AI-ObjectDetection

Artificial Intelligence Project Object Detection Using Artificial Neural Network

• Object detection is an important computer vision task used to detect instances of visual objects of certain classes (for example, humans, animals, cars, or buildings) in digital images such as photos or video frames.

• it classifies image into one of the ten given classes.

• our project detect ten type of clothes ( -T-shirt/top ,Trouser, Pullover, Dress, Coat,Sandal ,Shirt, Sneaker, Bag, Ankle boot)

DataSet Description

Fashion-MNIST is a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes.

DataSet link : https://www.kaggle.com/datasets/zalando-research/fashionmnist

Development platforms

Tools Colab

Languages : Python

Used Libraries : Pandas Numpy matplotlib OS glob CV2 Keras Tensorflow Sklearn Seaborn

Advantages of Model

• Detect many types of clothes

• Good overall accuracy 86%

• Less than 1 second to detect object

• Few times training

DisAdvantages of model

-detect only one object