Git client vs Notate ML

Access Git repositories on the go. Clone, edit, commit and push while allowing other apps access to repositories. Git is a important part of our work-life and iOS can take part in this. The ability to commit even when offline has added utility on a device that moves in and out of network coverage. Cloning repositories gets you a local copy on your iOS device with commits for all branches. You can browse the content from within the app and make changes. Other applications supporting the Files app, WebDAV or x-callback-url has access to these files. Changes made can be committed and the commits can in turn be pushed back to the remote. The idea of doing significant programming on iOS might seem far fetched when you are used to a large screen, a physical keyboard and a full IDE. But just as it turned out that not every email is serious prose, then not everything that goes on in Git is significant programming. Sometimes you just want to update a TODO file or make adjustments to your Jekyll site. Sometimes you just need to add a file the designer sent after hours. If you ever make reminders about small things to do with the code-base, then you should give Working Copy a try. You will spend less time moving stuff around and you will get much better commit messages when you write them for fixes that are still fresh in your mind. You won't be leaving your computer behind any time soon, but sometimes it is faster to just fix things with the device in your hand. When you do need to perform real work on iOS, Working Copy is a powerful tool. Editor has syntax highlighting for more than 50 programming languages and a built-in color picker. Preview images, Markdown and HTML files with a Javascript console pointing to errors in your code. Create new branches and merge or rebase them back, with a brilliant merge-tool for handling conflicts. If you need to automate your work there are Working Copy actions in the Shortcuts app for most operations. Even if you never edit a line of code on iOS, Working Copy is a great companion for reviewing and discussing code. Repositories are cross indexed and with powerful fuzzy search you can quickly jump from a symbol to the declaration or reverse from the declaration to all usages. A graph of your commits lets you zoom out for a overview of the commit tree or zoom in for specifics about each commit, with speed and beauty you won’t find in desktop Git applications. Review the changes your files have gone through with a diff viewer that is great for text and images. There is even hex-dump mode for that obscure occasion. Working Copy is a free download but you need to unlock pro features such as the ability to push commits and manage more than 5 repositories. There is no venture capital, large company or ads funding development and your support through in-app purchase directly sustains development. Try out pro features with a 10 day free trial. When you pay to unlock you get permanent access to all pro features at the time of purchase as well as any added the next year. When 12 months have passed you keep all existing pro features but any new ones introduced are locked until you renew your unlock.

Preparing input image datasets is a critical and challenging task in any Machine Learning project.  Notate ML brings the power and usability of Apple's mobile devices to accelerate this task and deliver higher quality training data to your object detection model. FEATURES ・Create a dataset, type, scan, or speak your labels into it ・Snap new pictures, or import old ones from your photo library ・Crop images, draw bounding boxes, tag and label objects of interest ・Export images and annotations for training with YOLO, Apple Create ML, or Google Auto ML CREATING A DATASET ・Create a new data set and give it a unique name ・Add labels in one of several ways: ・One at a time, using the keyboard ・Copy and paste a comma-separated list from another document ・Scan from a physical text source ・Use the device voice feature to speak them in ・Labels can be edited or deleted by swiping left on each row ・Only unused labels can be deleted IMPORTING IMAGES ・Tap into the dataset and import photos (up to 50 at a time) from your Photo Library ・This app can only access photos that you select using Apple's photo picker feature CAPTURING IMAGES FROM THE CAMERA ・While browsing the images in a dataset, tap the "Capture" button to snap new images with the camera ・The app will require your permission to access the camera ・If you choose to decline, you can always grant access at a later date using "Settings" ANNOTATING THE IMAGE ・Select an image from the dataset image browser to annotate it ZOOMING and CROPPING ・Pinch with two fingers to zoom in or out of the image ・Drag with two fingers to move (pan) the image about ・Optionally crop the image to the visible square dimensions ・Cropping can only be done when the image has no bounding boxes. ・Double tap on the image to reset zoom and recenter the image ・Tap the "Reset" button in the bottom panel to restore image and annotations to the original state before editing ・The cropped image dimensions and visible area dimensions in pixels are displayed above the image at all times TAGGING ・Drag with one finger or stylus to draw bounding boxes around objects of interest ・Long press on a box to select an existing annotation ・Use the picker to assign a label to the selected bounding box ・Or tap the red Delete button to remove the selected box ・Tap anywhere outside the selected box to unselect it ・Tap the "Reset" button to restore image and annotations to the original state before editing ・Tap the "Done" button to complete annotating the image EXPORTING THE DATASET ・While browsing dataset images, tap the "Export" button, to select export options ・Datasets can be exported in one of three "schemas" for use with different object detector training frameworks ・The YOLO schema generates a set of files organized for use with the YOLO framework ・The Create ML schema generates files to use as input to Apple's Create ML application ・The Auto ML schema generates files to use as input to Google's Auto ML service ・ After reviewing the export options, tap the "Export" button on the Export options screen to generate data files for training ・ Choose one of the sharing options (e.g. Airdrop, Files) enabled by your device to export the data files DELETING ・Delete an image by swiping left in the dataset image browser ・Delete an entire dataset by swiping left in the dataset browser ・If a dataset contains images, you will be prompted for confirmation Some tips ・Crop the images before tagging them ・Use a stylus for more accurate bounding boxes ・Maintain different datasets for training and validation ・Limit datasets to under 1000 images each, for ease of use ・Export and delete unused datasets to conserve storage