Think Different

  unplush Building a CNN model for object detection is a complex task that requires extensive knowledge of deep learning concepts, computer vision, and programming. So, I will provide you with a brief overview of the process and sample code to get you started. You will also need to have a basic understanding of Python, TensorFlow, Keras, and OpenCV. Before we start, let’s go through the steps involved in building an object detection model: Data collection: Collect a dataset of images with solar panels in different conditions (dust or clean). Data preprocessing: Preprocess the images to prepare them for training. This includes resizing the images, normalizing the pixel values, and splitting the data into training and validation sets. Model selection: Select a suitable model for the task. In this case, we will use VGG16, InceptionV3, Resnet50, and AlexNet. Model training: Train the selected model on the preprocessed data. Model evaluation: Evaluate the model’s performance on the vali...