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Merge branch 'main' into fix_typos

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blessedcoolant 2023-02-16 10:01:28 +13:00 committed by GitHub
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190
invokeai/backend/invoke_ai_web_server.py
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@ -28,7 +28,7 @@ from ldm.invoke.args import Args, APP_ID, APP_VERSION, calculate_init_img_hash
from ldm.invoke.conditioning import get_tokens_for_prompt, get_prompt_structure
from ldm.invoke.generator.diffusers_pipeline import PipelineIntermediateState
from ldm.invoke.generator.inpaint import infill_methods
from ldm.invoke.globals import Globals
from ldm.invoke.globals import Globals, global_converted_ckpts_dir
from ldm.invoke.pngwriter import PngWriter, retrieve_metadata
from ldm.invoke.prompt_parser import split_weighted_subprompts, Blend
@ -43,7 +43,8 @@ if not os.path.isabs(args.outdir):
# normalize the config directory relative to root
if not os.path.isabs(opt.conf):
opt.conf = os.path.normpath(os.path.join(Globals.root,opt.conf))
opt.conf = os.path.normpath(os.path.join(Globals.root, opt.conf))
class InvokeAIWebServer:
def __init__(self, generate: Generate, gfpgan, codeformer, esrgan) -> None:
@ -189,7 +190,8 @@ class InvokeAIWebServer:
(width, height) = pil_image.size
thumbnail_path = save_thumbnail(
pil_image, os.path.basename(file_path), self.thumbnail_image_path
pil_image, os.path.basename(
file_path), self.thumbnail_image_path
)
response = {
@ -264,14 +266,16 @@ class InvokeAIWebServer:
# location for "finished" images
self.result_path = args.outdir
# temporary path for intermediates
self.intermediate_path = os.path.join(self.result_path, "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/")
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
@ -290,7 +294,7 @@ class InvokeAIWebServer:
def load_socketio_listeners(self, socketio):
@socketio.on("requestSystemConfig")
def handle_request_capabilities():
print(f">> System config requested")
print(">> System config requested")
config = self.get_system_config()
config["model_list"] = self.generate.model_manager.list_models()
config["infill_methods"] = infill_methods()
@ -301,14 +305,16 @@ class InvokeAIWebServer:
try:
if not search_folder:
socketio.emit(
"foundModels",
{'search_folder': None, 'found_models': None},
)
"foundModels",
{'search_folder': None, 'found_models': None},
)
else:
search_folder, found_models = self.generate.model_manager.search_models(search_folder)
search_folder, found_models = self.generate.model_manager.search_models(
search_folder)
socketio.emit(
"foundModels",
{'search_folder': search_folder, 'found_models': found_models},
{'search_folder': search_folder,
'found_models': found_models},
)
except Exception as e:
self.socketio.emit("error", {"message": (str(e))})
@ -393,6 +399,67 @@ class InvokeAIWebServer:
traceback.print_exc()
print("\n")
@socketio.on('convertToDiffusers')
def convert_to_diffusers(model_to_convert: dict):
try:
if (model_info := self.generate.model_manager.model_info(model_name=model_to_convert['model_name'])):
if 'weights' in model_info:
ckpt_path = Path(model_info['weights'])
original_config_file = Path(model_info['config'])
model_name = model_to_convert['model_name']
model_description = model_info['description']
else:
self.socketio.emit(
"error", {"message": "Model is not a valid checkpoint file"})
else:
self.socketio.emit(
"error", {"message": "Could not retrieve model info."})
if not ckpt_path.is_absolute():
ckpt_path = Path(Globals.root, ckpt_path)
if original_config_file and not original_config_file.is_absolute():
original_config_file = Path(
Globals.root, original_config_file)
diffusers_path = Path(
ckpt_path.parent.absolute(),
f'{model_name}_diffusers'
)
if model_to_convert['save_location'] == 'root':
diffusers_path = Path(global_converted_ckpts_dir(), f'{model_name}_diffusers')
if model_to_convert['save_location'] == 'custom' and model_to_convert['custom_location'] is not None:
diffusers_path = Path(model_to_convert['custom_location'], f'{model_name}_diffusers')
if diffusers_path.exists():
shutil.rmtree(diffusers_path)
self.generate.model_manager.convert_and_import(
ckpt_path,
diffusers_path,
model_name=model_name,
model_description=model_description,
vae=None,
original_config_file=original_config_file,
commit_to_conf=opt.conf,
)
new_model_list = self.generate.model_manager.list_models()
socketio.emit(
"modelConverted",
{"new_model_name": model_name,
"model_list": new_model_list, 'update': True},
)
print(f">> Model Converted: {model_name}")
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:
@ -406,7 +473,8 @@ class InvokeAIWebServer:
)
os.remove(thumbnail_path)
except Exception as e:
socketio.emit("error", {"message": f"Unable to delete {f}: {str(e)}"})
socketio.emit(
"error", {"message": f"Unable to delete {f}: {str(e)}"})
pass
socketio.emit("tempFolderEmptied")
@ -421,7 +489,8 @@ class InvokeAIWebServer:
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))
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":
@ -434,7 +503,8 @@ class InvokeAIWebServer:
(width, height) = pil_image.size
thumbnail_path = save_thumbnail(
pil_image, os.path.basename(new_path), self.thumbnail_image_path
pil_image, os.path.basename(
new_path), self.thumbnail_image_path
)
image_array = [
@ -497,7 +567,8 @@ class InvokeAIWebServer:
(width, height) = pil_image.size
thumbnail_path = save_thumbnail(
pil_image, os.path.basename(path), self.thumbnail_image_path
pil_image, os.path.basename(
path), self.thumbnail_image_path
)
image_array.append(
@ -515,7 +586,8 @@ class InvokeAIWebServer:
}
)
except Exception as e:
socketio.emit("error", {"message": f"Unable to load {path}: {str(e)}"})
socketio.emit(
"error", {"message": f"Unable to load {path}: {str(e)}"})
pass
socketio.emit(
@ -569,7 +641,8 @@ class InvokeAIWebServer:
(width, height) = pil_image.size
thumbnail_path = save_thumbnail(
pil_image, os.path.basename(path), self.thumbnail_image_path
pil_image, os.path.basename(
path), self.thumbnail_image_path
)
image_array.append(
@ -588,7 +661,8 @@ class InvokeAIWebServer:
)
except Exception as e:
print(f">> Unable to load {path}")
socketio.emit("error", {"message": f"Unable to load {path}: {str(e)}"})
socketio.emit(
"error", {"message": f"Unable to load {path}: {str(e)}"})
pass
socketio.emit(
@ -626,7 +700,8 @@ class InvokeAIWebServer:
printable_parameters["init_mask"][:64] + "..."
)
print(f'\n>> Image Generation Parameters:\n\n{printable_parameters}\n')
print(
f'\n>> Image Generation Parameters:\n\n{printable_parameters}\n')
print(f'>> ESRGAN Parameters: {esrgan_parameters}')
print(f'>> Facetool Parameters: {facetool_parameters}')
@ -662,16 +737,18 @@ class InvokeAIWebServer:
try:
