rename to iopaint

.gitignore

@@ -4,7 +4,7 @@ examples/
 .idea/
 .vscode/
 build
-!lama_cleaner/app/build
+!iopaint/app/build
 dist/
 lama_cleaner.egg-info/
 venv/

README.md

@@ -1,75 +1 @@
-<p align="center">
-   <img alt="logo" height=256 src="./assets/logo.png" />
-</p>
-<h1 align="center">Lama Cleaner</h1>
-<p align="center">A free and open-source inpainting tool powered by SOTA AI model.</p>
-
-<p align="center">
-  <a href="https://github.com/Sanster/lama-cleaner">
-    <img alt="total download" src="https://pepy.tech/badge/lama-cleaner" />
-  </a>
-  <a href="https://pypi.org/project/lama-cleaner/">
-    <img alt="version" src="https://img.shields.io/pypi/v/lama-cleaner" />
-  </a>
-  <a href="https://colab.research.google.com/drive/1e3ZkAJxvkK3uzaTGu91N9TvI_Mahs0Wb?usp=sharing">
-    <img alt="Open in Colab" src="https://colab.research.google.com/assets/colab-badge.svg" />
-  </a>
-
-  <a href="https://huggingface.co/spaces/Sanster/Lama-Cleaner-lama">
-    <img alt="Hugging Face Spaces" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue" />
-  </a>
-
-  <a href="">
-    <img alt="python version" src="https://img.shields.io/pypi/pyversions/lama-cleaner" />
-  </a>
-  <a href="https://hub.docker.com/r/cwq1913/lama-cleaner">
-    <img alt="version" src="https://img.shields.io/docker/pulls/cwq1913/lama-cleaner" />
-  </a>
-</p>
-
-https://user-images.githubusercontent.com/3998421/196976498-ba1ad3ab-fa18-4c55-965f-5c6683141375.mp4
-
-## Features
-
-- Completely free and open-source, fully self-hosted, support CPU & GPU & M1/2
-- [Windows 1-Click Installer](https://lama-cleaner-docs.vercel.app/install/windows_1click_installer)
-- [Native macOS app](https://opticlean.io/)
-- Multiple SOTA AI [models](https://lama-cleaner-docs.vercel.app/models)
-  - Erase model: LaMa/LDM/ZITS/MAT/FcF/Manga
-  - Erase and Replace model: Stable Diffusion/Paint by Example
-- [Plugins](https://lama-cleaner-docs.vercel.app/plugins) for post-processing:
-  - [RemoveBG](https://github.com/danielgatis/rembg): Remove images background 
-  - [RealESRGAN](https://github.com/xinntao/Real-ESRGAN): Super Resolution
-  - [GFPGAN](https://github.com/TencentARC/GFPGAN): Face Restoration
-  - [RestoreFormer](https://github.com/wzhouxiff/RestoreFormer): Face Restoration
-  - [Segment Anything](https://lama-cleaner-docs.vercel.app/plugins#interactive-segmentation): Accurate and fast interactive object segmentation
-- [FileManager](https://lama-cleaner-docs.vercel.app/features/file_manager): Browse your pictures conveniently and save them directly to the output directory.
-- More features at [lama-cleaner-docs](https://lama-cleaner-docs.vercel.app/)
-
-## Quick Start
-
-Lama Cleaner make it easy to use SOTA AI model in just two commands:
-
-```bash
-# In order to use the GPU, install cuda version of pytorch first.
-# pip install torch==1.13.1+cu117 torchvision==0.14.1 --extra-index-url https://download.pytorch.org/whl/cu117
-pip install lama-cleaner
-lama-cleaner --model=lama --device=cpu --port=8080
-```
-
-That's it, Lama Cleaner is now running at http://localhost:8080
-
-See all command line arguments at [lama-cleaner-docs](https://lama-cleaner-docs.vercel.app/install/pip)
-
-## Development
-
-Only needed if you plan to modify the frontend and recompile yourself.
-
-### Frontend
-
-Frontend code are modified from [cleanup.pictures](https://github.com/initml/cleanup.pictures), You can experience their
-great online services [here](https://cleanup.pictures/).
-
-- Install dependencies:`cd lama_cleaner/app/ && pnpm install`
-- Start development server: `pnpm start`
-- Build: `pnpm build`
+# IOPaint

iopaint/__init__.py

@@ -10,6 +10,6 @@ warnings.simplefilter("ignore", UserWarning)
 def entry_point():
     # To make os.environ["XDG_CACHE_HOME"] = args.model_cache_dir works for diffusers
     # https://github.com/huggingface/diffusers/blob/be99201a567c1ccd841dc16fb24e88f7f239c187/src/diffusers/utils/constants.py#L18
-    from lama_cleaner.cli import typer_app
+    from iopaint.cli import typer_app
 
     typer_app()

iopaint/api.py

@@ -21,8 +21,8 @@ from fastapi.staticfiles import StaticFiles
 from loguru import logger
 from socketio import AsyncServer
 
