_img" in generation_parameters,
)
if generation_parameters
else 1
)
self.current_iteration = 1
self.total_iterations = (
generation_parameters["iterations"] if generation_parameters else 1
)
self.current_status = "Preparing"
self.is_processing = True
self.current_status_has_steps = False
self.has_error = False
def set_current_step(self, current_step):
self.current_step = current_step
def set_total_steps(self, total_steps):
self.total_steps = total_steps
def set_current_iteration(self, current_iteration):
self.current_iteration = current_iteration
def set_total_iterations(self, total_iterations):
self.total_iterations = total_iterations
def set_current_status(self, current_status):
self.current_status = current_status
def set_is_processing(self, is_processing):
self.is_processing = is_processing
def set_current_status_has_steps(self, current_status_has_steps):
self.current_status_has_steps = current_status_has_steps
def set_has_error(self, has_error):
self.has_error = has_error
def mark_complete(self):
self.current_status = "Processing Complete"
self.current_step = 0
self.total_steps = 0
self.current_iteration = 0
self.total_iterations = 0
self.is_processing = False
def to_formatted_dict(
self,
):
return {
"currentStep": self.current_step,
"totalSteps": self.total_steps,
"currentIteration": self.current_iteration,
"totalIterations": self.total_iterations,
"currentStatus": self.current_status,
"isProcessing": self.is_processing,
"currentStatusHasSteps": self.current_status_has_steps,
"hasError": self.has_error,
}
def _calculate_real_steps(self, steps, strength, has_init_image):
return math.floor(strength * steps) if has_init_image else steps
class CanceledException(Exception):
pass
"""
Returns a copy an image, cropped to a bounding box.
"""
def copy_image_from_bounding_box(
image: ImageType, x: int, y: int, width: int, height: int
) -> ImageType:
with image as im:
bounds = (x, y, x + width, y + height)
im_cropped = im.crop(bounds)
return im_cropped
"""
Converts a base64 image dataURL into an image.
The dataURL is split on the first commma.
"""
def dataURL_to_image(dataURL: str) -> ImageType:
image = Image.open(
io.BytesIO(
base64.decodebytes(
bytes(
dataURL.split(",", 1)[1],
"utf-8",
)
)
)
)
return image
"""
Converts a base64 image dataURL into bytes.
The dataURL is split on the first commma.
"""
def dataURL_to_bytes(dataURL: str) -> bytes:
return base64.decodebytes(
bytes(
dataURL.split(",", 1)[1],
"utf-8",
)
)
"""
Pastes an image onto another with a bounding box.
"""
def paste_image_into_bounding_box(
recipient_image: ImageType,
donor_image: ImageType,
x: int,
y: int,
width: int,
height: int,
) -> ImageType:
with recipient_image as im:
bounds = (x, y, x + width, y + height)
im.paste(donor_image, bounds)
return recipient_image
"""
Saves a thumbnail of an image, returning its path.
"""
def save_thumbnail(
image: ImageType,
filename: str,
path: str,
size: int = 256,
) -> str:
base_filename = os.path.splitext(filename)[0]
thumbnail_path = os.path.join(path, base_filename + ".webp")
if os.path.exists(thumbnail_path):
return thumbnail_path
thumbnail_width = size
thumbnail_height = round(size * (image.height / image.width))
image_copy = image.copy()
image_copy.thumbnail(size=(thumbnail_width, thumbnail_height))
image_copy.save(thumbnail_path, "WEBP")
return thumbnail_path