ShellHistory vs Vision Detector

ShellHistory for iPhone and iPad shows the shell history your Macs record with ShellHistory for Mac, synced through your private iCloud. It doesn't record commands itself. With ShellHistory you can: • Search your shell history, and filter it by shell, machine, session, directory, exit status or date. • See a command's details: when and where it ran, how it ended, how long it took, and every other run of it. • Explore how you work on the Statistics page: activity over time, success rate, exit codes and what they mean, your busiest hours and days, the slowest and most used commands, and your streak. • Keep the commands you need in notebooks, with placeholders like {{version}} filled in before you copy. • Have Apple Intelligence explain a command, on your device. • Find passwords, tokens and keys in your history and delete them on all your devices. • Search your history from Shortcuts, Spotlight and Siri. On iPad and the iPhone Duo, the history, a command's details and your notebooks fit side by side. Privacy Your history stays on your devices and in your private iCloud database, in encrypted fields. ShellHistory has no account and no servers of its own, and collects no data. ShellHistory is made by an independent developer. Questions, suggestions and bug reports: support@loshadki.app. Help: https://loshadki.app/shellhistory/

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.