-from lama_cleaner.file_manager import FileManager
-from lama_cleaner.helper import (
+from iopaint.file_manager import FileManager
+from iopaint.helper import (
     load_img,
     decode_base64_to_image,
     pil_to_bytes,
@@ -31,12 +31,12 @@ from lama_cleaner.helper import (
     gen_frontend_mask,
     adjust_mask,
 )
-from lama_cleaner.model.utils import torch_gc
-from lama_cleaner.model_info import ModelInfo
-from lama_cleaner.model_manager import ModelManager
-from lama_cleaner.plugins import build_plugins
-from lama_cleaner.plugins.base_plugin import BasePlugin
-from lama_cleaner.schema import (
+from iopaint.model.utils import torch_gc
+from iopaint.model_info import ModelInfo
+from iopaint.model_manager import ModelManager
+from iopaint.plugins import build_plugins
+from iopaint.plugins.base_plugin import BasePlugin
+from iopaint.schema import (
     GenInfoResponse,
     ApiConfig,
     ServerConfigResponse,
@@ -356,7 +356,7 @@ class Api:
 
 
 if __name__ == "__main__":
-    from lama_cleaner.schema import InteractiveSegModel, RealESRGANModel
+    from iopaint.schema import InteractiveSegModel, RealESRGANModel
 
     app = FastAPI()
     api = Api(

iopaint/batch_processing.py

@@ -17,9 +17,9 @@ from rich.progress import (
     TimeRemainingColumn,
 )
 
-from lama_cleaner.helper import pil_to_bytes
-from lama_cleaner.model_manager import ModelManager
-from lama_cleaner.schema import InpaintRequest
+from iopaint.helper import pil_to_bytes
+from iopaint.model_manager import ModelManager
+from iopaint.schema import InpaintRequest
 
 
 def glob_images(path: Path) -> Dict[str, Path]:

iopaint/benchmark.py

@@ -9,8 +9,8 @@ import nvidia_smi
 import psutil
 import torch
 
-from lama_cleaner.model_manager import ModelManager
-from lama_cleaner.schema import InpaintRequest, HDStrategy, SDSampler
+from iopaint.model_manager import ModelManager
+from iopaint.schema import InpaintRequest, HDStrategy, SDSampler
 
 try:
     torch._C._jit_override_can_fuse_on_cpu(False)

iopaint/cli.py

@@ -6,16 +6,16 @@ from fastapi import FastAPI
 from loguru import logger
 from typer import Option
 
-from lama_cleaner.const import *
-from lama_cleaner.download import cli_download_model, scan_models
-from lama_cleaner.runtime import setup_model_dir, dump_environment_info, check_device
+from iopaint.const import *
+from iopaint.download import cli_download_model, scan_models
+from iopaint.runtime import setup_model_dir, dump_environment_info, check_device
 
 typer_app = typer.Typer(pretty_exceptions_show_locals=False, add_completion=False)
 
 
 @typer_app.command(help="Install all plugins dependencies")
 def install_plugins_packages():
-    from lama_cleaner.installer import install_plugins_package
+    from iopaint.installer import install_plugins_package
 
     install_plugins_package()
 
@@ -67,12 +67,12 @@ def run(
         logger.info(f"{model} not found in {model_dir}, try to downloading")
         cli_download_model(model, model_dir)
 
-    from lama_cleaner.batch_processing import batch_inpaint
+    from iopaint.batch_processing import batch_inpaint
 
     batch_inpaint(model, device, image, mask, output, config, concat)
 
 
-@typer_app.command(help="Start lama cleaner server")
+@typer_app.command(help="Start IOPaint server")
 def start(
     host: str = Option("127.0.0.1"),
     port: int = Option(8080),
@@ -136,8 +136,8 @@ def start(
         logger.info(f"{model} not found in {model_dir}, try to downloading")
         cli_download_model(model, model_dir)
 
-    from lama_cleaner.api import Api
-    from lama_cleaner.schema import ApiConfig
+    from iopaint.api import Api
+    from iopaint.schema import ApiConfig
 
     app = FastAPI()
     api = Api(

iopaint/download.py

@@ -6,21 +6,21 @@ from huggingface_hub.constants import HF_HUB_CACHE
 from loguru import logger
 from pathlib import Path
 
-from lama_cleaner.const import (
+from iopaint.const import (
     DEFAULT_MODEL_DIR,
     DIFFUSERS_SD_CLASS_NAME,
     DIFFUSERS_SD_INPAINT_CLASS_NAME,
     DIFFUSERS_SDXL_CLASS_NAME,
     DIFFUSERS_SDXL_INPAINT_CLASS_NAME,
 )
-from lama_cleaner.model.utils import handle_from_pretrained_exceptions
-from lama_cleaner.model_info import ModelInfo, ModelType
-from lama_cleaner.runtime import setup_model_dir
+from iopaint.model.utils import handle_from_pretrained_exceptions
+from iopaint.model_info import ModelInfo, ModelType
+from iopaint.runtime import setup_model_dir
 
 
 def cli_download_model(model: str, model_dir: Path):
     setup_model_dir(model_dir)
-    from lama_cleaner.model import models
+    from iopaint.model import models
 
     if model in models and models[model].is_erase_model:
         logger.info(f"Downloading {model}...")
@@ -85,7 +85,7 @@ def scan_single_file_diffusion_models(cache_dir) -> List[ModelInfo]:
 
 def scan_inpaint_models(model_dir: Path) -> List[ModelInfo]:
     res = []
-    from lama_cleaner.model import models
+    from iopaint.model import models
 
