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ad-block-real-world

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

Project Organization

├── 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

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