# raccoon_dataset

**Repository Path**: eqlmap/raccoon_dataset

## Basic Information

- **Project Name**: raccoon_dataset
- **Description**: The dataset is used to train my own raccoon detector and I blogged about it on Medium
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-11-05
- **Last Updated**: 2021-11-02

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Raccoon Detector Dataset

This is a dataset that I collected to train my own Raccoon detector with [TensorFlow's Object Detection API](https://github.com/tensorflow/models/tree/master/research/object_detection). Images are from Google and Pixabay. In total, there are 200 images (160 are used for training and 40 for validation).

## Getting Started

##### Folder Structure:
```
+ annotations: contains the xml files in PASCAL VOC format
+ data: contains the input file for the TF object detection API and the label files (csv)
+ images: contains the image data in jpg format
+ training: contains the pipeline configuration file, frozen model and labelmap
- a few handy scripts: generate_tfrecord.py is used to generate the input files
for the TF API and xml_to_csv.py is used to convert the xml files into one csv
- a few jupyter notebooks: draw boxes is used to plot some of the data and
split labels is used to split the full labels into train and test labels
```

## Copyright

See [LICENSE](LICENSE) for details.
Copyright (c) 2017 [Dat Tran](http://www.dat-tran.com/).