     # logger.info(f"Scanning inpaint models in {model_dir}")
 

iopaint/helper.py

@@ -10,7 +10,7 @@ import cv2
 from PIL import Image, ImageOps, PngImagePlugin
 import numpy as np
 import torch
-from lama_cleaner.const import MPS_UNSUPPORT_MODELS
+from iopaint.const import MPS_UNSUPPORT_MODELS
 from loguru import logger
 from torch.hub import download_url_to_file, get_dir
 import hashlib
@@ -56,12 +56,12 @@ def download_model(url, model_md5: str = None):
                 try:
                     os.remove(cached_file)
                     logger.error(
-                        f"Model md5: {_md5}, expected md5: {model_md5}, wrong model deleted. Please restart lama-cleaner."
+                        f"Model md5: {_md5}, expected md5: {model_md5}, wrong model deleted. Please restart iopaint."
                         f"If you still have errors, please try download model manually first https://lama-cleaner-docs.vercel.app/install/download_model_manually.\n"
                     )
                 except:
                     logger.error(
-                        f"Model md5: {_md5}, expected md5: {model_md5}, please delete {cached_file} and restart lama-cleaner."
+                        f"Model md5: {_md5}, expected md5: {model_md5}, please delete {cached_file} and restart iopaint."
                     )
                 exit(-1)
 
@@ -80,12 +80,12 @@ def handle_error(model_path, model_md5, e):
         try:
             os.remove(model_path)
             logger.error(
-                f"Model md5: {_md5}, expected md5: {model_md5}, wrong model deleted. Please restart lama-cleaner."
+                f"Model md5: {_md5}, expected md5: {model_md5}, wrong model deleted. Please restart iopaint."
                 f"If you still have errors, please try download model manually first https://lama-cleaner-docs.vercel.app/install/download_model_manually.\n"
             )
         except:
             logger.error(
-                f"Model md5: {_md5}, expected md5: {model_md5}, please delete {model_path} and restart lama-cleaner."
+                f"Model md5: {_md5}, expected md5: {model_md5}, please delete {model_path} and restart iopaint."
             )
     else:
         logger.error(

iopaint/model/base.py

@@ -6,15 +6,15 @@ import torch
 import numpy as np
 from loguru import logger
 
-from lama_cleaner.helper import (
+from iopaint.helper import (
     boxes_from_mask,
     resize_max_size,
     pad_img_to_modulo,
     switch_mps_device,
 )
-from lama_cleaner.model.helper.g_diffuser_bot import expand_image
-from lama_cleaner.model.utils import get_scheduler
-from lama_cleaner.schema import InpaintRequest, HDStrategy, SDSampler
+from iopaint.model.helper.g_diffuser_bot import expand_image
+from iopaint.model.utils import get_scheduler
+from iopaint.schema import InpaintRequest, HDStrategy, SDSampler
 
 
 class InpaintModel:

iopaint/model/controlnet.py

@@ -5,16 +5,16 @@ import torch
 from diffusers import ControlNetModel, DiffusionPipeline
 from loguru import logger
 
-from lama_cleaner.model.base import DiffusionInpaintModel
-from lama_cleaner.model.helper.controlnet_preprocess import (
+from iopaint.model.base import DiffusionInpaintModel
+from iopaint.model.helper.controlnet_preprocess import (
     make_canny_control_image,
     make_openpose_control_image,
     make_depth_control_image,
     make_inpaint_control_image,
 )
-from lama_cleaner.model.helper.cpu_text_encoder import CPUTextEncoderWrapper
-from lama_cleaner.model.utils import get_scheduler, handle_from_pretrained_exceptions
-from lama_cleaner.schema import InpaintRequest, ModelType
+from iopaint.model.helper.cpu_text_encoder import CPUTextEncoderWrapper
+from iopaint.model.utils import get_scheduler, handle_from_pretrained_exceptions
+from iopaint.schema import InpaintRequest, ModelType
 
 
 class ControlNet(DiffusionInpaintModel):

iopaint/model/ddim_sampler.py

@@ -2,7 +2,7 @@ import torch
 import numpy as np
 from tqdm import tqdm
 
-from lama_cleaner.model.utils import make_ddim_timesteps, make_ddim_sampling_parameters, noise_like
+from iopaint.model.utils import make_ddim_timesteps, make_ddim_sampling_parameters, noise_like
 
 from loguru import logger
 

iopaint/model/fcf.py

@@ -6,9 +6,9 @@ import torch
 import numpy as np
 import torch.fft as fft
 
-from lama_cleaner.schema import InpaintRequest
+from iopaint.schema import InpaintRequest
 
-from lama_cleaner.helper import (
+from iopaint.helper import (
     load_model,
     get_cache_path_by_url,
     norm_img,
@@ -16,11 +16,11 @@ from lama_cleaner.helper import (
     resize_max_size,
     download_model,
 )
-from lama_cleaner.model.base import InpaintModel
+from iopaint.model.base import InpaintModel
 from torch import conv2d, nn
 import torch.nn.functional as F
 