seed = original_image["metadata"]["image"]["seed"]
except (KeyError) as e:
except KeyError:
seed = "unknown_seed"
pass
if postprocessing_parameters["type"] == "esrgan":
progress.set_current_status("common:statusUpscalingESRGAN")
elif postprocessing_parameters["type"] == "gfpgan":
progress.set_current_status("common:statusRestoringFacesGFPGAN")
progress.set_current_status(
"common:statusRestoringFacesGFPGAN")
elif postprocessing_parameters["type"] == "codeformer":
progress.set_current_status("common:statusRestoringFacesCodeFormer")
progress.set_current_status(
"common:statusRestoringFacesCodeFormer")
socketio.emit("progressUpdate", progress.to_formatted_dict())
eventlet.sleep(0)
@ -760,7 +837,7 @@ class InvokeAIWebServer:
@socketio.on("cancel")
def handle_cancel():
print(f">> Cancel processing requested")
print(">> Cancel processing requested")
self.canceled.set()
# TODO: I think this needs a safety mechanism.
@ -842,12 +919,10 @@ class InvokeAIWebServer:
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()
original_bounding_box = generation_parameters["bounding_box"].copy(
)
initial_image = dataURL_to_image(
generation_parameters["init_img"]
@ -924,7 +999,8 @@ class InvokeAIWebServer:
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')
generation_parameters["init_img"] = Image.open(
init_img_path).convert('RGB')
def image_progress(sample, step):
if self.canceled.is_set():
@ -983,9 +1059,9 @@ class InvokeAIWebServer:
},
)
if generation_parameters["progress_latents"]:
image = self.generate.sample_to_lowres_estimated_image(sample)
image = self.generate.sample_to_lowres_estimated_image(
sample)
(width, height) = image.size
width *= 8
height *= 8
@ -1004,7 +1080,8 @@ class InvokeAIWebServer:
},
)
self.socketio.emit("progressUpdate", progress.to_formatted_dict())
self.socketio.emit(
"progressUpdate", progress.to_formatted_dict())
eventlet.sleep(0)
def image_done(image, seed, first_seed, attention_maps_image=None):
@ -1016,7 +1093,6 @@ class InvokeAIWebServer:
nonlocal facetool_parameters
nonlocal progress
step_index = 1
nonlocal prior_variations
"""
@ -1032,7 +1108,8 @@ class InvokeAIWebServer:
progress.set_current_status("common:statusGenerationComplete")
self.socketio.emit("progressUpdate", progress.to_formatted_dict())
self.socketio.emit(
"progressUpdate", progress.to_formatted_dict())
eventlet.sleep(0)
all_parameters = generation_parameters
@ -1043,7 +1120,8 @@ class InvokeAIWebServer:
and all_parameters["variation_amount"] > 0
):
first_seed = first_seed or seed
this_variation = [[seed, all_parameters["variation_amount"]]]
this_variation = [
[seed, all_parameters["variation_amount"]]]
all_parameters["with_variations"] = (
prior_variations + this_variation
)
@ -1059,7 +1137,8 @@ class InvokeAIWebServer:
if esrgan_parameters:
progress.set_current_status("common:statusUpscaling")
progress.set_current_status_has_steps(False)
self.socketio.emit("progressUpdate", progress.to_formatted_dict())
self.socketio.emit(
"progressUpdate", progress.to_formatted_dict())
eventlet.sleep(0)
image = self.esrgan.process(
@ -1082,12 +1161,15 @@ class InvokeAIWebServer:
if facetool_parameters:
if facetool_parameters["type"] == "gfpgan":
progress.set_current_status("common:statusRestoringFacesGFPGAN")
progress.set_current_status(
"common:statusRestoringFacesGFPGAN")
elif facetool_parameters["type"] == "codeformer":
progress.set_current_status("common:statusRestoringFacesCodeFormer")
progress.set_current_status(
"common:statusRestoringFacesCodeFormer")
progress.set_current_status_has_steps(False)
self.socketio.emit("progressUpdate", progress.to_formatted_dict())
self.socketio.emit(
"progressUpdate", progress.to_formatted_dict())
eventlet.sleep(0)
if facetool_parameters["type"] == "gfpgan":
@ -1117,7 +1199,8 @@ class InvokeAIWebServer:
all_parameters["facetool_type"] = facetool_parameters["type"]
progress.set_current_status("common:statusSavingImage")
self.socketio.emit("progressUpdate", progress.to_formatted_dict())
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
@ -1128,12 +1211,14 @@ class InvokeAIWebServer:
)
if "init_mask" in all_parameters:
all_parameters["init_mask"] = "" # TODO: store the mask in metadata
# TODO: store the mask in metadata
all_parameters["init_mask"] = ""
if generation_parameters["generation_mode"] == "unifiedCanvas":
all_parameters["bounding_box"] = original_bounding_box
metadata = self.parameters_to_generated_image_metadata(all_parameters)
metadata = self.parameters_to_generated_image_metadata(
all_parameters)
command = parameters_to_command(all_parameters)
@ -1163,15 +1248,18 @@ class InvokeAIWebServer:
if progress.total_iterations > progress.current_iteration:
progress.set_current_step(1)
progress.set_current_status("common:statusIterationComplete")
progress.set_current_status(
"common:statusIterationComplete")
progress.set_current_status_has_steps(False)
else:
progress.mark_complete()
self.socketio.emit("progressUpdate", progress.to_formatted_dict())
self.socketio.emit(
"progressUpdate", progress.to_formatted_dict())
eventlet.sleep(0)
parsed_prompt, _ = get_prompt_structure(generation_parameters["prompt"])
parsed_prompt, _ = get_prompt_structure(
generation_parameters["prompt"])
tokens = None if type(parsed_prompt) is Blend else \
get_tokens_for_prompt(self.generate.model, parsed_prompt)
attention_maps_image_base64_url = None if attention_maps_image is None \
@ -1345,7 +1433,8 @@ class InvokeAIWebServer:
self, parameters, original_image_path
):
try:
current_metadata = retrieve_metadata(original_image_path)["sd-metadata"]
current_metadata = retrieve_metadata(
original_image_path)["sd-metadata"]
postprocessing_metadata = {}
"""
@ -1385,7 +1474,8 @@ class InvokeAIWebServer:
postprocessing_metadata
)
else:
current_metadata["image"]["postprocessing"] = [postprocessing_metadata]
current_metadata["image"]["postprocessing"] = [
postprocessing_metadata]
return current_metadata
@ -1424,7 +1514,7 @@ class InvokeAIWebServer:
if step_index:
filename += f".{step_index}"
if postprocessing:
filename += f".postprocessed"
filename += ".postprocessed"
filename += ".png"
@ -1497,7 +1587,8 @@ class InvokeAIWebServer:
)
elif "thumbnails" in url:
return os.path.abspath(
os.path.join(self.thumbnail_image_path, os.path.basename(url))
os.path.join(self.thumbnail_image_path,
os.path.basename(url))
)
else:
return os.path.abspath(
@ -1666,10 +1757,12 @@ def dataURL_to_image(dataURL: str) -> ImageType:
)
return image
"""
Converts an image into a base64 image dataURL.
"""
def image_to_dataURL(image: ImageType) -> str:
buffered = io.BytesIO()
image.save(buffered, format="PNG")
@ -1679,7 +1772,6 @@ def image_to_dataURL(image: ImageType) -> str:
return image_base64
"""
Converts a base64 image dataURL into bytes.
The dataURL is split on the first commma.

