湖州网站开发,免费获取资源的公众号,菜鸟教程python在线编程,成华区网站开发一、项目背景
革命性的AI图像编辑技术,让您的图片焕然一新!无论水印、logo、不想要的人物或物体,都能被神奇地移除,只留下纯净的画面。操作简单,效果出众,给你全新的视觉体验。开启图像编辑新纪元,尽在掌控!
利用去水印开源工具Lama Cleaner对照片中杂质进行去除…
一、项目背景
革命性的AI图像编辑技术,让您的图片焕然一新!无论水印、logo、不想要的人物或物体,都能被神奇地移除,只留下纯净的画面。操作简单,效果出众,给你全新的视觉体验。开启图像编辑新纪元,尽在掌控!
利用去水印开源工具Lama Cleaner对照片中杂质进行去除
可以去AI擦除一切应用体验!
先看效果 二、Lama Cleaner是什么
Lama Cleaner是一款开源且免费的人工学习图片去水印程序个人主要学习用途没有图片分辨率限制个人使用暂未发现并且保存的图片质量很高个人觉得跟原图差不多还能下载处理后的图片到本地。
三、操作
1、安装
In [1]
!pip install litelama0.1.7
Looking in indexes: https://mirror.baidu.com/pypi/simple/, https://mirrors.aliyun.com/pypi/simple/
Collecting litelama0.1.7Downloading https://mirrors.aliyun.com/pypi/packages/6e/59/873f5cbaeae1f2b17e6d1ae6c74e1efde28783db4d7442346a77a6140673/litelama-0.1.7-py3-none-any.whl (21 kB)
Collecting kornia0.7.0 (from litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/ac/fa/5612c4b1ad83b3044062e9dd0ca3c91937d8023cff0836269e18573655b0/kornia-0.7.2-py2.py3-none-any.whl (825 kB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 825.4/825.4 kB 1.1 MB/s eta 0:00:0000:0100:01
Requirement already satisfied: numpy1.24.4 in /opt/conda/envs/python35-paddle120-env/lib/python3.10/site-packages (from litelama0.1.7) (1.26.2)
Collecting omegaconf2.3.0 (from litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/e3/94/1843518e420fa3ed6919835845df698c7e27e183cb997394e4a670973a65/omegaconf-2.3.0-py3-none-any.whl (79 kB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 79.5/79.5 kB 1.1 MB/s eta 0:00:00a 0:00:01
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Requirement already satisfied: pillow10.0.1 in /opt/conda/envs/python35-paddle120-env/lib/python3.10/site-packages (from litelama0.1.7) (10.1.0)
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Collecting torch2.0.1 (from litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/33/b3/1fcc3bccfddadfd6845dcbfe26eb4b099f1dfea5aa0e5cfb92b3c98dba5b/torch-2.2.2-cp310-cp310-manylinux1_x86_64.whl (755.5 MB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 755.5/755.5 MB 769.7 kB/s eta 0:00:0000:0100:16
Collecting kornia-rs0.1.0 (from kornia0.7.0-litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/7b/ef/eec16e87bc8893f608a42c96739ad0c35e30877b0f64bd19d95971534cef/kornia_rs-0.1.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.4 MB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2.4/2.4 MB 1.3 MB/s eta 0:00:0000:0100:01
Requirement already satisfied: packaging in /opt/conda/envs/python35-paddle120-env/lib/python3.10/site-packages (from kornia0.7.0-litelama0.1.7) (23.2)
Collecting antlr4-python3-runtime4.9.* (from omegaconf2.3.0-litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/3e/38/7859ff46355f76f8d19459005ca000b6e7012f2f1ca597746cbcd1fbfe5e/antlr4-python3-runtime-4.9.3.tar.gz (117 kB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 117.0/117.0 kB 1.3 MB/s eta 0:00:00a 0:00:01Preparing metadata (setup.py) ... done
Requirement already satisfied: PyYAML5.1.0 in /opt/conda/envs/python35-paddle120-env/lib/python3.10/site-packages (from omegaconf2.3.0-litelama0.1.7) (6.0.1)
Requirement already satisfied: charset-normalizer4,2 in /opt/conda/envs/python35-paddle120-env/lib/python3.10/site-packages (from requests2.31.0-litelama0.1.7) (3.3.2)
Requirement already satisfied: idna4,2.5 in /opt/conda/envs/python35-paddle120-env/lib/python3.10/site-packages (from requests2.31.0-litelama0.1.7) (3.6)
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Requirement already satisfied: certifi2017.4.17 in /opt/conda/envs/python35-paddle120-env/lib/python3.10/site-packages (from requests2.31.0-litelama0.1.7) (2023.11.17)
Requirement already satisfied: filelock in /opt/conda/envs/python35-paddle120-env/lib/python3.10/site-packages (from torch2.0.1-litelama0.1.7) (3.13.1)
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Collecting sympy (from torch2.0.1-litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/d2/05/e6600db80270777c4a64238a98d442f0fd07cc8915be2a1c16da7f2b9e74/sympy-1.12-py3-none-any.whl (5.7 MB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 5.7/5.7 MB 1.3 MB/s eta 0:00:0000:0100:01
