A Flask application to manually label an existing dataset.
You want to create a training dataset for your next model. You have your assets/cars.csv
with already several fields:
Car;MPG;Cylinders;Displacement;Horsepower;Weight;Acceleration;Model;Origin
On top of these, you want to add a custom field with a special value that actually, just a human can set.
For example: Good_Looking
, with two possible values Yes
and Ǹo
.
The objective is to go through a maximum of dataset rows and set this value.
Iterating manually over the CSV file is not the more efficient way to do it.
With this project, you define the label settings and the labelling interface appearance and quickier your manual labelling.
Update the config.json
file to configure project.
{
"data": {
"input": "assets/cars.csv",
"output": "assets/labelled_cars.csv",
"delimiter": ";"
},
"interface": {
"fields": ["Car", "Model", "Origin"],
"theme": "light"
},
"label": {
"name": "Good_Looking",
"values": ["Yes", "No"]
}
}
- Installing virtual environment:
python3 -m pip install --user virtualenv
python3 -m venv env
source env/bin/activate
- Installing dependencies:
make
- Starting project:
make run
Labelling interface now available at http://127.0.0.1:5000
.
- Fix setuptools configuration;
- Replace with Poetry?
- Improve CI (linting, etc.);
- Setup release flow;
- Implement skip button;
- Local Bootstrap.