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invokeai/frontend/dist/index.html vendored
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@ -5,7 +5,7 @@
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>InvokeAI - A Stable Diffusion Toolkit</title>
<link rel="shortcut icon" type="icon" href="./assets/favicon-0d253ced.ico" />
<script type="module" crossorigin src="./assets/index-a93d4500.js"></script>
<script type="module" crossorigin src="./assets/index-6b9f1e33.js"></script>
<link rel="stylesheet" href="./assets/index-fecb6dd4.css">
</head>

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invokeai/frontend/dist/locales/common/en.json vendored
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@ -58,5 +58,7 @@
"statusUpscaling": "Upscaling",
"statusUpscalingESRGAN": "Upscaling (ESRGAN)",
"statusLoadingModel": "Loading Model",
"statusModelChanged": "Model Changed"
"statusModelChanged": "Model Changed",
"statusConvertingModel": "Converting Model",
"statusModelConverted": "Model Converted"
}

20
invokeai/frontend/dist/locales/modelmanager/en-US.json vendored
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@ -63,5 +63,23 @@
"formMessageDiffusersModelLocation": "Diffusers Model Location",
"formMessageDiffusersModelLocationDesc": "Please enter at least one.",
"formMessageDiffusersVAELocation": "VAE Location",
"formMessageDiffusersVAELocationDesc": "If not provided, InvokeAI will look for the VAE file inside the model location given above."
"formMessageDiffusersVAELocationDesc": "If not provided, InvokeAI will look for the VAE file inside the model location given above.",
"convert": "Convert",
"convertToDiffusers": "Convert To Diffusers",
"convertToDiffusersHelpText1": "This model will be converted to the 🧨 Diffusers format.",
"convertToDiffusersHelpText2": "This process will replace your Model Manager entry with the Diffusers version of the same model.",
"convertToDiffusersHelpText3": "Your checkpoint file on the disk will NOT be deleted or modified in anyway. You can add your checkpoint to the Model Manager again if you want to.",
"convertToDiffusersHelpText4": "This is a one time process only. It might take around 30s-60s depending on the specifications of your computer.",
"convertToDiffusersHelpText5": "Please make sure you have enough disk space. Models generally vary between 4GB-7GB in size.",
"convertToDiffusersHelpText6": "Do you wish to convert this model?",
"v1": "v1",
"v2": "v2",
"inpainting": "v1 Inpainting",
"customConfig": "Custom Config",
"pathToCustomConfig": "Path To Custom Config",
"statusConverting": "Converting",
"sameFolder": "Same Folder",
"invokeRoot": "Invoke Models",
"custom": "Custom",
"customSaveLocation": "Custom Save Location"
}

