update one click installer
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@ -86,10 +86,12 @@ get an access token from here [huggingface access token](https://huggingface.co/
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If you prefer to use docker, you can check out [docker](#docker)
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If you hava no idea what is docker or pip, please check [One Click Installer](./scripts/README.md)
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Available command line arguments:
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| Name | Description | Default |
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| -------------------- | ----------------------------------------------------------------------------------------------------------------------------- | -------- |
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| -------------------- | ------------------------------------------------------------------------------------------------------------------- | -------- |
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| --model | lama/ldm/zits/mat/fcf/sd1.5 See details in [Inpaint Model](#inpainting-model) | lama |
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| --hf_access_token | stable-diffusion need [huggingface access token](https://huggingface.co/docs/hub/security-tokens) to download model | |
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| --sd-run-local | Once the model as downloaded, you can pass this arg and remove `--hf_access_token` | |
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@ -228,7 +230,3 @@ gpu & cpu
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```
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docker build -f ./docker/GPUDockerfile -t lamacleaner .
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```
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## One Click Installer
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TODO
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2
scripts/.gitignore
vendored
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2
scripts/.gitignore
vendored
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@ -0,0 +1,2 @@
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lama-cleaner/
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*.zip
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15
scripts/README.md
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15
scripts/README.md
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@ -0,0 +1,15 @@
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# Lama Cleaner One Click Installer
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## macOS
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1. Download [lama-cleaner.zip]()
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1. Unpack lama-cleaner.zip
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1. Double click `mac_config.command`, follow the guide in the terminal to choice model and set other configs.
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- lama model: State of the art image inpainting AI model, useful to remove any unwanted object, defect, people from your pictures.
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- sd1.5 model: Stable Diffusion model, text-driven image editing. To use this model you need to [accepting the terms to access](https://huggingface.co/runwayml/stable-diffusion-inpainting), and
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get an access token from here [huggingface access token](https://huggingface.co/docs/hub/security-tokens).
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1. Double click `mac_start.command` to start the server.
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## Windows
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coming soon...
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@ -4,4 +4,7 @@ channels:
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- conda-forge
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dependencies:
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- conda
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- git
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- git-lfs
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- invoke
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- rich
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22
scripts/pack.bat
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22
scripts/pack.bat
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@ -0,0 +1,22 @@
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@echo off
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export "PYTHONNOUSERSITE=1"
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SET BUILD_DIST=lama-cleaner
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SET BUILD_ENV=installer
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SET USER_SCRIPTS=user_scripts
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echo "Creating a distributable package.."
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source "~\miniconda3\etc\profile.d\conda.sh"
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conda "install" "-c" "conda-forge" "-y" "conda-pack"
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conda "env" "create" "--prefix" "%BUILD_ENV%" "-f" "environment.yaml"
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conda "activate" "%CD%\%BUILD_ENV%"
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conda "pack" "--n-threads" "-1" "--prefix" "%BUILD_ENV%" "--format" "tar"
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mkdir "-p" "%BUILD_DIST%/%BUILD_ENV%"
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echo "Copy user scripts file %USER_SCRIPTS%"
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COPY "%USER_SCRIPTS%/*" "%BUILD_DIST%"
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cd "%BUILD_DIST%"
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tar "-xf" "%CD%.\%BUILD_ENV%%CD%tar" "-C" "%BUILD_ENV%"
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cd "%CD%."
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DEL /S "%BUILD_ENV%"
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DEL "%BUILD_ENV%%CD%tar"
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echo "zip %BUILD_DIST%%CD%zip"
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zip "-q" "-r" "%BUILD_DIST%%CD%zip" "%BUILD_DIST%"
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@ -1,11 +1,14 @@
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#!/bin/bash
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# Prepare basic python environment
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set -e
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# Ensuer not use user's python package
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export PYTHONNOUSERSITE=1
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BUILD_DIST=lama-cleaner
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BUILD_ENV=installer
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USER_SCRIPTS=user_scripts
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echo "Creating a distributable package.."
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@ -20,9 +23,8 @@ conda pack --n-threads -1 --prefix $BUILD_ENV --format tar
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mkdir -p ${BUILD_DIST}/$BUILD_ENV
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echo "Copy project file.."
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chmod u+x start.sh
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cp start.sh $BUILD_DIST
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echo "Copy user scripts file ${USER_SCRIPTS}"
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cp ${USER_SCRIPTS}/* $BUILD_DIST
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cd $BUILD_DIST
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tar -xf ../${BUILD_ENV}.tar -C $BUILD_ENV
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@ -31,5 +33,6 @@ cd ..
