Add CI

Author: jaggerwang

.github/workflows/main.yml

@@ -0,0 +1,17 @@
+name: Mirroring
+
+on: [push, delete]
+
+jobs:
+  to_gitlab:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+        with:
+          fetch-depth: 0
+      - uses: pixta-dev/repository-mirroring-action@v1
+        with:
+          target_repo_url:
+            git@gitlab.talos.basic.ai:basicai/xtreme1/image-object-detection.git
+          ssh_private_key:
+            ${{ secrets.GITLAB_SSH_PRIVATE_KEY }}

.ops/.gitlab-ci.yml

@@ -0,0 +1,54 @@
+stages:
+  - build-image
+  - deploy
+
+variables:
+  APP_NAME: "image-object-detection"
+  APP_VERSION: "0.5.1"
+  IMAGE_NAME: $CI_REGISTRY_IMAGE
+  IMAGE: $IMAGE_NAME:$CI_COMMIT_SHORT_SHA
+  KUBERNETES_NAMESPACE: "basicai-xtreme1"
+
+docker-build:
+  stage: build-image
+  tags:
+    - docker
+  rules:
+    - if: $CI_COMMIT_BRANCH =~ /^dev/
+    - if: $CI_COMMIT_BRANCH =~ /^main/
+    - if: $CI_COMMIT_TAG
+  variables:
+    DOCKER_HOST: tcp://docker:2376
+    DOCKER_TLS_CERTDIR: "/certs"
+    DOCKER_TLS_VERIFY: 1
+    DOCKER_CERT_PATH: "$DOCKER_TLS_CERTDIR/client"
+  services:
+    - docker:20-dind
+  before_script:
+    - until docker info; do sleep 1; done
+    - docker login -u $CI_DEPLOY_USER -p $CI_DEPLOY_PASSWORD $CI_REGISTRY
+  script:
+    - docker pull $IMAGE_NAME:latest || true
+    - docker build --cache-from $IMAGE_NAME:latest -t $IMAGE_NAME:$CI_COMMIT_REF_NAME -t $IMAGE_NAME:$CI_COMMIT_SHORT_SHA -t $IMAGE_NAME:latest .
+    - docker push $IMAGE_NAME:$CI_COMMIT_REF_NAME
+    - docker push $IMAGE_NAME:$CI_COMMIT_SHORT_SHA
+    - docker push $IMAGE_NAME:latest
+
+.deploy:
+  stage: deploy
+  tags:
+    - kubectl
+  before_script:
+    - cd .ops/$ENV
+    - sed -i 's/$APP_NAME/'"$APP_NAME"'/g' deployment.yml
+    - sed -i 's/$APP_VERSION/'"$APP_VERSION"'/g' deployment.yml
+    - sed -i 's|$IMAGE|'"$IMAGE"'|g' deployment.yml
+
+deploy-alidev:
+  extends: .deploy
+  rules:
+    - if: $CI_COMMIT_BRANCH =~ /^dev/
+  variables:
+    ENV: alidev
+  script:
+    - kubectl apply -f deployment.yml -n $KUBERNETES_NAMESPACE --kubeconfig=$KUBECONFIG_ALIYUN_DEVELOPMENT

