ML Image Identifier Lite vs Postcard

FEATURES: ML Image Identifier is an educational app that allows your iOS device to identify images in real-time, as you move the camera around your environment. It can scan for 3 categories of images ("Objects", "Cars", and "Food") and recognize "Text" (character boxes, OCR) and "Faces" (feature landmarks). The app automatically throttles the image processing to work on any device running iOS 12, though it may be sluggish on older devices. Devices running iOS 13 additionally have optical character-recognition (OCR) in "Text" mode. For the categorized images, the app displays the top-5 predicted matches, based on the neural networks' confidence levels as percentages. BACKGROUND: Once merely a subject of science-fiction, machine learning has permeated our lives in recent decades. We see it in numerous uses, such as handwriting recognition, facial recognition, image tagging, AI in games, targeted advertisements, predictive typing, and many automated tasks. Social networks are free because the data (i.e. text, images, survey responses, etc.) you provide can be valuable for numerous purposes. In short: Knowledge is power. With the release of iOS 11, Apple brought machine learning to the masses with CoreML, making it possible to run neural networks and other ML-related tools via hardware acceleration on any iOS device. This app is a demonstration of some possibilities - and some deficiencies - of machine learning. Modeling a neural network is only one part of the task. For a ML model to work, it must be fed massive amounts of test data (similarly to how it takes a living creature numerous stimuli to learn). Good test data can yield good results; poor test data can yield poor results. Sometimes, biases of those creating the tests can come into play, since they may unknowingly weigh certain test values over others. SPECIFICS: ML Image Identifier makes use of 3 ML models (all MIT- or Apache- licensed) and Apple's own Vision framework to serve as examples: "MobileNet" - This scans general objects. It works fairly well with household items. It cannot identify people. This ML model is an example of fairly high-quality results in image recognition and is much more compact than similar ML models that can be as large as 500MB. "CarRecognition" - This scans for makes and models of vehicles. It is very hit-or-miss and seems to heavily match automobiles from specific regions of the world. Most matches are the right body type but wrong make. This ML model is an example of mixed results in image recognition. "Food101" - This scans for prepared foods. It rarely works with general food items and seems to focus on foods that most people will not have in their houses, such as caviar and lobster. It also returns many false-positives for desserts. This ML model is an example of poor results in image recognition when used outside of very specific cases. The text-recognition mode looks for all potential text in view and highlights the words and individual characters in those words for easy viewing. It also supports OCR on iOS13. The facial-recognition mode looks for all potential human or human-like faces. Of those found, the app highlights the facial landmarks, such as eyes, nose, jawline, etc. This mode in particular works better on a newer device at a usable framerate, due to the hardware required for real-time image processing. If you enjoy this app, please consider ad-free version. If you enjoy the facial-recognition, consider HullBreach Studios' game "Exprestive", which is also available in the App Store.

Postcard Keeper turns the shoebox under your bed into a beautiful, private collection that lives quietly in your iCloud. Snap the front and back of every postcard, tag it with the contact who sent or received it, and Postcard Keeper organizes everything for you. Postmarks become pins on a world map. Your address book grows with the people you exchange mail with. Statistics let you see how far your collection has traveled. KEY FEATURES • Built-in scanner — capture the front and back of each postcard with corner-by-corner cropping and automatic perspective correction. • Private by default — every postcard, contact, and note lives in your own iCloud account. We never see your data. • Searchable backs — Postcard Keeper reads the handwritten and printed text on the back of each postcard using on-device text recognition, so a search for "Lisbon" finds the postcard whose note mentions Lisbon. • A world map of your postmarks — every received postcard with a postmark becomes a pin you can explore. • Address book built in — track names, postal addresses, Reddit usernames, and Postcrossing usernames. Import directly from your phone's Contacts. • Tags and filters — organize by year, country, sent vs. received, or any tag you choose. • Shareable gallery — opt in to a public iCloud link that shares only the fronts of the postcards you choose. Back images, notes, and contact info always stay private. • Stats and history — see how many postcards you've collected, how many countries they've come from, and who you've exchanged the most with. • Export to PDF — generate a printable album of your entire collection in one tap. PLANS Postcard Keeper is free for up to 25 postcards. Two optional subscriptions unlock larger collections: • Plus — $0.99/month, up to 200 postcards • Unlimited — $1.99/month, no limit Subscriptions auto-renew monthly via your Apple ID and can be canceled anytime in iOS Settings. EULA: https://www.apple.com/legal/internet-services/itunes/dev/stdeula/