-from lama_cleaner.model.utils import (
+from iopaint.model.utils import (
     setup_filter,
     _parse_scaling,
     _parse_padding,

iopaint/model/helper/cpu_text_encoder.py

@@ -1,5 +1,5 @@
 import torch
-from lama_cleaner.model.utils import torch_gc
+from iopaint.model.utils import torch_gc
 
 
 class CPUTextEncoderWrapper(torch.nn.Module):

iopaint/model/instruct_pix2pix.py

@@ -3,8 +3,8 @@ import cv2
 import torch
 from loguru import logger
 
-from lama_cleaner.model.base import DiffusionInpaintModel
-from lama_cleaner.schema import InpaintRequest
+from iopaint.model.base import DiffusionInpaintModel
+from iopaint.schema import InpaintRequest
 
 
 class InstructPix2Pix(DiffusionInpaintModel):

iopaint/model/kandinsky.py

@@ -3,9 +3,9 @@ import cv2
 import numpy as np
 import torch
 
-from lama_cleaner.model.base import DiffusionInpaintModel
-from lama_cleaner.model.utils import get_scheduler
-from lama_cleaner.schema import InpaintRequest
+from iopaint.model.base import DiffusionInpaintModel
+from iopaint.model.utils import get_scheduler
+from iopaint.schema import InpaintRequest
 
 
 class Kandinsky(DiffusionInpaintModel):

iopaint/model/lama.py

@@ -4,14 +4,14 @@ import cv2
 import numpy as np
 import torch
 
-from lama_cleaner.helper import (
+from iopaint.helper import (
     norm_img,
     get_cache_path_by_url,
     load_jit_model,
     download_model,
 )
-from lama_cleaner.model.base import InpaintModel
-from lama_cleaner.schema import InpaintRequest
+from iopaint.model.base import InpaintModel
+from iopaint.schema import InpaintRequest
 
 LAMA_MODEL_URL = os.environ.get(
     "LAMA_MODEL_URL",

iopaint/model/ldm.py

@@ -4,20 +4,20 @@ import numpy as np
 import torch
 from loguru import logger
 
-from lama_cleaner.model.base import InpaintModel
-from lama_cleaner.model.ddim_sampler import DDIMSampler
-from lama_cleaner.model.plms_sampler import PLMSSampler
-from lama_cleaner.schema import InpaintRequest, LDMSampler
+from iopaint.model.base import InpaintModel
+from iopaint.model.ddim_sampler import DDIMSampler
+from iopaint.model.plms_sampler import PLMSSampler
+from iopaint.schema import InpaintRequest, LDMSampler
 
 torch.manual_seed(42)
 import torch.nn as nn
-from lama_cleaner.helper import (
+from iopaint.helper import (
     download_model,
     norm_img,
     get_cache_path_by_url,
     load_jit_model,
 )
-from lama_cleaner.model.utils import (
+from iopaint.model.utils import (
     make_beta_schedule,
     timestep_embedding,
 )

iopaint/model/manga.py

@@ -7,9 +7,9 @@ import torch
 import time
 from loguru import logger
 
-from lama_cleaner.helper import get_cache_path_by_url, load_jit_model, download_model
-from lama_cleaner.model.base import InpaintModel
-from lama_cleaner.schema import InpaintRequest
+from iopaint.helper import get_cache_path_by_url, load_jit_model, download_model
+from iopaint.model.base import InpaintModel
+from iopaint.schema import InpaintRequest
 
 
 MANGA_INPAINTOR_MODEL_URL = os.environ.get(

iopaint/model/mat.py

@@ -8,14 +8,14 @@ import torch.nn as nn
 import torch.nn.functional as F
 import torch.utils.checkpoint as checkpoint
 
-from lama_cleaner.helper import (
+from iopaint.helper import (
     load_model,
     get_cache_path_by_url,
     norm_img,
     download_model,
 )
-from lama_cleaner.model.base import InpaintModel
-from lama_cleaner.model.utils import (
+from iopaint.model.base import InpaintModel
+from iopaint.model.utils import (
     setup_filter,
     Conv2dLayer,
     FullyConnectedLayer,
@@ -28,7 +28,7 @@ from lama_cleaner.model.utils import (
     normalize_2nd_moment,
     set_seed,
 )
-from lama_cleaner.schema import InpaintRequest
+from iopaint.schema import InpaintRequest
 
 
 class ModulatedConv2d(nn.Module):

iopaint/model/mi_gan.py

@@ -3,7 +3,7 @@ import os
 import cv2
 import torch
 
-from lama_cleaner.helper import (
+from iopaint.helper import (
     load_jit_model,
     download_model,
     get_cache_path_by_url,
@@ -11,8 +11,8 @@ from lama_cleaner.helper import (
     resize_max_size,
     norm_img,
 )
-from lama_cleaner.model.base import InpaintModel
-from lama_cleaner.schema import InpaintRequest
+from iopaint.model.base import InpaintModel
+from iopaint.schema import InpaintRequest
 
