add
Build-Deploy-Actions
Details
Build-Deploy-Actions
Details
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name: Build
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run-name: ${{ github.actor }} is upgrade release 🚀
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on: [push]
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env:
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REPOSITORY: ${{ github.repository }}
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COMMIT_ID: ${{ github.sha }}
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jobs:
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Build-Deploy-Actions:
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runs-on: ubuntu-latest
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steps:
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- run: echo "🎉 The job was automatically triggered by a ${{ github.event_name }} event."
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- run: echo "🐧 This job is now running on a ${{ runner.os }} server hosted by Gitea!"
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- run: echo "🔎 The name of your branch is ${{ github.ref }} and your repository is ${{ github.repository }}."
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- name: Check out repository code
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uses: actions/checkout@v3
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-
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name: Setup Git LFS
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run: |
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git lfs install
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git lfs fetch
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git lfs checkout
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- name: List files in the repository
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run: |
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ls ${{ github.workspace }}
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-
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name: Docker Image Info
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id: image-info
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run: |
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echo "::set-output name=image_name::$(echo $REPOSITORY | tr '[:upper:]' '[:lower:]')"
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echo "::set-output name=image_tag::${COMMIT_ID:0:10}"
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-
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name: Login to Docker Hub
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uses: docker/login-action@v2
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with:
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registry: artifacts.iflytek.com
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username: ${{ secrets.DOCKERHUB_USERNAME }}
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password: ${{ secrets.DOCKERHUB_TOKEN }}
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- name: Set up Docker Buildx
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uses: docker/setup-buildx-action@v2
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-
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name: Build and push
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run: |
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docker version
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docker buildx build -t artifacts.iflytek.com/docker-private/atp/${{ steps.image-info.outputs.image_name }}:${{ steps.image-info.outputs.image_tag }} . --file ${{ github.workspace }}/Dockerfile --load
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docker push artifacts.iflytek.com/docker-private/atp/${{ steps.image-info.outputs.image_name }}:${{ steps.image-info.outputs.image_tag }}
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docker rmi artifacts.iflytek.com/docker-private/atp/${{ steps.image-info.outputs.image_name }}:${{ steps.image-info.outputs.image_tag }}
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- run: echo "🍏 This job's status is ${{ job.status }}."
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FROM python:3.7.4-slim
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WORKDIR /app
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COPY requirements.txt /app
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RUN pip config set global.index-url https://pypi.mirrors.ustc.edu.cn/simple/
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RUN pip3 install --trusted-host pypi.python.org -r requirements.txt
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COPY . /app
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CMD ["python", "app.py"]
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#图像分类
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import gradio as gr
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from transformers import ViTFeatureExtractor, ViTForImageClassification
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from gradio.themes.utils import sizes
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theme = gr.themes.Default(radius_size=sizes.radius_none).set(
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block_label_text_color = '#4D63FF',
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block_title_text_color = '#4D63FF',
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button_primary_text_color = '#4D63FF',
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button_primary_background_fill='#FFFFFF',
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button_primary_border_color='#4D63FF',
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button_primary_background_fill_hover='#EDEFFF',
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)
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feature_extractor = ViTFeatureExtractor.from_pretrained('google/vit-base-patch16-224')
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model = ViTForImageClassification.from_pretrained('google/vit-base-patch16-224')
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def image_classification(image):
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inputs = feature_extractor(images=image, return_tensors="pt")
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outputs = model(**inputs)
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logits = outputs.logits
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predicted_class_idx = logits.argmax(-1).item()
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return model.config.id2label[predicted_class_idx]
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with gr.Blocks(theme=theme, css="footer {visibility: hidden}") as demo:
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gr.Markdown("""
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<div align='center' ><font size='60'>图像分类</font></div>
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""")
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with gr.Row():
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with gr.Column():
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image = gr.Image(label="图片")
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with gr.Row():
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button = gr.Button("提交", variant="primary")
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box2 = gr.Label(num_top_classes=1, label="类别")
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button.click(fn=image_classification, inputs=[image], outputs=box2)
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examples = gr.Examples(examples=[['cat.jpeg'], ['dog.jpeg'], ['zebra.jpeg']], inputs=[image], label="例子")
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if __name__ == "__main__":
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demo.queue(concurrency_count=3).launch(server_name = "0.0.0.0")
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gradio
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huggingface
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torch
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transformers
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