Pokedex

Pokedex it's a artificial intelligence that has as goal recognizing some pokemons images.

This is a project that was developed for Inteligência Artificial course from UFCG

---

Usage

• The model produced can classify seven pokemons, which are: pikachu, charmander, squirtle, bulbasaur, cyndaquil, totodile and chikorita.
• The searchimages package has some scripts that can be used for collecting images for the dataset.
• Since the trained model is too big for a commit , it will be find on google drive.
• The model was trained with a dataset of about 8490 images.
• Trained model

Set up

Creating the virtual environment

$ python -m venv pokevenv

Install dependencies

$ pip install -r requirements.txt

Activating virtual envrionment

$ . pokevenv/bin/activate

Using

To classify images

$ python3 classifier.py --model path_to_pokedex.model --labelbin lb.pickle --image examples/pikachu1.jpeg

To train a new model

$ python3 train.py --dataset path_to_dataset --model path_to_pokedex.model --labelbin lb.pickle

For more details about the arguments

$ python3 classifier.py --help

$ python3 train.py --help

---

Results

Graphics

• This is the graphic of the first model that was trained.

• This is the graphic of the last model that was trained; this one had a bigger dataset.

---

Classification

• Here there are some examples of successful images classification
• There are more examples of classification in examples package
• Pikachu
• Charmander
• Bulbasaur
• Squirtle
• Cyndaquil
• Chikorita
• Totodile

---

Built with

• Keras
• Tensorflow as Keras backend
• Sklearn
• OpenCV