 MIGAN_MODEL_URL = os.environ.get(
     "MIGAN_MODEL_URL",

iopaint/model/opencv2.py

@@ -1,6 +1,6 @@
 import cv2
-from lama_cleaner.model.base import InpaintModel
-from lama_cleaner.schema import InpaintRequest
+from iopaint.model.base import InpaintModel
+from iopaint.schema import InpaintRequest
 
 flag_map = {"INPAINT_NS": cv2.INPAINT_NS, "INPAINT_TELEA": cv2.INPAINT_TELEA}
 

iopaint/model/paint_by_example.py

@@ -4,9 +4,9 @@ import cv2
 import torch
 from loguru import logger
 
-from lama_cleaner.helper import decode_base64_to_image
-from lama_cleaner.model.base import DiffusionInpaintModel
-from lama_cleaner.schema import InpaintRequest
+from iopaint.helper import decode_base64_to_image
+from iopaint.model.base import DiffusionInpaintModel
+from iopaint.schema import InpaintRequest
 
 
 class PaintByExample(DiffusionInpaintModel):

iopaint/model/plms_sampler.py

@@ -1,7 +1,7 @@
 # From: https://github.com/CompVis/latent-diffusion/blob/main/ldm/models/diffusion/plms.py
 import torch
 import numpy as np
-from lama_cleaner.model.utils import make_ddim_timesteps, make_ddim_sampling_parameters, noise_like
+from iopaint.model.utils import make_ddim_timesteps, make_ddim_sampling_parameters, noise_like
 from tqdm import tqdm
 
 

iopaint/model/power_paint/power_paint.py

@@ -4,10 +4,10 @@ import cv2
 import torch
 from loguru import logger
 
-from lama_cleaner.model.base import DiffusionInpaintModel
-from lama_cleaner.model.helper.cpu_text_encoder import CPUTextEncoderWrapper
-from lama_cleaner.model.utils import handle_from_pretrained_exceptions
-from lama_cleaner.schema import InpaintRequest
+from iopaint.model.base import DiffusionInpaintModel
+from iopaint.model.helper.cpu_text_encoder import CPUTextEncoderWrapper
+from iopaint.model.utils import handle_from_pretrained_exceptions
+from iopaint.schema import InpaintRequest
 from .powerpaint_tokenizer import add_task_to_prompt
 
 

iopaint/model/power_paint/powerpaint_tokenizer.py

@@ -5,7 +5,7 @@ import random
 from typing import Any, List, Optional, Union
 from transformers import CLIPTokenizer
 
-from lama_cleaner.schema import PowerPaintTask
+from iopaint.schema import PowerPaintTask
 
 
 def add_task_to_prompt(prompt, negative_prompt, task: PowerPaintTask):

iopaint/model/sd.py

@@ -3,10 +3,10 @@ import cv2
 import torch
 from loguru import logger
 
-from lama_cleaner.model.base import DiffusionInpaintModel
-from lama_cleaner.model.helper.cpu_text_encoder import CPUTextEncoderWrapper
-from lama_cleaner.model.utils import handle_from_pretrained_exceptions
-from lama_cleaner.schema import InpaintRequest, ModelType
+from iopaint.model.base import DiffusionInpaintModel
+from iopaint.model.helper.cpu_text_encoder import CPUTextEncoderWrapper
+from iopaint.model.utils import handle_from_pretrained_exceptions
+from iopaint.schema import InpaintRequest, ModelType
 
 
 class SD(DiffusionInpaintModel):

iopaint/model/sdxl.py

@@ -6,9 +6,9 @@ import torch
 from diffusers import AutoencoderKL
 from loguru import logger
 
-from lama_cleaner.model.base import DiffusionInpaintModel
-from lama_cleaner.model.utils import handle_from_pretrained_exceptions
-from lama_cleaner.schema import InpaintRequest, ModelType
+from iopaint.model.base import DiffusionInpaintModel
+from iopaint.model.utils import handle_from_pretrained_exceptions
+from iopaint.schema import InpaintRequest, ModelType
 
 
 class SDXL(DiffusionInpaintModel):

iopaint/model/utils.py

@@ -27,7 +27,7 @@ from diffusers import (
 from diffusers.configuration_utils import FrozenDict
 from loguru import logger
 
-from lama_cleaner.schema import SDSampler
+from iopaint.schema import SDSampler
 from torch import conv2d, conv_transpose2d
 
 

iopaint/model/zits.py

@@ -5,11 +5,11 @@ import cv2
 import torch
 import torch.nn.functional as F
 
-from lama_cleaner.helper import get_cache_path_by_url, load_jit_model, download_model
-from lama_cleaner.schema import InpaintRequest
+from iopaint.helper import get_cache_path_by_url, load_jit_model, download_model
+from iopaint.schema import InpaintRequest
 import numpy as np
 
-from lama_cleaner.model.base import InpaintModel
+from iopaint.model.base import InpaintModel
 