Collecting networkx (from torch2.0.1-litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/d5/f0/8fbc882ca80cf077f1b246c0e3c3465f7f415439bdea6b899f6b19f61f70/networkx-3.2.1-py3-none-any.whl (1.6 MB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.6/1.6 MB 1.3 MB/s eta 0:00:0000:0100:01
Requirement already satisfied: jinja2 in /opt/conda/envs/python35-paddle120-env/lib/python3.10/site-packages (from torch2.0.1-litelama0.1.7) (3.1.2)
Requirement already satisfied: fsspec in /opt/conda/envs/python35-paddle120-env/lib/python3.10/site-packages (from torch2.0.1-litelama0.1.7) (2023.10.0)
Collecting nvidia-cuda-nvrtc-cu1212.1.105 (from torch2.0.1-litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/b6/9f/c64c03f49d6fbc56196664d05dba14e3a561038a81a638eeb47f4d4cfd48/nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 23.7/23.7 MB 1.3 MB/s eta 0:00:0000:0100:01
Collecting nvidia-cuda-runtime-cu1212.1.105 (from torch2.0.1-litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/eb/d5/c68b1d2cdfcc59e72e8a5949a37ddb22ae6cade80cd4a57a84d4c8b55472/nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 823.6/823.6 kB 1.2 MB/s eta 0:00:0000:0100:01
Collecting nvidia-cuda-cupti-cu1212.1.105 (from torch2.0.1-litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/7e/00/6b218edd739ecfc60524e585ba8e6b00554dd908de2c9c66c1af3e44e18d/nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (14.1 MB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 14.1/14.1 MB 1.2 MB/s eta 0:00:0000:0100:01
Collecting nvidia-cudnn-cu128.9.2.26 (from torch2.0.1-litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/ff/74/a2e2be7fb83aaedec84f391f082cf765dfb635e7caa9b49065f73e4835d8/nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl (731.7 MB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 731.7/731.7 MB 737.2 kB/s eta 0:00:0000:0100:16
Collecting nvidia-cublas-cu1212.1.3.1 (from torch2.0.1-litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/37/6d/121efd7382d5b0284239f4ab1fc1590d86d34ed4a4a2fdb13b30ca8e5740/nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl (410.6 MB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 410.6/410.6 MB 1.0 MB/s eta 0:00:0000:0100:08
Collecting nvidia-cufft-cu1211.0.2.54 (from torch2.0.1-litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/86/94/eb540db023ce1d162e7bea9f8f5aa781d57c65aed513c33ee9a5123ead4d/nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl (121.6 MB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 121.6/121.6 MB 1.3 MB/s eta 0:00:0000:0100:03
Collecting nvidia-curand-cu1210.3.2.106 (from torch2.0.1-litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/44/31/4890b1c9abc496303412947fc7dcea3d14861720642b49e8ceed89636705/nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl (56.5 MB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 56.5/56.5 MB 1.4 MB/s eta 0:00:0000:0100:01
Collecting nvidia-cusolver-cu1211.4.5.107 (from torch2.0.1-litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/bc/1d/8de1e5c67099015c834315e333911273a8c6aaba78923dd1d1e25fc5f217/nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl (124.2 MB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 124.2/124.2 MB 1.4 MB/s eta 0:00:0000:0100:03
Collecting nvidia-cusparse-cu1212.1.0.106 (from torch2.0.1-litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/65/5b/cfaeebf25cd9fdec14338ccb16f6b2c4c7fa9163aefcf057d86b9cc248bb/nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl (196.0 MB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 196.0/196.0 MB 1.2 MB/s eta 0:00:0000:0100:04
Collecting nvidia-nccl-cu122.19.3 (from torch2.0.1-litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/38/00/d0d4e48aef772ad5aebcf70b73028f88db6e5640b36c38e90445b7a57c45/nvidia_nccl_cu12-2.19.3-py3-none-manylinux1_x86_64.whl (166.0 MB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 166.0/166.0 MB 1.2 MB/s eta 0:00:0000:0100:04
Collecting nvidia-nvtx-cu1212.1.105 (from torch2.0.1-litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/da/d3/8057f0587683ed2fcd4dbfbdfdfa807b9160b809976099d36b8f60d08f03/nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 99.1/99.1 kB 1.0 MB/s eta 0:00:00a 0:00:01
