Pixel Gen vs Vision Detector

This app will generate random images using Perlin Noise based on parameters you provide. You can save the images.

Vision Detector is an AI image analysis tool that supports CoreML machine learning models, multi-modal Large Language Models, and on-device Apple Intelligence. Choose the mode that best fits your use case. You can choose one of the following image input sources: - Live video by the built-in camera - Still image by the built-in camera - Photo Library - Files (iCloud, Google Drive, Dropbox, etc.) For live video inputs, continuous inference is performed on the camera feed. However, the frame rate and other parameters depend on the device. # Notification Center Vision Detector can call Notification Center for predefined conditions. Broadcasting notifications sends notifications to all Apple devices signed in with the same Apple Account. ## CoreML Mode Vision Detector locally executes CoreML models using Apple’s Vision framework. Before using this mode, prepare a machine learning model in the CoreML format (.mlmodel or .mlpackage) using Create ML. Import ML models via iCloud or AirDrop. Vision Detector supports the following types of CoreML models: - Image classification - Object detection - Object Segmentation - Style transfer Built-in Vision framework is also available for human mask and image classification. ## Vision LLM Mode Vision Detector can use multi-modal large language model (LLMs). Define what to do with the prompt as follows: - If the image is a screenshot, answer the name of the software - Call a notification when you see a cat - Count the number of persons in the image, and notify when it changes ## Apple Intelligence mode The images are completely processed on your device locally with your prompt.