22
invokeai/frontend/dist/locales/modelmanager/en.json vendored
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@ -63,5 +63,25 @@
"formMessageDiffusersModelLocation": "Diffusers Model Location",
"formMessageDiffusersModelLocationDesc": "Please enter at least one.",
"formMessageDiffusersVAELocation": "VAE Location",
"formMessageDiffusersVAELocationDesc": "If not provided, InvokeAI will look for the VAE file inside the model location given above."
"formMessageDiffusersVAELocationDesc": "If not provided, InvokeAI will look for the VAE file inside the model location given above.",
"convert": "Convert",
"convertToDiffusers": "Convert To Diffusers",
"convertToDiffusersHelpText1": "This model will be converted to the 🧨 Diffusers format.",
"convertToDiffusersHelpText2": "This process will replace your Model Manager entry with the Diffusers version of the same model.",
"convertToDiffusersHelpText3": "Your checkpoint file on the disk will NOT be deleted or modified in anyway. You can add your checkpoint to the Model Manager again if you want to.",
"convertToDiffusersHelpText4": "This is a one time process only. It might take around 30s-60s depending on the specifications of your computer.",
"convertToDiffusersHelpText5": "Please make sure you have enough disk space. Models generally vary between 4GB-7GB in size.",
"convertToDiffusersHelpText6": "Do you wish to convert this model?",
"convertToDiffusersSaveLocation": "Save Location",
"v1": "v1",
"v2": "v2",
"inpainting": "v1 Inpainting",
"customConfig": "Custom Config",
"pathToCustomConfig": "Path To Custom Config",
"statusConverting": "Converting",
"modelConverted": "Model Converted",
"sameFolder": "Same folder",
"invokeRoot": "InvokeAI folder",
"custom": "Custom",
"customSaveLocation": "Custom Save Location"
}

2
invokeai/frontend/dist/locales/parameters/en-US.json vendored
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@ -57,6 +57,6 @@
"useInitImg": "Use Initial Image",
"info": "Info",
"deleteImage": "Delete Image",
"initialImage": "Inital Image",
"initialImage": "Initial Image",
"showOptionsPanel": "Show Options Panel"
}

2
invokeai/frontend/dist/locales/parameters/en.json vendored
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@ -60,6 +60,6 @@
"useInitImg": "Use Initial Image",
"info": "Info",
"deleteImage": "Delete Image",
"initialImage": "Inital Image",
"initialImage": "Initial Image",
"showOptionsPanel": "Show Options Panel"
}

2
invokeai/frontend/dist/locales/parameters/ja.json vendored
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@ -56,7 +56,7 @@
"useInitImg": "Use Initial Image",
"info": "情報",
"deleteImage": "画像を削除",
"initialImage": "Inital Image",
"initialImage": "Initial Image",
"showOptionsPanel": "オプションパネルを表示"
}

4
invokeai/frontend/public/locales/common/en.json
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@ -58,5 +58,7 @@
"statusUpscaling": "Upscaling",
"statusUpscalingESRGAN": "Upscaling (ESRGAN)",
"statusLoadingModel": "Loading Model",
"statusModelChanged": "Model Changed"
"statusModelChanged": "Model Changed",
"statusConvertingModel": "Converting Model",
"statusModelConverted": "Model Converted"
}

20
invokeai/frontend/public/locales/modelmanager/en-US.json
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@ -63,5 +63,23 @@
"formMessageDiffusersModelLocation": "Diffusers Model Location",
"formMessageDiffusersModelLocationDesc": "Please enter at least one.",
"formMessageDiffusersVAELocation": "VAE Location",
"formMessageDiffusersVAELocationDesc": "If not provided, InvokeAI will look for the VAE file inside the model location given above."
"formMessageDiffusersVAELocationDesc": "If not provided, InvokeAI will look for the VAE file inside the model location given above.",
"convert": "Convert",
"convertToDiffusers": "Convert To Diffusers",
"convertToDiffusersHelpText1": "This model will be converted to the 🧨 Diffusers format.",
"convertToDiffusersHelpText2": "This process will replace your Model Manager entry with the Diffusers version of the same model.",
"convertToDiffusersHelpText3": "Your checkpoint file on the disk will NOT be deleted or modified in anyway. You can add your checkpoint to the Model Manager again if you want to.",
"convertToDiffusersHelpText4": "This is a one time process only. It might take around 30s-60s depending on the specifications of your computer.",
"convertToDiffusersHelpText5": "Please make sure you have enough disk space. Models generally vary between 4GB-7GB in size.",
"convertToDiffusersHelpText6": "Do you wish to convert this model?",
"v1": "v1",
"v2": "v2",
"inpainting": "v1 Inpainting",
"customConfig": "Custom Config",
"pathToCustomConfig": "Path To Custom Config",
"statusConverting": "Converting",
"sameFolder": "Same Folder",
"invokeRoot": "Invoke Models",
"custom": "Custom",
"customSaveLocation": "Custom Save Location"
}

