Image Classification Guide

Welcome to the Image Classification Guide! This section will provide you with comprehensive information about the image classification capabilities of our AI Toolkit.

Overview

Image classification is the process of assigning a label to an image based on its content. It is a fundamental task in computer vision and has numerous applications, such as object detection, medical imaging, and content moderation.

Getting Started

Before you begin, make sure you have the AI Toolkit installed. If not, you can download it from our website.

Prerequisites

Basic understanding of Python
Familiarity with machine learning concepts

Installation

To install the AI Toolkit, run the following command in your terminal:

pip install ai_toolkit

Quick Start

Here's a simple example of how to perform image classification using the AI Toolkit:

from ai_toolkit.image_classification import ImageClassifier

# Initialize the classifier
classifier = ImageClassifier()

# Load an image
image_path = "path/to/your/image.jpg"
image = load_image(image_path)

# Classify the image
label = classifier.classify(image)

# Print the label
print(label)

Models

The AI Toolkit provides various pre-trained models for image classification. You can choose from models like ResNet, Inception, and MobileNet.

ResNet

ResNet is a deep convolutional neural network architecture known for its ability to achieve high accuracy on image classification tasks.

from ai_toolkit.image_classification import ResNetClassifier

# Initialize the ResNet classifier
resnet_classifier = ResNetClassifier()

# Load an image
image_path = "path/to/your/image.jpg"
image = load_image(image_path)

# Classify the image
label = resnet_classifier.classify(image)

# Print the label
print(label)

Inception

Inception is another popular model for image classification. It uses a combination of convolutional and pooling layers to achieve high accuracy.

from ai_toolkit.image_classification import InceptionClassifier

# Initialize the Inception classifier
inception_classifier = InceptionClassifier()

# Load an image
image_path = "path/to/your/image.jpg"
image = load_image(image_path)

# Classify the image
label = inception_classifier.classify(image)

# Print the label
print(label)

MobileNet

MobileNet is a lightweight model designed for mobile and edge devices. It provides a good balance between accuracy and speed.

from ai_toolkit.image_classification import MobileNetClassifier

# Initialize the MobileNet classifier
mobilenet_classifier = MobileNetClassifier()

# Load an image
image_path = "path/to/your/image.jpg"
image = load_image(image_path)

# Classify the image
label = mobilenet_classifier.classify(image)

# Print the label
print(label)