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update docker

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Qing 2022-10-05 23:15:09 +08:00
parent 8a565e97b3
commit 1fd74a7cc6
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36
.github/workflows/docker_image.yml vendored Normal file
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name: Publish Docker image
on:
release:
types: [published]
jobs:
push_to_registry:
name: Push Docker image to Docker Hub
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v3
# - name: Log in to Docker Hub
# uses: docker/login-action@f054a8b539a109f9f41c372932f1ae047eff08c9
# with:
# username: ${{ secrets.DOCKER_USERNAME }}
# password: ${{ secrets.DOCKER_PASSWORD }}
- name: Extract metadata (tags, labels) for Docker
id: meta
uses: docker/metadata-action@98669ae865ea3cffbcbaa878cf57c20bbf1c6c38
with:
images: cwq1913/lamacleaner
tags: type=semver,pattern={{version}}
- name: Build and push CPU Docker image
uses: docker/build-push-action@v3.1.1
with:
context: .
file: ./docker/CPUDockerfile
push: false
tags: |
${{ steps.meta.outputs.tags }}
cpu
labels: ${{ steps.meta.outputs.labels }}

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Dockerfile
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#
# Lama Cleaner Dockerfile
# @author Loreto Parisi (loretoparisi at gmail dot com)
#
FROM python:3.7.4-slim-buster
LABEL maintainer Loreto Parisi loretoparisi@gmail.com
WORKDIR app
RUN apt-get update && apt-get install -y --no-install-recommends \
software-properties-common \
libsm6 libxext6 ffmpeg libfontconfig1 libxrender1 libgl1-mesa-glx \
curl \
npm
# python requirements
COPY . .
COPY requirements.txt /etc/tmp/requirements.txt
RUN pip install -r /etc/tmp/requirements.txt
# nodejs
RUN npm install n -g && \
n lts
# yarn
RUN npm install -g yarn
# webapp
RUN cd lama_cleaner/app/ && \
yarn && \
yarn build
EXPOSE 8080
CMD ["bash"]

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README.md
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@ -33,29 +33,54 @@
## Usage
<details>
<summary>1. Remove any unwanted things on the image</summary>
| Usage | Before | After |
| ---------------------- | --------------------------------------------- | -------------------------------------------------------------- |
| ---------------------- | --------------------------------------------- | --------------------------------------------------- |
| Remove unwanted things | ![unwant_object2](./assets/unwant_object.jpg) | ![unwant_object2](./assets/unwant_object_clean.jpg) |
| Remove unwanted person | ![unwant_person](./assets/unwant_person.jpg) | ![unwant_person](./assets/unwant_person_clean.jpg) |
| Remove Text | ![text](./assets/unwant_text.jpg) | ![text](./assets/unwant_text_clean.jpg) |
| Remove watermark | ![watermark](./assets/watermark.jpg) | ![watermark_clean](./assets/watermark_cleanup.jpg) |
</details>
<details>
<summary>2. Fix old photo</summary>
| Usage | Before | After |
| ------------- | ----------------------------------- | ----------------------------------------------- |
| Fix old photo | ![oldphoto](./assets/old_photo.jpg) | ![oldphoto_clean](./assets/old_photo_clean.jpg) |
</details>
<details>
<summary>3. Replace something on the image </summary>
| Usage | Before | After |
| ---------------------- | ------------------------ | -------------------------------------------------------------- |
| Text Driven Inpainting | ![dog](./assets/dog.jpg) | Prompt: a fox sitting on a bench<br/> ![fox](./assets/fox.jpg) |
</details>
## Quick Start
The easiest way to use Lama Cleaner is to install it using `pip`:
```bash
pip install lama-cleaner
# Model will be downloaded automatically
# Models will be downloaded at first time used
lama-cleaner --model=lama --device=cpu --port=8080
# Lama Cleaner is now running at http://localhost:8080
```
Available arguments:
If you prefer to use docker, you can check out [docker](#docker)
Available command line arguments:
| Name | Description | Default |
|-------------------|-------------------------------------------------------------------------------------------------------------------------------| -------- |
| -------------------- | ----------------------------------------------------------------------------------------------------------------------------- | -------- |
| --model | lama/ldm/zits/mat/fcf/sd1.4 See details in [Inpaint Model](#inpainting-model) | lama |
| --hf_access_token | stable-diffusion(sd) model need [huggingface access token](https://huggingface.co/docs/hub/security-tokens) to download model | |
| --sd-run-local | Once the model as downloaded, you can pass this arg and remove `--hf_access_token` | |
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## Docker
Run within a Docker container. Set the `CACHE_DIR` to models location path. Optionally add a `-d` option to
the `docker run` command below to run as a daemon.
You can use [pre-build docker image]() to run Lama Cleaner. The model will be downloaded to the cache directory when first time used.
You can mount existing cache directory to start the container,
so you don't have to download the model every time you start the container.
### Build Docker image
The cache directories for different models correspond as follows:
```
docker build -f Dockerfile -t lamacleaner .
```
- lama/ldm/zits/mat/fcf: /root/.cache/torch
- sd1.4: /root/.cache/huggingface
### Run Docker (cpu)
```
docker run -p 8080:8080 -e CACHE_DIR=/app/models -v $(pwd)/models:/app/models -v $(pwd):/app --rm lamacleaner \
python3 main.py --device=cpu --port=8080 --host=0.0.0.0
docker run -p 8080:8080 \
-v /path/to/torch_cache:/root/.cache/torch \
-v /path/to/huggingface_cache:/root/.cache/huggingface \
--rm lamacleaner \
lama-cleaner --device=cpu --port=8080 --host=0.0.0.0
```
### Run Docker (gpu)
```
docker run --gpus all -p 8080:8080 -e CACHE_DIR=/app/models -v $(pwd)/models:/app/models -v $(pwd):/app --rm lamacleaner \
python3 main.py --device=cuda --port=8080 --host=0.0.0.0
docker run --gpus all -p 8080:8080 \
-v /path/to/torch_cache:/root/.cache/torch \
-v /path/to/huggingface_cache:/root/.cache/huggingface \
lama-cleaner --device=cuda --port=8080 --host=0.0.0.0
```
Then open [http://localhost:8080](http://localhost:8080)
### Build Docker image
cpu only
```
docker build -f ./docker/CPUDockerfile -t lamacleaner .
```
gpu & cpu
- cuda11.6
- pytorch1.12.1
```
docker build -f ./docker/GPUDockerfile -t lamacleaner .
```
## One Click Installer
TODO

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docker/CPUDockerfile Normal file
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FROM python:3.7.4-slim-buster
RUN apt-get update && apt-get install -y --no-install-recommends \
software-properties-common \
libsm6 libxext6 ffmpeg libfontconfig1 libxrender1 libgl1-mesa-glx \
curl
RUN pip install --upgrade pip && \
pip install torch==1.12.1 --extra-index-url https://download.pytorch.org/whl/cpu
RUN pip install lama-cleaner
EXPOSE 8080
CMD ["bash"]

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docker/GPUDockerfile Normal file
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FROM nvidia/cuda:11.6.1-runtime-ubuntu20.04
RUN apt-get update && apt-get install -y --no-install-recommends \
software-properties-common \
libsm6 libxext6 ffmpeg libfontconfig1 libxrender1 libgl1-mesa-glx \
curl python3-pip
RUN pip3 install --upgrade pip && \
pip3 install torch==1.12.1 --extra-index-url https://download.pytorch.org/whl/cu116
RUN pip3 install lama-cleaner
EXPOSE 8080
CMD ["bash"]