 ZITS_INPAINT_MODEL_URL = os.environ.get(
     "ZITS_INPAINT_MODEL_URL",

iopaint/model_info.py

@@ -2,13 +2,13 @@ from typing import List
 
 from pydantic import computed_field, BaseModel
 
-from lama_cleaner.const import (
+from iopaint.const import (
     SDXL_CONTROLNET_CHOICES,
     SD2_CONTROLNET_CHOICES,
     SD_CONTROLNET_CHOICES,
 )
-from lama_cleaner.model import InstructPix2Pix, Kandinsky22, PowerPaint, SD2
-from lama_cleaner.schema import ModelType
+from iopaint.model import InstructPix2Pix, Kandinsky22, PowerPaint, SD2
+from iopaint.schema import ModelType
 
 
 class ModelInfo(BaseModel):

iopaint/model_manager.py

@@ -4,12 +4,12 @@ import torch
 from loguru import logger
 import numpy as np
 
-from lama_cleaner.download import scan_models
-from lama_cleaner.helper import switch_mps_device
-from lama_cleaner.model import models, ControlNet, SD, SDXL
-from lama_cleaner.model.utils import torch_gc
-from lama_cleaner.model_info import ModelInfo, ModelType
-from lama_cleaner.schema import InpaintRequest
+from iopaint.download import scan_models
+from iopaint.helper import switch_mps_device
+from iopaint.model import models, ControlNet, SD, SDXL
+from iopaint.model.utils import torch_gc
+from iopaint.model_info import ModelInfo, ModelType
+from iopaint.schema import InpaintRequest
 
 
 class ModelManager:

iopaint/plugins/anime_seg.py

@@ -5,9 +5,9 @@ import torch.nn.functional as F
 import numpy as np
 from PIL import Image
 
-from lama_cleaner.helper import load_model
-from lama_cleaner.plugins.base_plugin import BasePlugin
-from lama_cleaner.schema import RunPluginRequest
+from iopaint.helper import load_model
+from iopaint.plugins.base_plugin import BasePlugin
+from iopaint.schema import RunPluginRequest
 
 
 class REBNCONV(nn.Module):

iopaint/plugins/base_plugin.py

@@ -1,7 +1,7 @@
 from loguru import logger
 import numpy as np
 
-from lama_cleaner.schema import RunPluginRequest
+from iopaint.schema import RunPluginRequest
 
 
 class BasePlugin:

iopaint/plugins/gfpgan_plugin.py

@@ -2,9 +2,9 @@ import cv2
 import numpy as np
 from loguru import logger
 
-from lama_cleaner.helper import download_model
-from lama_cleaner.plugins.base_plugin import BasePlugin
-from lama_cleaner.schema import RunPluginRequest
+from iopaint.helper import download_model
+from iopaint.plugins.base_plugin import BasePlugin
+from iopaint.schema import RunPluginRequest
 
 
 class GFPGANPlugin(BasePlugin):

iopaint/plugins/interactive_seg.py

@@ -7,10 +7,10 @@ import numpy as np
 import torch
 from loguru import logger
 
-from lama_cleaner.helper import download_model
-from lama_cleaner.plugins.base_plugin import BasePlugin
-from lama_cleaner.plugins.segment_anything import SamPredictor, sam_model_registry
-from lama_cleaner.schema import RunPluginRequest
+from iopaint.helper import download_model
+from iopaint.plugins.base_plugin import BasePlugin
+from iopaint.plugins.segment_anything import SamPredictor, sam_model_registry
+from iopaint.schema import RunPluginRequest
 
 # 从小到大
 SEGMENT_ANYTHING_MODELS = {

iopaint/plugins/realesrgan.py

@@ -5,10 +5,10 @@ import numpy as np
 import torch
 from loguru import logger
 
-from lama_cleaner.const import RealESRGANModel
-from lama_cleaner.helper import download_model
-from lama_cleaner.plugins.base_plugin import BasePlugin
-from lama_cleaner.schema import RunPluginRequest
+from iopaint.const import RealESRGANModel
+from iopaint.helper import download_model
+from iopaint.plugins.base_plugin import BasePlugin
+from iopaint.schema import RunPluginRequest
 
 
 class RealESRGANUpscaler(BasePlugin):

iopaint/plugins/remove_bg.py

@@ -3,8 +3,8 @@ import cv2
 import numpy as np
 from torch.hub import get_dir
 
-from lama_cleaner.plugins.base_plugin import BasePlugin
-from lama_cleaner.schema import RunPluginRequest
+from iopaint.plugins.base_plugin import BasePlugin
+from iopaint.schema import RunPluginRequest
 
 
 class RemoveBG(BasePlugin):

iopaint/plugins/restoreformer.py

@@ -2,9 +2,9 @@ import cv2
 import numpy as np
 from loguru import logger
 
-from lama_cleaner.helper import download_model
-from lama_cleaner.plugins.base_plugin import BasePlugin
-from lama_cleaner.schema import RunPluginRequest
+from iopaint.helper import download_model
+from iopaint.plugins.base_plugin import BasePlugin
+from iopaint.schema import RunPluginRequest
 
 
 class RestoreFormerPlugin(BasePlugin):

iopaint/plugins/segment_anything/build_sam.py

@@ -8,7 +8,7 @@ import torch
 
 from functools import partial
 
-from lama_cleaner.plugins.segment_anything.modeling.tiny_vit_sam import TinyViT
+from iopaint.plugins.segment_anything.modeling.tiny_vit_sam import TinyViT
 
 from .modeling import (
     ImageEncoderViT,

iopaint/runtime.py

@@ -9,7 +9,7 @@ from loguru import logger
 from rich import print
 from typing import Dict, Any
 