22
invokeai/frontend/public/locales/modelmanager/en.json
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@ -63,5 +63,25 @@
"formMessageDiffusersModelLocation": "Diffusers Model Location",
"formMessageDiffusersModelLocationDesc": "Please enter at least one.",
"formMessageDiffusersVAELocation": "VAE Location",
"formMessageDiffusersVAELocationDesc": "If not provided, InvokeAI will look for the VAE file inside the model location given above."
"formMessageDiffusersVAELocationDesc": "If not provided, InvokeAI will look for the VAE file inside the model location given above.",
"convert": "Convert",
"convertToDiffusers": "Convert To Diffusers",
"convertToDiffusersHelpText1": "This model will be converted to the 🧨 Diffusers format.",
"convertToDiffusersHelpText2": "This process will replace your Model Manager entry with the Diffusers version of the same model.",
"convertToDiffusersHelpText3": "Your checkpoint file on the disk will NOT be deleted or modified in anyway. You can add your checkpoint to the Model Manager again if you want to.",
"convertToDiffusersHelpText4": "This is a one time process only. It might take around 30s-60s depending on the specifications of your computer.",
"convertToDiffusersHelpText5": "Please make sure you have enough disk space. Models generally vary between 4GB-7GB in size.",
"convertToDiffusersHelpText6": "Do you wish to convert this model?",
"convertToDiffusersSaveLocation": "Save Location",
"v1": "v1",
"v2": "v2",
"inpainting": "v1 Inpainting",
"customConfig": "Custom Config",
"pathToCustomConfig": "Path To Custom Config",
"statusConverting": "Converting",
"modelConverted": "Model Converted",
"sameFolder": "Same folder",
"invokeRoot": "InvokeAI folder",
"custom": "Custom",
"customSaveLocation": "Custom Save Location"
}

2
invokeai/frontend/public/locales/parameters/en-US.json
View File

@ -57,6 +57,6 @@
"useInitImg": "Use Initial Image",
"info": "Info",
"deleteImage": "Delete Image",
"initialImage": "Inital Image",
"initialImage": "Initial Image",
"showOptionsPanel": "Show Options Panel"
}

2
invokeai/frontend/public/locales/parameters/en.json
View File

@ -60,6 +60,6 @@
"useInitImg": "Use Initial Image",
"info": "Info",
"deleteImage": "Delete Image",
"initialImage": "Inital Image",
"initialImage": "Initial Image",
"showOptionsPanel": "Show Options Panel"
}

2
invokeai/frontend/public/locales/parameters/ja.json
View File

@ -56,7 +56,7 @@
"useInitImg": "Use Initial Image",
"info": "情報",
"deleteImage": "画像を削除",
"initialImage": "Inital Image",
"initialImage": "Initial Image",
"showOptionsPanel": "オプションパネルを表示"
}

11
invokeai/frontend/src/app/invokeai.d.ts vendored
View File

@ -219,6 +219,12 @@ export declare type InvokeDiffusersModelConfigProps = {
};
};
export declare type InvokeModelConversionProps = {
model_name: string;
save_location: string;
custom_location: string | null;
};
/**
* These types type data received from the server via socketio.
*/
@ -228,6 +234,11 @@ export declare type ModelChangeResponse = {
model_list: ModelList;
};
export declare type ModelConvertedResponse = {
converted_model_name: string;
model_list: ModelList;
};
export declare type ModelAddedResponse = {
new_model_name: string;
model_list: ModelList;

5
invokeai/frontend/src/app/socketio/actions.ts
View File

@ -38,6 +38,11 @@ export const addNewModel = createAction<
export const deleteModel = createAction<string>('socketio/deleteModel');
export const convertToDiffusers =
createAction<InvokeAI.InvokeModelConversionProps>(
'socketio/convertToDiffusers'
);
export const requestModelChange = createAction<string>(
'socketio/requestModelChange'
);

7
invokeai/frontend/src/app/socketio/emitters.ts
View File

@ -15,6 +15,7 @@ import {
addLogEntry,
generationRequested,
modelChangeRequested,
modelConvertRequested,
setIsProcessing,
} from 'features/system/store/systemSlice';
import { InvokeTabName } from 'features/ui/store/tabMap';
@ -178,6 +179,12 @@ const makeSocketIOEmitters = (
emitDeleteModel: (modelName: string) => {
socketio.emit('deleteModel', modelName);
},
emitConvertToDiffusers: (
modelToConvert: InvokeAI.InvokeModelConversionProps
) => {
dispatch(modelConvertRequested());
socketio.emit('convertToDiffusers', modelToConvert);
},
emitRequestModelChange: (modelName: string) => {
dispatch(modelChangeRequested());
socketio.emit('requestModelChange', modelName);

25
invokeai/frontend/src/app/socketio/listeners.ts
View File

@ -365,6 +365,7 @@ const makeSocketIOListeners = (
const { new_model_name, model_list, update } = data;
dispatch(setModelList(model_list));
dispatch(setIsProcessing(false));
dispatch(setCurrentStatus(i18n.t('modelmanager:modelAdded')));
dispatch(
addLogEntry({
timestamp: dateFormat(new Date(), 'isoDateTime'),
@ -407,6 +408,30 @@ const makeSocketIOListeners = (
})
);
},
onModelConverted: (data: InvokeAI.ModelConvertedResponse) => {
const { converted_model_name, model_list } = data;
dispatch(setModelList(model_list));
dispatch(setCurrentStatus(i18n.t('common:statusModelConverted')));
dispatch(setIsProcessing(false));
dispatch(setIsCancelable(true));
dispatch(
addLogEntry({
timestamp: dateFormat(new Date(), 'isoDateTime'),
message: `Model converted: ${converted_model_name}`,
level: 'info',
})
);
dispatch(
addToast({
title: `${i18n.t(
'modelmanager:modelConverted'
)}: ${converted_model_name}`,
status: 'success',
duration: 2500,
isClosable: true,
})
);
},
onModelChanged: (data: InvokeAI.ModelChangeResponse) => {
const { model_name, model_list } = data;
dispatch(setModelList(model_list));

