InsectsRecognition

About   |   Data   |   Content   |   Technologies   |   Requirements   |   Starting   |   License   |   Author

🎯 About

There are 5 type of insects in the dataset, that is Butterfly, Dragonfly, Grasshoper, Ladybug, and Mosquito. The goal is to differenciate the images of each insect using machine learning. In this project we use Tensorflow and Keras to make a Sequential Deep Learning. We are using two kind of Deep Learning model, Mark1 and Mark2. Mark 1 is a complex layered model with 6 Million trainable parameters. Mark2 is fast Deep Learning model with 4 Million trainable parameters.

📰 Data

The original data came from Kaggle but I have already clean the data and sort the Training , Val and Testing Data at GDrive.

The dataset is a group of jpeg files, so its is easier to deal with the datatype as all of the pictures are in one uniform datatype. the size of each picture is 150 x 150.

✨ Content

✔️ Mark1 Model (code);

✔️ Mark1 Model (visuallize);

✔️ Mark2 Model (code);

✔️ Mark2 Model (visuallize);

✔️ Training State;

✔️ Predictor Demo;

🚀 Technologies

The following tools were used in this project:

• Python
• Tensorflow

✅ Requirements

Before starting 🏁, you need to have Git and Pip installed.

🏁 Starting

# Clone this project
$ git clone https://github.com/ariffrahimin/insectsrecognition

$ cd insectsrecognition

$ pip install -r requirements.txt
# if not working try run "pip3 install -r requirements.txt"

$ python predictor.py

📝 License

This project is under license from MIT. For more details, see the LICENSE file.

Made with ❤️ by ARIFF RAHIMIN BIN MOHAMED NORAZMAN

 

Back to top