This project aims to create an object detection model capable of automatically detecting advertsiment on images.
Dataset available in: https://mekabytes.com/dataset/info/billboards-signs-and-branding
Authors:
- Julio Oliveira
- Jordan Farrel
├── LICENSE
├── README.md <- The top-level README for developers using this project.
├── data
│ ├── annotations <- Annotations.
│ └── images <- The original images.
│
├── models <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
│ the creator's initials, and a short `-` delimited description, e.g.
│ `1.0-jqp-initial-data-exploration`.
│
├── references <- Data dictionaries, manuals, and all other explanatory materials.
│
├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
├── src <- Source code for use in this project.
├── __init__.py <- Makes src a Python module
│
├── dataset <- Datasets classes
│ └── ads_dataset.py
│
├── predict_model.py
└── train_model.py
References:
https://www.kaggle.com/ipythonx/keras-global-wheat-detection-with-mask-rcnn/notebook