Image Classification: Step-by-step Classifying Images with Python and Techniques of Computer Vision and Machine Learning

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ASIN ‏ : ‎ B07NKT94GV
Publisher ‏ : ‎ M.J. Magic Publishing; 1st edition (February 9, 2019)
Publication date ‏ : ‎ February 9, 2019
Language ‏ : ‎ English
File size ‏ : ‎ 4207 KB
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Format ‏ : ‎ Print Replica

Image Classification: Step-by-step Classifying Images with Python and Techniques of Computer Vision and Machine Learning

In this post, we will explore the process of image classification using Python and popular techniques of computer vision and machine learning. Image classification is the task of assigning a label or category to an image based on its content. This task is commonly used in various fields such as healthcare, autonomous driving, and security.

To classify images, we will be using the following steps:

1. Data Collection: The first step in image classification is to gather a dataset of images that are labeled with their corresponding categories. This dataset will be used to train our machine learning model.

2. Data Preprocessing: Before feeding the images into the model, we need to preprocess them by resizing, normalizing, and augmenting the data to improve the model’s performance.

3. Model Building: We will build a convolutional neural network (CNN) using popular libraries such as TensorFlow or PyTorch. CNNs are widely used in image classification tasks due to their ability to learn spatial hierarchies of features.

4. Model Training: We will train the CNN model on our dataset using techniques such as backpropagation and stochastic gradient descent to optimize the model’s parameters.

5. Model Evaluation: Once the model is trained, we will evaluate its performance on a separate test dataset to measure its accuracy, precision, recall, and F1 score.

6. Prediction: Finally, we will use the trained model to classify new images and make predictions on their categories.

By following these steps and utilizing the power of computer vision and machine learning techniques, we can successfully classify images with Python. Stay tuned for the upcoming tutorials where we will dive deeper into each of these steps and provide code examples to help you get started with image classification.
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