CHAMASIFIER a.k.a CHA-kka MA-nga clas-SIFIER is a machine learning project which can identify the two of the fruits 'Chacka' and 'Manga'(JackFruit and Mango).The ML algorithm used here is Convolutional Neural Network. This algorithm can classify images based on the features.Tensorflow library is used here for the purpose of creation,training and testing of the model.For the website implementation we used the flask library of python.
The main features of Chamasifier are,
- Trained with over 600 images,
- has an accuracy of ~0.7,
- it has 3 convolution layers and 3 pooling layers,
- 2 dense hidden layers,
- rmsprop optimization.
BFH/recVTOJ0fhTpNx2Tm/2021
Chamasifer uses CNN(convolutional neural network) to do images recognition, images classifications. CNN image classifications takes an input image, process it and classify it under certain categories. The four steps for building a CNN model are convolution, max pooling, flattening, full connection. Convolution is the first layer to extract features from an input image. This layer preserves the relationship between pixels. Then the Pooling layers section would reduce the number of parameters when the images are too large. Flattening is converts the data into a 1-dimensional array for inputting it to the next layer. Max pooling takes the largest element from the rectified feature map.
The various libraries used in the project are listed in the requirements.txt file.
Python and pip should be installed in the system. Can be installed by using
sudo apt install python python-pip
Other requirements are written in the requirements.txt file. It can be installed using
pip install -r requirements.txt
- Open Chamasifier
- Upload the picture of a jackfruit or a mango.
- Get the result, it's as simple as that
