Oil-and-gas-pipeline-leakage

Randonmly generated data without corrosion defect.
Used data.csv for Polynomial and linear regression - polynomial regression.ipynb
Randomly generated fake_data2.csv in new.py without "CR-corrosion defect" feature.
Predicted "CR-corrosion defect" feature for fake_data2.csv using the .ipnyb above.
Final dataset is called generated_data.csv
Created a python script for the model - digitalModel.py
Created a physical model data with 50 data points- stream.csv
Created an endpoint for the model - app.py
Created an endpoint streaming to the digital model to -app2.py (http://127.0.0.1:5001/)

To get a feel and for the values to output in mm:

Name		Name	Last commit message	Last commit date
Latest commit History 25 Commits
.ipynb_checkpoints		.ipynb_checkpoints
.vscode		.vscode
Data		Data
__pycache__		__pycache__
static/css		static/css
templates		templates
Digital Model-short-data.ipynb		Digital Model-short-data.ipynb
Digital Model-with crossval score.ipynb		Digital Model-with crossval score.ipynb
Digital Model.ipynb		Digital Model.ipynb
DigitalModelClass.py		DigitalModelClass.py
README.md		README.md
app.py		app.py
app2.py		app2.py
app_1.py		app_1.py
app_2.py		app_2.py
dataGenerate.py		dataGenerate.py
dataGenerate2.py		dataGenerate2.py
digitalModel.py		digitalModel.py
digital_model.pkl		digital_model.pkl
digital_model_class.pkl		digital_model_class.pkl
generated_dataset.csv		generated_dataset.csv
polynomial regression.ipynb		polynomial regression.ipynb
requirements.txt		requirements.txt
stream.csv		stream.csv