From d42fd9f8d2295e76cbd0ca02a4169460c4bf9ab5 Mon Sep 17 00:00:00 2001 From: SathvikNayak123 Date: Thu, 29 Aug 2024 18:54:57 +0530 Subject: [PATCH] updated_readme --- README.md | 64 +++++++++++++- app.py | 19 ++-- dvc.lock | 24 ++--- inputImage.jpg | Bin 138291 -> 71299 bytes .../meta.yaml | 15 ---- .../metrics/accuracy | 1 - .../metrics/loss | 1 - .../params/AUGMENTATION | 1 - .../params/BATCH_SIZE | 1 - .../params/CLASSES | 1 - .../params/EPOCHS | 1 - .../params/IMAGE_SIZE | 1 - .../params/INCLUDE_TOP | 1 - .../params/LEARNING_RATE | 1 - .../params/WEIGHTS | 1 - .../tags/mlflow.log-model.history | 1 - .../tags/mlflow.runName | 1 - .../tags/mlflow.source.git.commit | 1 - .../tags/mlflow.source.name | 1 - .../tags/mlflow.source.type | 1 - .../tags/mlflow.user | 1 - mlruns/0/meta.yaml | 6 -- params.yaml | 4 +- requirements.txt | 8 +- scores.json | 4 +- static/dagshub.png | Bin 0 -> 106578 bytes static/flask_app.png | Bin 0 -> 234055 bytes static/mlflow.png | Bin 0 -> 127844 bytes templates/index.html | 16 ++-- workflow.md | 82 ++++++++++++++++++ 30 files changed, 187 insertions(+), 71 deletions(-) delete mode 100644 mlruns/0/cafde92fb561412baa32970f2d3fcc7d/meta.yaml delete mode 100644 mlruns/0/cafde92fb561412baa32970f2d3fcc7d/metrics/accuracy delete mode 100644 mlruns/0/cafde92fb561412baa32970f2d3fcc7d/metrics/loss delete mode 100644 mlruns/0/cafde92fb561412baa32970f2d3fcc7d/params/AUGMENTATION delete mode 100644 mlruns/0/cafde92fb561412baa32970f2d3fcc7d/params/BATCH_SIZE delete mode 100644 mlruns/0/cafde92fb561412baa32970f2d3fcc7d/params/CLASSES delete mode 100644 mlruns/0/cafde92fb561412baa32970f2d3fcc7d/params/EPOCHS delete mode 100644 mlruns/0/cafde92fb561412baa32970f2d3fcc7d/params/IMAGE_SIZE delete mode 100644 mlruns/0/cafde92fb561412baa32970f2d3fcc7d/params/INCLUDE_TOP delete mode 100644 mlruns/0/cafde92fb561412baa32970f2d3fcc7d/params/LEARNING_RATE delete mode 100644 mlruns/0/cafde92fb561412baa32970f2d3fcc7d/params/WEIGHTS delete mode 100644 mlruns/0/cafde92fb561412baa32970f2d3fcc7d/tags/mlflow.log-model.history delete mode 100644 mlruns/0/cafde92fb561412baa32970f2d3fcc7d/tags/mlflow.runName delete mode 100644 mlruns/0/cafde92fb561412baa32970f2d3fcc7d/tags/mlflow.source.git.commit delete mode 100644 mlruns/0/cafde92fb561412baa32970f2d3fcc7d/tags/mlflow.source.name delete mode 100644 mlruns/0/cafde92fb561412baa32970f2d3fcc7d/tags/mlflow.source.type delete mode 100644 mlruns/0/cafde92fb561412baa32970f2d3fcc7d/tags/mlflow.user delete mode 100644 mlruns/0/meta.yaml create mode 100644 static/dagshub.png create mode 100644 static/flask_app.png create mode 100644 static/mlflow.png create mode 100644 workflow.md diff --git a/README.md b/README.md index b8f399f..d2e8019 100644 --- a/README.md +++ b/README.md @@ -1 +1,63 @@ -# cancer-dl \ No newline at end of file +# cancer-dl + +# Chest Cancer Detection Using Deep Learning with MLOps + +This project focuses on detecting chest cancer from medical images using deep learning techniques. It integrates MLOps practices for robust and reproducible model development, deployment, and monitoring. + +## Project Overview + +- **Data Source**: Chest cancer images from Kaggle. +- **Model**: VGG16 with a transfer learning approach. +- **Processes**: + - **Data Ingestion**: Automated data ingestion pipeline. + - **Training**: Initial training of a base model and modification of the model for improved performance. + - **Evaluation**: Rigorous evaluation of model performance using various metrics. + - **Prediction**: Generation of predictions using the trained model. + +## MLOps Tools and Techniques + +- **MLflow**: Used for tracking experiments and hyperparameter tuning. + ![Hyperparameter Tuning with MLflow](static\mlflow.png) + +- **DAGsHub**: Visualized data pipeline for streamlined data processing and management. + ![Data Pipeline Display with DAGsHub](static\dagshub.png) + +- **DVC (Data Version Control)**: Implemented for data versioning to ensure reproducibility. + +- **Flask Application**: Built a web app to provide an interface for users to upload images and receive predictions. + ![Flask App Interface](static\flask_app.png) + +- **Docker**: Dockerized the application for consistent deployment across environments. + +- **GitHub Actions**: Implemented CI/CD pipelines for continuous integration and deployment. + +- **AWS**: Deployed the application on AWS for scalable access. + +## Getting Started + +To get started with this project, follow these steps: + +1. Clone the repository: + ```bash + git clone https://github.com/SathvikNayak123/cancer-dl.git + ``` +2. Install the necessary dependencies: + ```bash + pip install -r requirements.txt + ``` +3. Initialized DVC: + ```bash + dvc init + ``` +4. Run app + ```bash + python app.py + ``` + +## Deployment + +The model and application are deployed on AWS, ensuring scalability and high availability. +The deployment process is automated using Docker and GitHub Actions for seamless updates and maintenance. + +## P.S +For details about project and workflow and commands for AWS deployment, refer **worklow.md** \ No newline at end of file diff --git a/app.py b/app.py index d1ab5cb..2361bec 100644 --- a/app.py +++ b/app.py @@ -1,35 +1,36 @@ from flask import Flask, request, jsonify, render_template import os from flask_cors import CORS, cross_origin -from cnnClassifier.pipeline.predict import PredictionPipeline from cnnClassifier.utils.common import decodeImage +from cnnClassifier.pipeline.predict import PredictionPipeline - -os.environ['LANG'] = 'en_US.UTF-8' -os.environ['LC_ALL'] = 'en_US.UTF-8' +os.putenv('LANG', 'en_US.UTF-8') +os.putenv('LC_ALL', 'en_US.UTF-8') app = Flask(__name__) CORS(app) + class ClientApp: def __init__(self): self.filename = "inputImage.jpg" self.classifier = PredictionPipeline(self.filename) -clApp = ClientApp() @app.route("/", methods=['GET']) @cross_origin() def home(): return render_template('index.html') -@app.route("/train", methods=['GET', 'POST']) +@app.route("/train", methods=['GET','POST']) @cross_origin() def trainRoute(): - os.system("dvc repro") + os.system("python main.py") + # os.system("dvc repro") return "Training done successfully!" + @app.route("/predict", methods=['POST']) @cross_origin() def predictRoute(): @@ -39,5 +40,7 @@ def predictRoute(): return jsonify(result) + if __name__ == "__main__": - app.run(host='0.0.0.0', port=8080) + clApp = ClientApp() + app.run(host='0.0.0.0', port=8080) #for AWS diff --git a/dvc.lock b/dvc.lock index 7a06899..a24b574 100644 --- a/dvc.lock +++ b/dvc.lock @@ -36,13 +36,13 @@ stages: - 224 - 3 INCLUDE_TOP: false - LEARNING_RATE: 0.01 + LEARNING_RATE: 0.001 WEIGHTS: imagenet outs: - path: artifacts/prepare_base_model hash: md5 - md5: cfd2c0def201f160979a863fcdaf5c58.dir - size: 118054560 + md5: 7159acba305ef31d358d9ed3f146f526.dir + size: 118053368 nfiles: 2 training: cmd: python src/cnnClassifier/pipeline/stage03_training.py @@ -54,8 +54,8 @@ stages: nfiles: 485 - path: artifacts/prepare_base_model hash: md5 - md5: cfd2c0def201f160979a863fcdaf5c58.dir - size: 118054560 + md5: 7159acba305ef31d358d9ed3f146f526.dir + size: 118053368 nfiles: 2 - path: config/config.yaml hash: md5 @@ -69,7 +69,7 @@ stages: params.yaml: AUGMENTATION: true BATCH_SIZE: 16 - EPOCHS: 1 + EPOCHS: 20 IMAGE_SIZE: - 224 - 224 @@ -77,8 +77,8 @@ stages: outs: - path: artifacts/training/model.h5 hash: md5 - md5: c99218865b913c4c55239c5dc49b6748 - size: 59337520 + md5: 1a16e1f5ef6f389a3358067108ece334 + size: 59135136 evaluation: cmd: python src/cnnClassifier/pipeline/stage04_evalaution.py deps: @@ -89,8 +89,8 @@ stages: nfiles: 485 - path: artifacts/training/model.h5 hash: md5 - md5: c99218865b913c4c55239c5dc49b6748 - size: 59337520 + md5: 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