Merge branch 'main' into fix_typos

invokeai/backend/invoke_ai_web_server.py

@@ -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",
+                        "foundModels",
-                    {'search_folder': None, 'found_models': None},
+                        {'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.

invokeai/frontend/dist/index.html

@@ -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>
 

invokeai/frontend/dist/locales/common/en.json

@@ -58,5 +58,7 @@
   "statusUpscaling": "Upscaling",
   "statusUpscalingESRGAN": "Upscaling (ESRGAN)",
   "statusLoadingModel": "Loading Model",
-  "statusModelChanged": "Model Changed"
+  "statusModelChanged": "Model Changed",
+  "statusConvertingModel": "Converting Model",
+  "statusModelConverted": "Model Converted"
 }

invokeai/frontend/dist/locales/modelmanager/en-US.json

@@ -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"
 }

invokeai/frontend/dist/locales/modelmanager/en.json

@@ -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"
 }

invokeai/frontend/dist/locales/parameters/en-US.json

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

invokeai/frontend/dist/locales/parameters/en.json

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

invokeai/frontend/dist/locales/parameters/ja.json

@@ -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"
   }
   

invokeai/frontend/public/locales/common/en.json

@@ -58,5 +58,7 @@
   "statusUpscaling": "Upscaling",
   "statusUpscalingESRGAN": "Upscaling (ESRGAN)",
   "statusLoadingModel": "Loading Model",
-  "statusModelChanged": "Model Changed"
+  "statusModelChanged": "Model Changed",
+  "statusConvertingModel": "Converting Model",
+  "statusModelConverted": "Model Converted"
 }

invokeai/frontend/public/locales/modelmanager/en-US.json

@@ -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"
 }

invokeai/frontend/public/locales/modelmanager/en.json

@@ -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"
 }

invokeai/frontend/public/locales/parameters/en-US.json

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

invokeai/frontend/public/locales/parameters/en.json

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

invokeai/frontend/public/locales/parameters/ja.json

@@ -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"
   }
   

invokeai/frontend/src/app/invokeai.d.ts

@@ -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;

invokeai/frontend/src/app/socketio/actions.ts

@@ -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'
 );

invokeai/frontend/src/app/socketio/emitters.ts

@@ -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);

invokeai/frontend/src/app/socketio/listeners.ts

@@ -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));

invokeai/frontend/src/app/socketio/middleware.ts

@@ -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;

invokeai/frontend/src/common/util/parameterTranslation.ts

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

invokeai/frontend/src/features/system/components/ModelManager/CheckpointModelEdit.tsx

@@ -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"

invokeai/frontend/src/features/system/components/ModelManager/ModelConvert.tsx

@@ -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>
+  );
+}

invokeai/frontend/src/features/system/components/ModelManager/ModelListItem.tsx

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

invokeai/frontend/src/features/system/components/ModelManager/SearchModels.tsx

@@ -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"

invokeai/frontend/src/features/system/store/systemSlice.ts

@@ -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,

invokeai/frontend/src/features/ui/components/ImageToImage/ImageToImagePanel.tsx

@@ -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">

ldm/invoke/generator/base.py

@@ -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)

ldm/invoke/globals.py

@@ -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
 

ldm/invoke/model_manager.py

@@ -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(
+            location = str(file.resolve()).replace("\\", "/")
-                {"name": file.stem, "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