-from lama_cleaner.const import Device
+from iopaint.const import Device
 
 _PY_VERSION: str = sys.version.split()[0].rstrip("+")
 
@@ -28,7 +28,7 @@ _CANDIDATES = [
     "transformers",
     "opencv-python",
     "accelerate",
-    "lama-cleaner",
+    "iopaint",
     "rembg",
     "realesrgan",
     "gfpgan",

iopaint/schema.py

@@ -5,7 +5,7 @@ from typing import Optional, Literal, List
 
 from pydantic import BaseModel, Field, field_validator
 
-from lama_cleaner.const import Device, InteractiveSegModel, RealESRGANModel
+from iopaint.const import Device, InteractiveSegModel, RealESRGANModel
 
 
 class PluginInfo(BaseModel):

iopaint/tests/test_adjust_mask.py

@@ -1,6 +1,6 @@
 import cv2
-from lama_cleaner.helper import adjust_mask
-from lama_cleaner.tests.utils import current_dir, save_dir
+from iopaint.helper import adjust_mask
+from iopaint.tests.utils import current_dir, save_dir
 
 mask_p = current_dir / "overture-creations-5sI6fQgYIuo_mask.png"
 

iopaint/tests/test_controlnet.py

@@ -1,7 +1,7 @@
 import os
 
-from lama_cleaner.const import SD_CONTROLNET_CHOICES
-from lama_cleaner.tests.utils import current_dir, check_device, get_config, assert_equal
+from iopaint.const import SD_CONTROLNET_CHOICES
+from iopaint.tests.utils import current_dir, check_device, get_config, assert_equal
 
 os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
 from pathlib import Path
@@ -9,8 +9,8 @@ from pathlib import Path
 import pytest
 import torch
 
-from lama_cleaner.model_manager import ModelManager
-from lama_cleaner.schema import HDStrategy, SDSampler
+from iopaint.model_manager import ModelManager
+from iopaint.schema import HDStrategy, SDSampler
 
 
 model_name = "runwayml/stable-diffusion-inpainting"

iopaint/tests/test_instruct_pix2pix.py

@@ -3,9 +3,9 @@ from pathlib import Path
 import pytest
 import torch
 
-from lama_cleaner.model_manager import ModelManager
-from lama_cleaner.schema import HDStrategy
-from lama_cleaner.tests.utils import get_config, check_device, assert_equal, current_dir
+from iopaint.model_manager import ModelManager
+from iopaint.schema import HDStrategy
+from iopaint.tests.utils import get_config, check_device, assert_equal, current_dir
 
 model_name = "timbrooks/instruct-pix2pix"
 

iopaint/tests/test_load_img.py

@@ -1,5 +1,5 @@
-from lama_cleaner.helper import load_img
-from lama_cleaner.tests.utils import current_dir
+from iopaint.helper import load_img
+from iopaint.tests.utils import current_dir
 
 png_img_p = current_dir / "image.png"
 jpg_img_p = current_dir / "bunny.jpeg"

iopaint/tests/test_model.py

@@ -1,9 +1,9 @@
 import pytest
 import torch
 
-from lama_cleaner.model_manager import ModelManager
-from lama_cleaner.schema import HDStrategy, LDMSampler
-from lama_cleaner.tests.utils import assert_equal, get_config, current_dir, check_device
+from iopaint.model_manager import ModelManager
+from iopaint.schema import HDStrategy, LDMSampler
+from iopaint.tests.utils import assert_equal, get_config, current_dir, check_device
 
 
 @pytest.mark.parametrize("device", ["cuda", "mps", "cpu"])

iopaint/tests/test_model_md5.py

@@ -1,6 +1,6 @@
 def test_load_model():
-    from lama_cleaner.plugins import InteractiveSeg
-    from lama_cleaner.model_manager import ModelManager
+    from iopaint.plugins import InteractiveSeg
+    from iopaint.model_manager import ModelManager
 
     interactive_seg_model = InteractiveSeg("vit_l", "cpu")
 

iopaint/tests/test_model_switch.py

@@ -1,12 +1,12 @@
 import os
 
-from lama_cleaner.schema import InpaintRequest
+from iopaint.schema import InpaintRequest
 
 os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
 
 import torch
 
-from lama_cleaner.model_manager import ModelManager
+from iopaint.model_manager import ModelManager
 
 
 def test_model_switch():

iopaint/tests/test_outpainting.py

@@ -1,6 +1,6 @@
 import os
 
-from lama_cleaner.tests.utils import current_dir, check_device
+from iopaint.tests.utils import current_dir, check_device
 
 os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
 from pathlib import Path
@@ -8,9 +8,9 @@ from pathlib import Path
 import pytest
 import torch
 