11
invokeai/frontend/src/app/socketio/middleware.ts
View File

@ -48,6 +48,7 @@ export const socketioMiddleware = () => {
onFoundModels,
onNewModelAdded,
onModelDeleted,
onModelConverted,
onModelChangeFailed,
onTempFolderEmptied,
} = makeSocketIOListeners(store);
@ -64,6 +65,7 @@ export const socketioMiddleware = () => {
emitSearchForModels,
emitAddNewModel,
emitDeleteModel,
emitConvertToDiffusers,
emitRequestModelChange,
emitSaveStagingAreaImageToGallery,
emitRequestEmptyTempFolder,
@ -125,6 +127,10 @@ export const socketioMiddleware = () => {
onModelDeleted(data);
});
socketio.on('modelConverted', (data: InvokeAI.ModelConvertedResponse) => {
onModelConverted(data);
});
socketio.on('modelChanged', (data: InvokeAI.ModelChangeResponse) => {
onModelChanged(data);
});
@ -199,6 +205,11 @@ export const socketioMiddleware = () => {
break;
}
case 'socketio/convertToDiffusers': {
emitConvertToDiffusers(action.payload);
break;
}
case 'socketio/requestModelChange': {
emitRequestModelChange(action.payload);
break;

10
invokeai/frontend/src/common/util/parameterTranslation.ts
View File

@ -178,12 +178,16 @@ export const frontendToBackendParameters = (
? randomInt(NUMPY_RAND_MIN, NUMPY_RAND_MAX)
: seed;
// parameters common to txt2img and img2img
if (['txt2img', 'img2img'].includes(generationMode)) {
generationParameters.seamless = seamless;
// txt2img exclusive parameters
if (generationMode === 'txt2img') {
generationParameters.hires_fix = hiresFix;
if (hiresFix) generationParameters.strength = hiresStrength;
}
// parameters common to txt2img and img2img
if (['txt2img', 'img2img'].includes(generationMode)) {
generationParameters.seamless = seamless;
if (shouldRunESRGAN) {
esrganParameters = {

4
invokeai/frontend/src/features/system/components/ModelManager/CheckpointModelEdit.tsx
View File

@ -27,6 +27,7 @@ import type { InvokeModelConfigProps } from 'app/invokeai';
import type { RootState } from 'app/store';
import type { FieldInputProps, FormikProps } from 'formik';
import { isEqual, pickBy } from 'lodash';
import ModelConvert from './ModelConvert';
const selector = createSelector(
[systemSelector],
@ -101,10 +102,11 @@ export default function CheckpointModelEdit() {
return openModel ? (
<Flex flexDirection="column" rowGap="1rem" width="100%">
<Flex alignItems="center">
<Flex alignItems="center" gap={4} justifyContent="space-between">
<Text fontSize="lg" fontWeight="bold">
{openModel}
</Text>
<ModelConvert model={openModel} />
</Flex>
<Flex
flexDirection="column"

148
invokeai/frontend/src/features/system/components/ModelManager/ModelConvert.tsx Normal file
View File

@ -0,0 +1,148 @@
import {
Flex,
ListItem,
Radio,
RadioGroup,
Text,
UnorderedList,
Tooltip,
} from '@chakra-ui/react';
import { convertToDiffusers } from 'app/socketio/actions';
import { RootState } from 'app/store';
import { useAppDispatch, useAppSelector } from 'app/storeHooks';
import IAIAlertDialog from 'common/components/IAIAlertDialog';
import IAIButton from 'common/components/IAIButton';
import IAIInput from 'common/components/IAIInput';
import { useState, useEffect } from 'react';
import { useTranslation } from 'react-i18next';
interface ModelConvertProps {
model: string;
}
export default function ModelConvert(props: ModelConvertProps) {
const { model } = props;
const model_list = useAppSelector(
(state: RootState) => state.system.model_list
);
const retrievedModel = model_list[model];
const dispatch = useAppDispatch();
const { t } = useTranslation();
const isProcessing = useAppSelector(
(state: RootState) => state.system.isProcessing
);
const isConnected = useAppSelector(
(state: RootState) => state.system.isConnected
);
const [saveLocation, setSaveLocation] = useState<string>('same');
const [customSaveLocation, setCustomSaveLocation] = useState<string>('');
useEffect(() => {
setSaveLocation('same');
}, [model]);
const modelConvertCancelHandler = () => {
setSaveLocation('same');
};
const modelConvertHandler = () => {
const modelToConvert = {
model_name: model,
save_location: saveLocation,
custom_location:
saveLocation === 'custom' && customSaveLocation !== ''
? customSaveLocation
: null,
};
dispatch(convertToDiffusers(modelToConvert));
};
return (
<IAIAlertDialog
title={`${t('modelmanager:convert')} ${model}`}
acceptCallback={modelConvertHandler}
cancelCallback={modelConvertCancelHandler}
acceptButtonText={`${t('modelmanager:convert')}`}
triggerComponent={
<IAIButton
size={'sm'}
aria-label={t('modelmanager:convertToDiffusers')}
isDisabled={
retrievedModel.status === 'active' || isProcessing || !isConnected
}
className=" modal-close-btn"
marginRight="2rem"
>
🧨 {t('modelmanager:convertToDiffusers')}
</IAIButton>
}
motionPreset="slideInBottom"
>
<Flex flexDirection="column" rowGap={4}>
<Text>{t('modelmanager:convertToDiffusersHelpText1')}</Text>
<UnorderedList>
<ListItem>{t('modelmanager:convertToDiffusersHelpText2')}</ListItem>
<ListItem>{t('modelmanager:convertToDiffusersHelpText3')}</ListItem>
<ListItem>{t('modelmanager:convertToDiffusersHelpText4')}</ListItem>
<ListItem>{t('modelmanager:convertToDiffusersHelpText5')}</ListItem>
</UnorderedList>
<Text>{t('modelmanager:convertToDiffusersHelpText6')}</Text>
</Flex>
<Flex flexDir="column" gap={4}>
<Flex marginTop="1rem" flexDir="column" gap={2}>
<Text fontWeight="bold">
{t('modelmanager:convertToDiffusersSaveLocation')}
</Text>
<RadioGroup value={saveLocation} onChange={(v) => setSaveLocation(v)}>
<Flex gap={4}>
<Radio value="same">
<Tooltip label="Save converted model in the same folder">
{t('modelmanager:sameFolder')}
</Tooltip>
</Radio>
<Radio value="root">
<Tooltip label="Save converted model in the InvokeAI root folder">
{t('modelmanager:invokeRoot')}
</Tooltip>
</Radio>
<Radio value="custom">
<Tooltip label="Save converted model in a custom folder">
{t('modelmanager:custom')}
</Tooltip>
</Radio>
</Flex>
</RadioGroup>
</Flex>
{saveLocation === 'custom' && (
<Flex flexDirection="column" rowGap={2}>
<Text
fontWeight="bold"
fontSize="sm"
color="var(--text-color-secondary)"
>
{t('modelmanager:customSaveLocation')}
</Text>
<IAIInput
value={customSaveLocation}
onChange={(e) => {
if (e.target.value !== '')
setCustomSaveLocation(e.target.value);
}}
width="25rem"
/>
</Flex>
)}
</Flex>
</IAIAlertDialog>
);
}