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rm -rf $BUILD_ENV
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rm ${BUILD_ENV}.tar
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zip -r $BUILD_DIST.zip $BUILD_DIST
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echo "zip ${BUILD_DIST}.zip"
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zip -q -r $BUILD_DIST.zip $BUILD_DIST
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@ -1,14 +0,0 @@
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#!/bin/bash
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source installer/bin/activate
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conda-unpack
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conda --version
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git --version
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echo Using `which pip3`
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pip3 install lama-cleaner
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# TODO: add model input prompt
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lama-cleaner --device cpu --model lama
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0
scripts/user_scripts/README.md
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0
scripts/user_scripts/README.md
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13
scripts/user_scripts/mac_config.command
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13
scripts/user_scripts/mac_config.command
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#!/bin/bash
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set -e
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cd "$(dirname "$0")"
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echo `pwd`
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source ./installer/bin/activate
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conda-unpack
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pip3 install -U lama-cleaner
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invoke config --disable-device-choice
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scripts/user_scripts/mac_start.command
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11
scripts/user_scripts/mac_start.command
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#!/bin/bash
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set -e
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cd "$(dirname "$0")"
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echo `pwd`
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source ./installer/bin/activate
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conda-unpack
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invoke start
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100
scripts/user_scripts/tasks.py
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100
scripts/user_scripts/tasks.py
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import os
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import json
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from enum import Enum
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import socket
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import logging
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from contextlib import closing
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from invoke import task
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from rich import print
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from rich.prompt import IntPrompt, Prompt, Confirm
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from rich.logging import RichHandler
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FORMAT = "%(message)s"
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logging.basicConfig(
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level="INFO", format=FORMAT, datefmt="[%X]", handlers=[RichHandler()]
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)
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log = logging.getLogger("lama-cleaner")
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def find_free_port() -> int:
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with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as s:
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s.bind(('', 0))
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s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
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return s.getsockname()[1]
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CONFIG_PATH = "config.json"
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class MODEL(str, Enum):
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SD15 = "sd1.5"
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LAMA = 'lama'
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class DEVICE(str, Enum):
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CUDA = "cuda"
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CPU = "cpu"
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@task
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def info(c):
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print("Environment information".center(60, "-"))
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try:
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c.run("git --version")
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c.run("conda --version")
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c.run("which python")
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c.run("python --version")
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c.run("which pip")
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c.run("pip --version")
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c.run("pip list | grep lama")
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except:
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pass
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print("-"*60)
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@task(pre=[info])
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def config(c, disable_device_choice=False):
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# TODO: 提示选择模型,选择设备,端口,host
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# 如果是 sd 模型,提示接受条款和输入 huggingface token
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model = Prompt.ask("Choice model", choices=[MODEL.SD15, MODEL.LAMA], default=MODEL.SD15)
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hf_access_token = ""
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if model == MODEL.SD15:
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while True:
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hf_access_token = Prompt.ask("Huggingface access token (https://huggingface.co/docs/hub/security-tokens)")
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if hf_access_token == "":
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log.warning("Access token is required to download model")
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else:
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break
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if disable_device_choice:
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device = DEVICE.CPU
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else:
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device = Prompt.ask("Choice device", choices=[DEVICE.CUDA, DEVICE.CPU], default=DEVICE.CUDA)
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if device == DEVICE.CUDA:
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import torch
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if not torch.cuda.is_available():
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log.warning("Did not find CUDA device on your computer, fallback to cpu")
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device = DEVICE.CPU
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configs = {"model": model, "device": device, "hf_access_token": hf_access_token}
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log.info(f"Save config to {CONFIG_PATH}")
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with open(CONFIG_PATH, 'w', encoding='utf-8') as f:
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json.dump(configs, f, indent=2, ensure_ascii=False)
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log.info(f"Config finish, you can close this window.")
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@task(pre=[info])
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def start(c):
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if not os.path.exists(CONFIG_PATH):
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log.info("Config file not exists, please run config.sh first")
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exit()
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log.info(f"Load config from {CONFIG_PATH}")
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with open(CONFIG_PATH, 'r', encoding='utf-8') as f:
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configs = json.load(f)
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model = configs['model']
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device = configs['device']
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hf_access_token = configs['hf_access_token']
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port = find_free_port()
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log.info(f"Using random port: {port}")
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c.run(f"lama-cleaner --model {model} --device {device} --hf_access_token={hf_access_token} --port {port} --gui --gui-size 1400 900")
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