Docker & CI/CD Pipeline Added

.github/workflows/main.yaml

@@ -0,0 +1,98 @@
+name: workflow
+
+on:
+  push:
+    branches:
+      - main
+    paths-ignore:
+      - 'README.md'
+
+permissions:
+  id-token: write
+  contents: read
+
+jobs:
+  integration:
+    name: Continuous Integration
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout Code
+        uses: actions/checkout@v3
+
+      - name: Lint code
+        run: echo "Linting repository"
+
+      - name: Run unit tests
+        run: echo "Running unit tests"
+
+  build-and-push-ecr-image:
+    name: Continuous Delivery
+    needs: integration
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout Code
+        uses: actions/checkout@v3
+
+      - name: Install Utilities
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y jq unzip
+      - name: Configure AWS credentials
+        uses: aws-actions/configure-aws-credentials@v1
+        with:
+          aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
+          aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
+          aws-region: ${{ secrets.AWS_REGION }}
+
+      - name: Login to Amazon ECR
+        id: login-ecr
+        uses: aws-actions/amazon-ecr-login@v1
+
+      - name: Build, tag, and push image to Amazon ECR
+        id: build-image
+        env:
+          ECR_REGISTRY: ${{ steps.login-ecr.outputs.registry }}
+          ECR_REPOSITORY: ${{ secrets.ECR_REPOSITORY_NAME }}
+          IMAGE_TAG: latest
+        run: |
+          # Build a docker container and
+          # push it to ECR so that it can
+          # be deployed to ECS.
+          docker build -t $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG .
+          docker push $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG
+          echo "::set-output name=image::$ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG"
+          
+          
+  Continuous-Deployment:
+    needs: build-and-push-ecr-image
+    runs-on: self-hosted
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v3
+
+      - name: Configure AWS credentials
+        uses: aws-actions/configure-aws-credentials@v1
+        with:
+          aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
+          aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
+          aws-region: ${{ secrets.AWS_REGION }}
+
+      - name: Login to Amazon ECR
+        id: login-ecr
+        uses: aws-actions/amazon-ecr-login@v1
+
+
+      - name: Pull latest images
+        run: |
+         docker pull ${{secrets.AWS_ECR_LOGIN_URI}}/${{ secrets.ECR_REPOSITORY_NAME }}:latest
+         
+      # - name: Stop and remove  container if running
+      #   run: |
+      #    docker ps -q --filter "name=waste-detection" | grep -q . && docker stop waste-detection && docker rm -fv waste-detection
+
+      - name: Run Docker Image to serve users
+        run: |
+         docker run -d -p 8080:8080 --ipc="host" --name=waste-detection -e 'AWS_ACCESS_KEY_ID=${{ secrets.AWS_ACCESS_KEY_ID }}' -e 'AWS_SECRET_ACCESS_KEY=${{ secrets.AWS_SECRET_ACCESS_KEY }}' -e 'AWS_REGION=${{ secrets.AWS_REGION }}'  ${{secrets.AWS_ECR_LOGIN_URI}}/${{ secrets.ECR_REPOSITORY_NAME }}:latest
+      - name: Clean previous images and containers
+        run: |
+         docker system prune -f

Dockerfile

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+FROM python:3.10-slim-buster
+
+WORKDIR /app
+COPY . /app
+
+RUN apt update -y && apt install awscli -y
+
+RUN apt-get update && apt-get install ffmpeg libsm6 libxext6 unzip -y && pip install -r requirements.txt
+
+CMD ["python3", "app.py"]

README.md

@@ -1 +1,140 @@
-# waste-detection-using-yoloV5
+# Waste Detection using yoloV5
+
+## Workflows
+
+1. Update config.yaml
+2. Update secrets.yaml [Optional]
+3. Update params.yaml
+4. Update the entity
+5. Update the configuration manager in src config
+6. Update the components
+7. Update the pipeline
+
+
+## Dataset
+
+* Here, I have used [this](https://drive.google.com/file/d/1YBtZfdYtJ341DJ51JJFA8iOrHC4A9b22/view?usp=sharing) waste detection dataset. You can use your own dataset. Just place the URL of the dataset in `config/config.yaml/data_ingestion/source_URL`
+
+## Steps to run
+
+### STEP 00 : Clone the repository
+
+```bash
+https://github.com/utpal108/waste-detection-using-yoloV5
+```
+### STEP 01 : Create a virtial environment after opening the repository
+
+Using Anaconda Virtual Environments
+
+```bash
+conda create -n venv python=3.10 -y
+conda activate venv
+```
+Or for Linux operating system, you can use that
+
+```bash
+python3.10 -m venv venv
+source venv/bin/activate
+```
+
+
+### STEP 02 : install the requirements
+```bash
+pip install -r requirements.txt
+```
+
+Finally, run the following command to run your application:
+```bash
+python app.py
+```
+
+### STEP 03 : run the application
+
+Now,open up your local host with a port like that on your web browser.
+```bash
+http://localhost:8080
+```
+### STEP 04 : train the model
+Before predicting, you have to train your model with your own dataset.
+```bash
+http://localhost:8080/train
+```
+After completing the training, you can now detect waste from any image or live video.
+
+To detect waste from any live video, you have to follow this URL
+```bash
+http://localhost:8080/live
+```
+
+## AWS-CICD-Deployment-with-Github-Actions
+
+### STEP 00 : Login to AWS console.
+
+### STEP 01 : Create IAM user for deployment
+
+	#with specific access
+
+	1. EC2 access : It is virtual machine
+
+	2. ECR: Elastic Container registry to save your docker image in aws
+
+
+	#Description: About the deployment
+
+	1. Build docker image of the source code
+
+	2. Push your docker image to ECR
+
+	3. Launch Your EC2 
+
+	4. Pull Your image from ECR in EC2
+
+	5. Lauch your docker image in EC2
+
+	#Policy:
+
+	1. AmazonEC2ContainerRegistryFullAccess
+
+	2. AmazonEC2FullAccess
+
+
+### STEP 02 : Create ECR repo to store/save docker image
+    - Save the URI: 681776806933.dkr.ecr.us-east-2.amazonaws.com/waste-detection
+
+
+### STEP 03 : Create EC2 machine (Ubuntu) 
+
+### STEP 04 : Open EC2 and Install docker in EC2 Machine:
+
+
+	#optinal
+
+	sudo apt-get update -y
+
+	sudo apt-get upgrade
+
+	#required
+
+	curl -fsSL https://get.docker.com -o get-docker.sh
+
+	sudo sh get-docker.sh
+
+	sudo usermod -aG docker ubuntu
+
+	newgrp docker
+
+### STEP 05 : Configure EC2 as self-hosted runner:
+    setting>actions>runner>new self hosted runner> choose os> then run command one by one
+
+
+### STEP 06 : Setup github secrets:
+
+    AWS_ACCESS_KEY_ID=
+
+    AWS_SECRET_ACCESS_KEY=
+
+    AWS_REGION = us-east-2
+
+    AWS_ECR_LOGIN_URI = demo>>  681776806933.dkr.ecr.us-east-2.amazonaws.com
+
+    ECR_REPOSITORY_NAME = waste-detection