Dataset HydroFarm

The dataset contains images categorized into sehat and tidak sehat , organized into train , test , and validation folders, each with subfolders for each class ( /sehat and /tidak sehat ). Images are in JPEG or PNG format with a recommended resolution of 240x240 pixels, suitable for the VGG16 model’s input requirements. The dataset is intended for deep learning applications, viewable with standard image viewers, and executable with Python, particularly using TensorFlow and Keras . To access and run the VGG16 model, Google Colab or Jupyter Notebook can be used for cloud. For processing, an image data generator is set up to normalize the images, while VGG16 (with pre-trained ImageNet weights) serves as the base model with added dense layers for binary classification between sehat and tidak sehat . The model can then be compiled with an optimizer (e.g., Adam) and trained on the data with appropriate evaluation on validation and test sets.