.ops/alidev/deployment.yml

@@ -0,0 +1,71 @@
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: $APP_NAME
+spec:
+  replicas: 1
+  strategy:
+    type: Recreate
+  selector:
+    matchLabels:
+      app.kubernetes.io/name: xtreme1
+      app.kubernetes.io/instance: xtreme1
+      app.kubernetes.io/component: $APP_NAME
+  template:
+    metadata:
+      labels:
+        app.kubernetes.io/name: xtreme1
+        app.kubernetes.io/instance: xtreme1
+        app.kubernetes.io/component: $APP_NAME
+    spec:
+      nodeSelector:
+        dedicated: model
+      affinity:
+        podAntiAffinity:
+          preferredDuringSchedulingIgnoredDuringExecution:
+          - weight: 100
+            podAffinityTerm:
+              labelSelector:
+                matchExpressions:
+                - key: "app.kubernetes.io/name"
+                  operator: In
+                  values:
+                  - xtreme1
+                - key: "app.kubernetes.io/instance"
+                  operator: In
+                  values:
+                  - xtreme1
+                - key: "app.kubernetes.io/component"
+                  operator: In
+                  values:
+                  - $APP_NAME
+              topologyKey: "kubernetes.io/hostname"
+      imagePullSecrets:
+        - name: basicai-registry
+      containers:
+        - name: $APP_NAME
+          image: $IMAGE
+          resources:
+            requests:
+              memory: 1Gi
+              cpu: 100m
+            limits:
+              aliyun.com/gpu-mem: 8
+              aliyun.com/gpu-core.percentage: 50
+          ports:
+            - name: http
+              containerPort: 5000
+---
+apiVersion: v1
+kind: Service
+metadata:
+  name: $APP_NAME
+spec:
+  selector:
+    app.kubernetes.io/name: xtreme1
+    app.kubernetes.io/instance: xtreme1
+    app.kubernetes.io/component: $APP_NAME
+  ports:
+    - name: http
+      port: 80
+      targetPort: 5000

Dockerfile

@@ -1,5 +1,10 @@
-FROM  basicai/xtreme1-image-object-detection:base
+FROM basicai/xtreme1-image-object-detection-base
+
 RUN pip install flask_cors
-COPY ./ /yolor
-WORKDIR /yolor/src
-CMD ["python","-u","server.py","--device=0","--weights=../coco80.pt","--conf-thres=0.5","--port=5000"] 
+
+WORKDIR /app
+RUN wget https://basicai-asset.s3.us-west-2.amazonaws.com/xtreme1/model/coco80.pth
+COPY . ./
+
+WORKDIR /app/src
+CMD ["python", "-u", "server.py", "--device=0", "--weights=../coco80.pt", "--conf-thres=0.5", "--port=5000"] 

README.md

@@ -0,0 +1,22 @@
+# Image Object Detection
+
+Create base image:
+```bash
+cd base_image
+docker build -t basicai/xtreme1-image-object-detection-base .
+```
+
+Using base container to run model service:
+```bash
+docker run -it --rm -p 5000:5000 -v .:/app --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=0 -m 32G --memory-reservation 8G --cpu-shares=80 --shm-size=32G xtreme1-image-object-detection-base env LANG=C.UTF-8 /bin/bash
+
+# The following commands run in the container
+cd /app
+wget https://basicai-asset.s3.us-west-2.amazonaws.com/xtreme1/model/coco80.pth
+
+cd src
+python -u server.py --device=0 --weights=../coco80.pt --conf-thres=0.5 --port=5000
+
+# Test
+python client_demo.py
+```

docker/Dockerfile_cuda_10.2 renamed to base_image/Dockerfile

@@ -2,26 +2,23 @@ FROM nvcr.io/nvidia/pytorch:19.11-py3
 
 USER root
 ENV DEBIAN_FRONTEND noninteractive
-RUN sed -i s@/archive.ubuntu.com/@/mirrors.aliyun.com/@g /etc/apt/sources.list
-RUN apt-get clean && apt-get update && apt-get install -y zip htop screen libgl1-mesa-glx net-tools lrzsz
+RUN apt-get clean && \
+    apt-get update && \
+    apt-get install -y zip htop screen libgl1-mesa-glx net-tools lrzsz
 
-RUN pip uninstall torch torchtext torchvision --y	
-COPY pip.conf /etc/pip.conf
+RUN pip uninstall torch torchtext torchvision --y
 RUN pip install seaborn thop torch torchvision torchaudio
 
 RUN git clone https://github.com/JunnYu/mish-cuda
-RUN git clone https://github.com/fbcotter/pytorch_wavelets
-
 RUN cd mish-cuda && python setup.py build install --record mish-install.log
+
+RUN git clone https://github.com/fbcotter/pytorch_wavelets
 RUN cd pytorch_wavelets && pip install .
 
 WORKDIR /home
 
 ENV PATH="/home/.local/bin:${PATH}"
 
-#USER root
 RUN mkdir /logs && chmod -R 777 /logs
 
-# Set a fixed model cache directory.
 ENV FVCORE_CACHE="/tmp"
-