-from lama_cleaner.model_manager import ModelManager
-from lama_cleaner.schema import HDStrategy, SDSampler
-from lama_cleaner.tests.test_model import get_config, assert_equal
+from iopaint.model_manager import ModelManager
+from iopaint.schema import HDStrategy, SDSampler
+from iopaint.tests.test_model import get_config, assert_equal
 
 
 @pytest.mark.parametrize("name", ["runwayml/stable-diffusion-inpainting"])

iopaint/tests/test_paint_by_example.py

@@ -2,9 +2,9 @@ import cv2
 import pytest
 from PIL import Image
 
-from lama_cleaner.model_manager import ModelManager
-from lama_cleaner.schema import HDStrategy
-from lama_cleaner.tests.utils import (
+from iopaint.model_manager import ModelManager
+from iopaint.schema import HDStrategy
+from iopaint.tests.utils import (
     current_dir,
     get_config,
     get_data,

iopaint/tests/test_plugins.py

@@ -3,17 +3,17 @@ import os
 import time
 from PIL import Image
 
-from lama_cleaner.helper import encode_pil_to_base64, gen_frontend_mask
-from lama_cleaner.plugins.anime_seg import AnimeSeg
-from lama_cleaner.schema import RunPluginRequest
-from lama_cleaner.tests.utils import check_device, current_dir, save_dir
+from iopaint.helper import encode_pil_to_base64, gen_frontend_mask
+from iopaint.plugins.anime_seg import AnimeSeg
+from iopaint.schema import RunPluginRequest
+from iopaint.tests.utils import check_device, current_dir, save_dir
 
 os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
 
 import cv2
 import pytest
 
-from lama_cleaner.plugins import (
+from iopaint.plugins import (
     RemoveBG,
     RealESRGANUpscaler,
     GFPGANPlugin,

iopaint/tests/test_save_exif.py

@@ -5,7 +5,7 @@ from typing import List
 
 from PIL import Image
 
-from lama_cleaner.helper import pil_to_bytes, load_img
+from iopaint.helper import pil_to_bytes, load_img
 
 current_dir = Path(__file__).parent.absolute().resolve()
 

iopaint/tests/test_sd_model.py

@@ -2,7 +2,7 @@ import os
 
 from loguru import logger
 
-from lama_cleaner.tests.utils import check_device, get_config, assert_equal
+from iopaint.tests.utils import check_device, get_config, assert_equal
 
 os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
 from pathlib import Path
@@ -10,8 +10,8 @@ from pathlib import Path
 import pytest
 import torch
 
-from lama_cleaner.model_manager import ModelManager
-from lama_cleaner.schema import HDStrategy, SDSampler, FREEUConfig
+from iopaint.model_manager import ModelManager
+from iopaint.schema import HDStrategy, SDSampler, FREEUConfig
 
 current_dir = Path(__file__).parent.absolute().resolve()
 save_dir = current_dir / "result"

iopaint/tests/test_sdxl.py

@@ -1,15 +1,15 @@
 import os
 
-from lama_cleaner.tests.utils import check_device, current_dir
+from iopaint.tests.utils import check_device, current_dir
 
 os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
 
 import pytest
 import torch
 
-from lama_cleaner.model_manager import ModelManager
-from lama_cleaner.schema import HDStrategy, SDSampler, FREEUConfig
-from lama_cleaner.tests.test_model import get_config, assert_equal
+from iopaint.model_manager import ModelManager
+from iopaint.schema import HDStrategy, SDSampler, FREEUConfig
+from iopaint.tests.test_model import get_config, assert_equal
 
 
 @pytest.mark.parametrize("device", ["cuda", "mps"])

iopaint/tests/utils.py

@@ -3,8 +3,8 @@ import cv2
 import pytest
 import torch
 
-from lama_cleaner.helper import encode_pil_to_base64
-from lama_cleaner.schema import LDMSampler, HDStrategy, InpaintRequest, SDSampler
+from iopaint.helper import encode_pil_to_base64
+from iopaint.schema import LDMSampler, HDStrategy, InpaintRequest, SDSampler
 from PIL import Image
 
 current_dir = Path(__file__).parent.absolute().resolve()

iopaint/web_config.py

@@ -5,7 +5,7 @@ from datetime import datetime
 import gradio as gr
 from loguru import logger
 
-from lama_cleaner.const import *
+from iopaint.const import *
 
 _config_file = None
 

main.py

@@ -1,4 +1,4 @@
-from lama_cleaner import entry_point
+from iopaint import entry_point
 
 if __name__ == "__main__":
     entry_point()

publish.sh

@@ -4,6 +4,8 @@ set -e
 pushd ./web_app
 npm run build
 popd
+rm -r ./iopaint/web_app
+cp -r web_app/dist ./iopaint/web_app
 
 rm -r -f dist
 python3 setup.py sdist bdist_wheel

requirements.txt

@@ -6,7 +6,6 @@ safetensors
 controlnet-aux==0.0.3
 fastapi==0.108.0
 python-socketio==5.7.2
-flaskwebgui==0.3.5
 typer
 pydantic
 rich