Commit e7af30dd authored by narugo1992's avatar narugo1992
Browse files

Merge branch 'main' into ccip

parents ed8bb266 2819e994

.github/workflows/badge.yml

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@@ -10,7 +10,7 @@ jobs: 
    runs-on: ubuntu-latest

    strategy:

      matrix:

        python-version: [ 3.7 ]

        python-version: [ 3.8 ]

    steps:

      - name: Checkout code

        uses: actions/checkout@v2

.github/workflows/doc.yml

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@@ -15,7 +15,7 @@ jobs: 
    if: ${{ !contains(github.event.head_commit.message, 'ci skip') }}

    strategy:

      matrix:

        python-version: [ 3.7 ]

        python-version: [ 3.8 ]



    services:

      plantuml:
@@ -89,7 +89,7 @@ jobs: 
    if: "!contains(github.event.head_commit.message, 'ci skip')"

    strategy:

      matrix:

        python-version: [ 3.7 ]

        python-version: [ 3.8 ]



    services:

      plantuml:

.github/workflows/test.yml

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#file: noinspection YAMLSchemaValidation

name: Code Test



on:
@@ -7,7 +8,7 @@ jobs: 
  unittest:

    name: Code test

    runs-on: ${{ matrix.os }}

    if: "!contains(github.event.head_commit.message, 'ci skip')"

    if: ${{ !contains(github.event.head_commit.message, 'ci skip') && !contains(github.event.head_commit.message, 'test skip') }}

    strategy:

      fail-fast: false

      matrix:
@@ -22,7 +23,8 @@ jobs: 
          - '3.10'

          - '3.11'

        exclude:

          - python-version: '3.11'

          - os: 'macos-latest'

            python-version: '3.7'



    steps:

      - name: Get system version for Linux

MANIFEST.in

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@@ -2,4 +2,4 @@ include README.md 
include MANIFEST.in

include requirements.txt

include requirements-*.txt

recursive-include imgutils *.json *.yml *.yaml
 
recursive-include imgutils *.json *.yml *.yaml *.png

README.md

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@@ -71,13 +71,17 @@ print(lpips_clustering(images)) # -1 means noises, the same as that in sklearn 


Currently, object detection is supported for anime heads and person, as shown below



* Face Detection



![face detection](https://github.com/deepghs/imgutils/blob/gh-pages/main/_images/face_detect_demo.plot.py.svg)



* Head Detection



![head detection](https://github.com/deepghs/imgutils/blob/gh-pages/main/_images/head_detect.plot.py.svg)

![head detection](https://github.com/deepghs/imgutils/blob/gh-pages/main/_images/head_detect_demo.plot.py.svg)



* Person Detection



![person detection](https://github.com/deepghs/imgutils/blob/gh-pages/main/_images/person_detect.plot.py.svg)

![person detection](https://github.com/deepghs/imgutils/blob/gh-pages/main/_images/person_detect_demo.plot.py.svg)



Based on practical tests, head detection currently has a very stable performance and can be used for automation tasks.

However, person detection is still being further iterated and will focus on enhancing detection capabilities for
@@ -88,7 +92,7 @@ artistic illustrations in the future. 
Anime images can be converted to line drawings using the model provided

by [patrickvonplaten/controlnet_aux](https://github.com/patrickvonplaten/controlnet_aux), as shown below.



![edge example](https://github.com/deepghs/imgutils/blob/gh-pages/main/_images/edge.plot.py.svg)

![edge example](https://github.com/deepghs/imgutils/blob/gh-pages/main/_images/edge_demo.plot.py.svg)



It is worth noting that the `lineart` model may consume more computational resources, while `canny` is the fastest but

has average effect. Therefore, `lineart_anime` may be the most balanced choice in most cases.