AI Photo Enhancer Apps! Do They Work?!

The Edit Place
26 Feb 202309:23

TLDRIn this video, the host addresses skepticism about AI photo enhancer apps that claim to transform blurry or pixelated photos into sharp images. The host serves as a guinea pig, testing several apps including Vivid AI Photo Enhancer, Pixel Up, and Max Sharp AI. Using a set of photographs of his wife, Michelle, ranging from in-focus to completely out of focus, the host evaluates the effectiveness of each app. Surprisingly, some apps manage to add texture and detail to the photos, even restoring hair and facial features in out-of-focus shots. The Vivid app and Pixel Up app show the most promise, with the host recommending them for enhancing slightly out-of-focus photos. The video concludes with a caution against the overpriced subscription model of some apps and a suggestion to use such apps for enhancing old or important photos.

Takeaways

  • 🎯 The video discusses the skepticism around AI photo enhancer apps that claim to improve blurry or pixelated photos.
  • 📸 The creator tests several apps using a set of his wife's photos, including a perfectly sharp one, a softened one, and a completely out-of-focus one.
  • 💡 Vivid AI Photo Enhancer and Pixel Up are highlighted as effective apps that added texture and details to the photos, even to a technically sharp but softened image.
  • 🚀 The AI's ability to analyze and enhance photos was impressive, especially with a mid-focused photo, though it couldn't fully restore highly blurred images.
  • 💰 The apps are free to download but come with in-app purchases and subscription offers, which the creator finds excessive.
  • 📱 For slightly out-of-focus photos, the apps performed well, offering a viable solution for quick photo fixes on a mobile device.
  • 🤔 The creator is surprised by the results, as they exceeded his initial expectations, contrary to his skepticism about the apps' capabilities.
  • 🔍 Other apps like Pixel Map and Loopsy Enhance were tested, with mixed results; some offered similar quality enhancements, while others fell short.
  • 🚫 The Sharp AI Photo Enhancer, advertised on TikTok, was deemed the least effective and not worth the investment.
  • 📈 The pricing models of the apps were criticized, with the creator suggesting a one-time payment could be more acceptable than a yearly subscription.
  • 🌟 The video concludes with a recommendation to use Vivid or Pixel Up for photo enhancement needs, especially for those with slightly blurred photos.

Q & A

  • What is the main topic discussed in the video?

    -The main topic discussed in the video is the effectiveness of AI photo enhancer apps that claim to improve the quality of blurry or pixelated photos.

  • What kind of photos did the author use to test the AI enhancer apps?

    -The author used a few different types of photos: one that was in perfect focus, one with soft clarity and texture filters applied, and one that was completely out of focus.

  • How many AI photo enhancer apps did the author download and test?

    -The author downloaded and tested four different AI photo enhancer apps.

  • What was the author's initial skepticism about these apps?

    -The author was skeptical that these apps could truly enhance blurry or pixelated photos to make them look perfect and sharp, suspecting they might just be applying sharpening filters.

  • Which app did the author find most impressive and why?

    -The author found the Vivid AI photo enhancer app to be the most impressive because it added texture to the skin and analyzed what should be sharp versus soft, providing a noticeable improvement in the photo's quality.

  • What was the author's opinion on the subscription model used by these apps?

    -The author expressed frustration with the subscription model, finding it excessive and questioning why every app seems to have one.

  • How did the author feel about the results from the Pixel Up app?

    -The author was impressed with the results from the Pixel Up app, noting that it provided similar results to the Vivid app and would consider paying a one-time fee for its features.

  • What was the author's final recommendation for enhancing slightly out of focus photos?

    -The author recommended using either the Vivid app or the Pixel Up app for enhancing slightly out of focus photos, as they provided the best results in the tests.

  • Which app did the author consider to be the worst and not worth any amount of money?

    -The author considered the app advertised on Tick Tock, which was referred to as the Loopsy enhance app or the Sharp AI photo enhancer, to be the worst and not worth any money.

  • What was the author's general impression of the AI photo enhancer apps after testing them?

    -The author was surprised and somewhat impressed by the capabilities of some AI photo enhancer apps, particularly the Vivid and Pixel Up apps, which were able to improve the quality of out-of-focus photos more than expected.

  • What advice does the author give for using these apps?

    -The author advises that while these apps can be useful for enhancing certain photos, they should not be relied upon as a primary tool for photography. They suggest considering a one-time purchase for apps like Pixel Up if someone has many photos to enhance.

Outlines

00:00

📱 Testing AI Apps for Photo Sharpening

The speaker begins by addressing a common inquiry they receive about apps that claim to enhance blurry or pixelated photos to perfection. They decide to test several apps, including Vivid AI Photo Enhancer and Pixel Max Sharp AI, to determine their effectiveness. The test involves using different photos of the speaker's wife, Michelle, ranging from a perfectly sharp image to one that's completely out of focus. The speaker then proceeds to download and evaluate the apps, noting their subscription-based pricing models and the results they provide. The Vivid app impresses the speaker with its ability to add texture and detail to a soft photo, and the Pixel Max app also shows promising results, although the speaker is skeptical of the high subscription costs.