1
invokeai/frontend/src/features/system/components/ModelManager/ModelListItem.tsx
View File

@ -83,6 +83,7 @@ export default function ModelListItem(props: ModelListItemProps) {
>
{t('modelmanager:load')}
</Button>
<IAIIconButton
icon={<EditIcon />}
size={'sm'}

72
invokeai/frontend/src/features/system/components/ModelManager/SearchModels.tsx
View File

@ -3,7 +3,16 @@ import IAICheckbox from 'common/components/IAICheckbox';
import IAIIconButton from 'common/components/IAIIconButton';
import React from 'react';
import { Box, Flex, FormControl, HStack, Text, VStack } from '@chakra-ui/react';
import {
Box,
Flex,
FormControl,
HStack,
Radio,
RadioGroup,
Text,
VStack,
} from '@chakra-ui/react';
import { createSelector } from '@reduxjs/toolkit';
import { useAppDispatch, useAppSelector } from 'app/storeHooks';
import { systemSelector } from 'features/system/store/systemSelectors';
@ -135,6 +144,8 @@ export default function SearchModels() {
);
const [modelsToAdd, setModelsToAdd] = React.useState<string[]>([]);
const [modelType, setModelType] = React.useState<string>('v1');
const [pathToConfig, setPathToConfig] = React.useState<string>('');
const resetSearchModelHandler = () => {
dispatch(setSearchFolder(null));
@ -167,11 +178,19 @@ export default function SearchModels() {
const modelsToBeAdded = foundModels?.filter((foundModel) =>
modelsToAdd.includes(foundModel.name)
);
const configFiles = {
v1: 'configs/stable-diffusion/v1-inference.yaml',
v2: 'configs/stable-diffusion/v2-inference-v.yaml',
inpainting: 'configs/stable-diffusion/v1-inpainting-inference.yaml',
custom: pathToConfig,
};
modelsToBeAdded?.forEach((model) => {
const modelFormat = {
name: model.name,
description: '',
config: 'configs/stable-diffusion/v1-inference.yaml',
config: configFiles[modelType as keyof typeof configFiles],
weights: model.location,
vae: '',
width: 512,
@ -346,6 +365,55 @@ export default function SearchModels() {
{t('modelmanager:addSelected')}
</IAIButton>
</Flex>
<Flex
gap={4}
backgroundColor="var(--background-color)"
padding="1rem 1rem"
borderRadius="0.2rem"
flexDirection="column"
>
<Flex gap={4}>
<Text fontWeight="bold" color="var(--text-color-secondary)">
Pick Model Type:
</Text>
<RadioGroup
value={modelType}
onChange={(v) => setModelType(v)}
defaultValue="v1"
name="model_type"
>
<Flex gap={4}>
<Radio value="v1">{t('modelmanager:v1')}</Radio>
<Radio value="v2">{t('modelmanager:v2')}</Radio>
<Radio value="inpainting">
{t('modelmanager:inpainting')}
</Radio>
<Radio value="custom">{t('modelmanager:customConfig')}</Radio>
</Flex>
</RadioGroup>
</Flex>
{modelType === 'custom' && (
<Flex flexDirection="column" rowGap={2}>
<Text
fontWeight="bold"
fontSize="sm"
color="var(--text-color-secondary)"
>
{t('modelmanager:pathToCustomConfig')}
</Text>
<IAIInput
value={pathToConfig}
onChange={(e) => {
if (e.target.value !== '') setPathToConfig(e.target.value);
}}
width="42.5rem"
/>
</Flex>
)}
</Flex>
<Flex
rowGap="1rem"
flexDirection="column"

