from imageai.Prediction.Custom import CustomImagePrediction import os. The code above imports the ImageAI library for custom image prediction and the python os class. execution_path = os.getcwd() The ...

This project is an end-to-end solution for classifying images from the CIFAR-10 dataset. It includes a Python-based Jupyter notebook for training and saving the model, and a Streamlit app for ...

The ImageNet dataset contains 3.2 million labeled images, organized in 12 subtrees and 5247 synsets in total, with an average of 600 images per synset, making it one of the largest publicly available ...

Defect prediction has been a popular research topic where machine learning (ML) and deep learning (DL) have found numerous applications. However, these ML/DL-based defect prediction models are often ...

The availability of large volumes of data is a key requirement in the development of efficient, robust, and advanced machine learning based prediction models. This paper introduces the ImageNet ...

In this article, I’ll be discussing how to create an image dataset as well as label it using python. For creating an image dataset, we need to acquire images by web scraping or better to say image ...