05:04

🔍 Evaluating the Effectiveness of Photo Enhancement Apps

In the second paragraph, the speaker continues their evaluation of photo enhancement apps. They discuss the results of using the Vivid and Pixel Up apps, noting that they are impressed by the improvements made to out-of-focus photos. The speaker also mentions the cost of these apps, suggesting that while they might not be worth a yearly subscription, they could be useful for a one-time purchase to enhance a large batch of old or out-of-focus photos. The speaker then briefly examines other apps, such as Loopsy Enhance, which they find to be less effective and more expensive than the Vivid and Pixel Up apps. They conclude by recommending the Vivid and Pixel Up apps for users looking to sharpen their photos and encourage viewers to subscribe for more content and share their thoughts in the comments.

Mindmap

Keywords

AI Photo Enhancer Apps

AI Photo Enhancer Apps refer to software applications that use artificial intelligence to improve the quality of digital photos. In the video, the host is skeptical about the effectiveness of these apps in enhancing blurry or pixelated photos. The main theme revolves around testing these apps to see if they can truly make a significant improvement to the quality of photos.

Blurry Photos

Blurry photos are images that lack sharpness due to motion, incorrect focus, or other factors during the capture process. The video script discusses the challenge of enhancing such photos using AI apps, which is central to the experiment conducted by the host.

Sharpness

Sharpness in photography refers to the clarity and definition of an image. The host is interested in seeing if the AI apps can increase the sharpness of photos, turning blurry images into sharp ones, which is a key aspect of the video's investigation.

In-Focus

In-focus is a term used to describe a part of an image that is sharp and clearly defined. The host uses an in-focus photo as a benchmark to compare the results of the AI enhancement process.

Texture Filter

A texture filter in photo editing is used to add or enhance the surface texture of an image. The script mentions the host's experiment with a texture filter to see if the AI can add skin texture to a technically sharp but softened photo.

Out-of-Focus

Out-of-focus describes parts of an image that are not sharp and appear blurred. The host tests the AI enhancers on out-of-focus photos to evaluate their ability to recover details from such images.

App Store

The App Store is a digital distribution platform, developed by Apple Inc., for mobile apps on iOS. In the video, the host searches the App Store for AI sharpen apps to download and test.

In-App Purchases

In-app purchases are payments for digital goods or services within an app that a user has already downloaded. The script mentions that while the apps are free to download, they come with in-app purchases, which is a common monetization strategy for free apps.

Subscription Model

A subscription model is a business model in which customers pay a subscription fee to have access to a product or service on a regular basis. The video discusses the prevalence of subscription-based services in apps, which the host finds frustrating.

High-Resolution Photos

High-resolution photos are images with a greater number of pixels, resulting in more detailed and clearer pictures. The host mentions high-resolution photos in the context of testing the AI enhancers to see if they can improve the quality of such images.

AI Generated Faces

AI generated faces refer to images created by artificial intelligence that mimic human faces. The host notes that one of the AI apps produced results resembling AI-generated faces, indicating that the app was not simply sharpening the image but attempting to recreate facial features.

Digitizing Photos

Digitizing photos involves converting traditional physical photos into digital formats. The host suggests that AI enhancers could be useful for improving the quality of old, out-of-focus photos during the digitization process.

Highlights

The video discusses the skepticism around AI photo enhancer apps that claim to improve blurry or pixelated photos.

The host decides to test a few AI photo enhancer apps to see if they can truly enhance poor quality photos.

Different levels of focus in photos are used for the test, including a perfectly sharp photo, a softened sharpened version, and an out-of-focus shot.

The host searches for AI sharpen apps on the App Store and selects a few for testing, including Vivid AI Photo Enhancer and Pixel Up.

Vivid AI Photo Enhancer is tested first, showing a significant improvement in texture and clarity in a previously blurry photo.

The host is impressed by the app's ability to analyze and enhance soft skin areas while maintaining sharpness.

An out-of-focus photo is tested, and the AI manages to bring back some details, although not as lifelike as the original.

The host expresses surprise at the AI's ability to enhance a partially blurry photo, making it suitable for smaller viewing sizes.

The video compares the AI-enhanced photo to the original sharp photo, noting that while not identical, the AI version is impressive for certain uses.

Pixel Up is tested next and shows comparable results to Vivid, with the host considering it a good investment for enhancing photos.

The host criticizes the marketing of some apps, accusing them of misleading users by pixelating original photos to show a虚假 (false) improvement.

Some apps offer a one-time payment option, which the host finds more reasonable than weekly subscriptions.

The host finds that not all apps perform equally, with some producing poor results, like the one advertised on TikTok.

The video concludes with a recommendation to use Vivid or Pixel Up for photo enhancement, but advises against the TikTok-advertised app.

The host suggests that these apps could be useful for digitizing old photos or enhancing slightly out-of-focus images.

The video ends with a call to action for viewers to subscribe and comment on other apps to test in future videos.