7
invokeai/frontend/src/features/system/store/systemSlice.ts
View File

@ -214,6 +214,12 @@ export const systemSlice = createSlice({
state.isProcessing = true;
state.currentStatusHasSteps = false;
},
modelConvertRequested: (state) => {
state.currentStatus = i18n.t('common:statusConvertingModel');
state.isCancelable = false;
state.isProcessing = true;
state.currentStatusHasSteps = false;
},
setSaveIntermediatesInterval: (state, action: PayloadAction<number>) => {
state.saveIntermediatesInterval = action.payload;
},
@ -265,6 +271,7 @@ export const {
setModelList,
setIsCancelable,
modelChangeRequested,
modelConvertRequested,
setSaveIntermediatesInterval,
setEnableImageDebugging,
generationRequested,

15
invokeai/frontend/src/features/ui/components/ImageToImage/ImageToImagePanel.tsx
View File

@ -1,6 +1,5 @@
import { Flex } from '@chakra-ui/react';
import { Feature } from 'app/features';
import { useAppDispatch, useAppSelector } from 'app/storeHooks';
import FaceRestoreSettings from 'features/parameters/components/AdvancedParameters/FaceRestore/FaceRestoreSettings';
import FaceRestoreToggle from 'features/parameters/components/AdvancedParameters/FaceRestore/FaceRestoreToggle';
import ImageFit from 'features/parameters/components/AdvancedParameters/ImageToImage/ImageFit';
@ -16,10 +15,7 @@ import ParametersAccordion from 'features/parameters/components/ParametersAccord
import ProcessButtons from 'features/parameters/components/ProcessButtons/ProcessButtons';
import NegativePromptInput from 'features/parameters/components/PromptInput/NegativePromptInput';
import PromptInput from 'features/parameters/components/PromptInput/PromptInput';
import { setHiresFix } from 'features/parameters/store/postprocessingSlice';
import InvokeOptionsPanel from 'features/ui/components/InvokeParametersPanel';
import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
import { useEffect } from 'react';
import { useTranslation } from 'react-i18next';
export default function ImageToImagePanel() {
@ -56,17 +52,6 @@ export default function ImageToImagePanel() {
},
};
const dispatch = useAppDispatch();
const activeTabName = useAppSelector(activeTabNameSelector);
useEffect(() => {
if (activeTabName === 'img2img') {
const handleChangeHiresFix = () => dispatch(setHiresFix(false));
handleChangeHiresFix();
}
}, [activeTabName, dispatch]);
return (
<InvokeOptionsPanel>
<Flex flexDir="column" rowGap="0.5rem">

2
invokeai/frontend/stats.html
View File

File diff suppressed because one or more lines are too long

7
ldm/invoke/generator/base.py
View File

@ -247,11 +247,14 @@ class Generator:
fixdevice = 'cpu' if (self.model.device.type == 'mps') else self.model.device
# limit noise to only the diffusion image channels, not the mask channels
input_channels = min(self.latent_channels, 4)
# round up to the nearest block of 8
temp_width = int((width + 7) / 8) * 8
temp_height = int((height + 7) / 8) * 8
noise = torch.stack([
rand_perlin_2d((height, width),
rand_perlin_2d((temp_height, temp_width),
(8, 8),
device = self.model.device).to(fixdevice) for _ in range(input_channels)], dim=0).to(self.model.device)
return noise
return noise[0:4, 0:height, 0:width]
def new_seed(self):
self.seed = random.randrange(0, np.iinfo(np.uint32).max)

5
ldm/invoke/globals.py
View File

@ -33,7 +33,7 @@ Globals.models_file = 'models.yaml'
Globals.models_dir = 'models'
Globals.config_dir = 'configs'
Globals.autoscan_dir = 'weights'
Globals.converted_ckpts_dir = 'converted-ckpts'
Globals.converted_ckpts_dir = 'converted_ckpts'
# Try loading patchmatch
Globals.try_patchmatch = True
@ -66,6 +66,9 @@ def global_models_dir()->Path:
def global_autoscan_dir()->Path:
return Path(Globals.root, Globals.autoscan_dir)
def global_converted_ckpts_dir()->Path:
return Path(global_models_dir(), Globals.converted_ckpts_dir)
def global_set_root(root_dir:Union[str,Path]):
Globals.root = root_dir

12
ldm/invoke/model_manager.py
View File

@ -759,7 +759,7 @@ class ModelManager(object):
return
model_name = model_name or diffusers_path.name
model_description = model_description or "Optimized version of {model_name}"
model_description = model_description or f"Optimized version of {model_name}"
print(f">> Optimizing {model_name} (30-60s)")
try:
# By passing the specified VAE too the conversion function, the autoencoder
@ -799,15 +799,17 @@ class ModelManager(object):
models_folder_safetensors = Path(search_folder).glob("**/*.safetensors")
ckpt_files = [x for x in models_folder_ckpt if x.is_file()]
safetensor_files = [x for x in models_folder_safetensors if x.is_file]
safetensor_files = [x for x in models_folder_safetensors if x.is_file()]
files = ckpt_files + safetensor_files
found_models = []
for file in files:
found_models.append(
{"name": file.stem, "location": str(file.resolve()).replace("\\", "/")}
)
location = str(file.resolve()).replace("\\", "/")
if 'model.safetensors' not in location and 'diffusion_pytorch_model.safetensors' not in location:
found_models.append(
{"name": file.stem, "location": location}
)
return search_folder, found_models