Collecting triton2.2.0 (from torch2.0.1-litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/95/05/ed974ce87fe8c8843855daa2136b3409ee1c126707ab54a8b72815c08b49/triton-2.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (167.9 MB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 167.9/167.9 MB 1.2 MB/s eta 0:00:0000:0100:04
Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu1211.4.5.107-torch2.0.1-litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/58/d1/d1c80553f9d5d07b6072bc132607d75a0ef3600e28e1890e11c0f55d7346/nvidia_nvjitlink_cu12-12.4.99-py3-none-manylinux2014_x86_64.whl (21.1 MB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 21.1/21.1 MB 1.4 MB/s eta 0:00:0000:0100:01
Requirement already satisfied: MarkupSafe2.0 in /opt/conda/envs/python35-paddle120-env/lib/python3.10/site-packages (from jinja2-torch2.0.1-litelama0.1.7) (2.1.3)
Collecting mpmath0.19 (from sympy-torch2.0.1-litelama0.1.7)Downloading https://mirrors.aliyun.com/pypi/packages/43/e3/7d92a15f894aa0c9c4b49b8ee9ac9850d6e63b03c9c32c0367a13ae62209/mpmath-1.3.0-py3-none-any.whl (536 kB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 536.2/536.2 kB 1.3 MB/s eta 0:00:0000:0100:01
Building wheels for collected packages: antlr4-python3-runtimeBuilding wheel for antlr4-python3-runtime (setup.py) ... doneCreated wheel for antlr4-python3-runtime: filenameantlr4_python3_runtime-4.9.3-py3-none-any.whl size144554 sha256077a76af915c8b5e871c1a81a6cbda25ccce15c65326cd9d79be4d51a5141f99Stored in directory: /home/aistudio/.cache/pip/wheels/79/82/b1/b79d6e90f34257cd436860ed4f4a09f9e1ea8cd32da7046ea4
Successfully built antlr4-python3-runtime
Installing collected packages: mpmath, antlr4-python3-runtime, triton, sympy, omegaconf, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, networkx, kornia-rs, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, torch, kornia, litelama
Successfully installed antlr4-python3-runtime-4.9.3 kornia-0.7.2 kornia-rs-0.1.2 litelama-0.1.7 mpmath-1.3.0 networkx-3.2.1 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.19.3 nvidia-nvjitlink-cu12-12.4.99 nvidia-nvtx-cu12-12.1.105 omegaconf-2.3.0 sympy-1.12 torch-2.2.2 triton-2.2.02、clean_object
In [2]
from litelama import LiteLama
from litelama.model import download_file
import os
from fastapi import FastAPI, BodyMODEL_PATH work/models/def clean_object_init_img_with_mask(init_img_with_mask):return clean_object(init_img_with_mask[image],init_img_with_mask[mask])def clean_object(image,mask):Lama LiteLama2()init_image imagemask_image maskinit_image init_image.convert(RGB)mask_image mask_image.convert(RGB)device cuda:0result Nonetry:Lama.to(device)result Lama.predict(init_image, mask_image)except:passfinally:Lama.to(cpu)return [result]class LiteLama2(LiteLama):_instance Nonedef __new__(cls, *args, **kw):if cls._instance is None:cls._instance object.__new__(cls, *args, **kw)return cls._instancedef __init__(self, checkpoint_pathNone, config_pathNone):self._checkpoint_path checkpoint_pathself._config_path config_pathself._model Noneif self._checkpoint_path is None:checkpoint_path os.path.join(MODEL_PATH, big-lama.safetensors)if os.path.exists(checkpoint_path) and os.path.isfile(checkpoint_path):passelse:download_file(https://huggingface.co/anyisalin/big-lama/resolve/main/big-lama.safetensors, checkpoint_path)self._checkpoint_path checkpoint_pathself.load(locationcpu)3、去除标记物 In [3]
from PIL import Image
from work.scripts import lama
# 打开图片文件
image Image.open(work/scripts/1.jpg)
mask Image.open(work/scripts/image.png)
_output clean_object(image,mask)
print(_output)
/opt/conda/envs/python35-paddle120-env/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.htmlfrom .autonotebook import tqdm as notebook_tqdm[PIL.Image.Image image modeRGB size464x712 at 0x7F5007677B20]4、查看结果
In [4]
_output[0].show() PIL.Image.Image image modeRGB size464x712
四、Gradio应用部署
本文开头所示的Gradio应用已经打包在work/scripts目录下的app.gradio.py文件内大家可按照aistudio应用部署的方法进行在线部署也可下载文件到本地进行本地运行。
具体步骤如下
编辑器右上角找到部署按钮 选择Gradio部署 填写应用信息执行文件选择 app.gradio.py部署环境选择 GPU 即可最后点击部署接下来耐心等待部署完成。
