What is happening to creativity?

I'm seeing more of the same coming out of generative AI on social media. It is often nicely rendered but devoid of meaning, usually not quite right but puzzling rather than thought-provoking.

prompt: "More of the Same AI Social Media"

The Utopian view of social media is it will allow everyone to show and sell their wares and share ideas with anyone world wide. The reality is a lot different the limited number of places are clogged with wanna bee celebrities, their followers, copycats and a lot of anti-social behaviour. Anything originally creative that is good is swapped in copies and quickly becomes impossible to find. It is only the social media giants making ridiculous amounts of money from the "content" supplied (mostly for free). The change of ideas soon becomes closed in a self-fulfilling bubble that simply feed others in the group with what they want to hear (seldom the truth). It's all very sad.

I now see similar rhetoric being promoted for a utopian world we will be all using AI tools instead of employing or paying others. Already I can see a rush with everyone is trying to cash in, chasing money for nothing, from the likes of chatGPT in just seconds! The Net is filling with lots of sameness that is largely vaporware and again not quite right (full of bias, oversights and untruths). Bit sad really.

However, I just hope that the hype just dies away and the artist, creatives and makers get time to quietly try out the new tools. Mainly to get more productive and build a social place where they own the creative content (not just copying someone else style using a short prompt) but truly making something.

I like Danny Gregory’s weekly essays and this week was aimed at those who refuse to be creative.

Good timely advice. 

Composition - Cropping and Framing

The next photowalk is coming up this weekend. Seeing in Detail, and will include some surprise discussion of Composition and Framing, which can be carried out in the field, but Cropping, an underutilized photo editing tool, can also help in seeing more detail, but after the fact in post-processing.

In a photowalk a couple of years ago we tried out hand-held viewfinders to select the best composition before we took our photos. John Noble had made some wonderful adjustable viewfinders from matte board that could be adjusted to some common aspect ratios.

These aspect ratios become very important when it comes to composition because it is the frame that naturally constrains our vision and brain. It is seldom discussed in photographic compositional rules yet it is the most fundamental aspect of how the composition is perceived. These four boundary lines (I'm assuming for now the frame isn't oval or circular, and that introduces different compositional considerations) change the width and height as the aspect ratio is changed, Each proportion affects the dynamics of what is happening inside that frame.

ratio	common applications
1:1	Square eg Instagram
1:2	Panoramic
2:3	most Digital Cameras & some phones
3:4	Micro Four Thirds Cameras
4:5	Once favoured for Portraits eg 10" by 8"
9:16	Wide Screen TV, phones
10:16	Newer Wide Screen Monitors & TVs

As an exercise, mainly to convince yourself that the frame is the most important compositional aspect (and the cropping tool is one of the best ways to improve your photo). Find a photo you have taken, and then create a series of sub-photos from it but cropping to a few if not all the common ratios shown in the table above.

The Shape of Things to Come?

I’ve left to last, writing about aspects that I believe Ai techniques should be applied for photo editing and management in the future. The movement to apply different Ai based refinements into existing tools (eg masking, blending etc) will definitely continue. What I would love is to be able to train my own AI with my style of processing images and being able to supervise a more automatic “workflow” to suit both the photograph's content and my objectives.

Ted Forbes of the YouTube channel “The Art of Photography” has reviewed a new AI based photo editing offering called Imagen AI

This does sound a lot like something I have been looking for, a service that will automatically create edits for you using your styles (or generic “talent profiles”). At present, it appears very much aimed at bulk usage cases like event and wedding photographers and specifically from Lightroom. I hope the methods can be taken further, expanded to be more general and interfaced with other software/starting points.

So this is interesting, but not immediately helpful for me (whilst I do have an old version of Lightroom still but never use it) and I’m not holding my breath that it might become the next big thing.

Google have now also released its own text-to-image service also called Imagen, It's a competator for other similar AIart and whilst appropriate prompting can elicite photo-realistic images it's unlikey to be interest to or useful for most photographers.

Portrait AI Helps Out

It is my belief that Portrait AI features in photo editing software can help photographers enhance their portraits and avoid a lot of tedium. I don’t regularly take portraits (other than family, which I very rarely post online). The software I have, ON1 Photo RAW and Luminar Neo both offer powerful AI-powered portrait features that speed up post-processing and also achieve great results. By automating the tedious task of skin retouching and facial feature adjustments, like teeth and eye whitening.

My current favourite is ON1 Photo RAW which includes AI-powered features like face detection and skin retouching. With AI-powered face detection, the software will automatically detect the faces in your photos, making it easier to apply targeted edits that are in line with your style. The skin retouching feature allows you to quickly and easily smooth out blemishes, wrinkles, and other imperfections in your subject's skin and identify and work on key facial features.

Luminar Neo also offers powerful portrait AI features, including AI Skin Enhancer and AI Portrait Enhancer. The AI Skin Enhancer feature allows you to quickly and easily smooth out skin imperfections, while the AI Portrait Enhancer can help you adjust your subject's face shape, eye size, and other facial features, the face-thinning and eye-widening are a little over the top but have been fun to play with.

Portrait AI features are now widely available in photo editing software, but have not been heavily promoted or hyped as much as sky replacement AI, however it does offer photographers powerful tools to enhance their portraits with ease. Many of the alterations are very subtle but that's good. I'd be interested to find out if professional portrait and wedding photographers are taking advantage of these tools and what their clients think?

Ps I’ve given Chatgpt a second chance, to edit my text for this post. I’ve still had tone it back down a little but it hasn’t introduce half truth or outrageous claims this time.

Some more thoughts and experience with deep learning of neural networks

This was initially a postscript to the previous article about Luminar. I’m a classic dyslexic, and struggle to write still, even using a computer my typing text is a bit of a struggle and has red underlined words on most lines, punctuation is missing and I might waffle on a bit. So I have been looking at getting GhatGPT to edit my words. I submitted yesterday's draft post with the prompt rewrite for a blog post. And rewrite it did

“Luminar, the popular photo editing software, has come a long way since its inception. ….. They were the original developers of Nik Collection and Snapseed, two of the most popular post-processing tools in the apple market.”

“Nevertheless, Skylum's commitment to innovation is admirable, and it will be interesting to see what new AI iterations of Luminar will come out in the future.”

There was quite a bit of positive promotion of the wonders of Luminar and how thrilled I was with it elsewhere in the text returned. If you read my post I wasn’t exactly thrilled. although I do use the software regularly. Its enthusiasm was really stretching the truth, and I only used the ChatGPT output as a guide for my post in a few places. This really bought home that you must be sceptical of this AI and fact-checking its output is super important. 

1. There is an obvious conspiracy theory that big companies are already paying OpenAI for good reviews whenever specific brands, company names or keywords are used. I do doubt this is the case yet (and sorry I even mentioned it). 
2. A more likely explanation is the blogging world, and specifically “influencers” have filled the space with very favourable reviews and self-promotions.  And stuffed the “content” with relevant #hashtags. These have totally overwhelmed honest reviews or news and as a result the deep learning has been trained on a very positively biased data set. Ok that is exactly what the net is like these days so why am I surprised? 

Just be careful what you believe coming from AI, if you even know it was AI generated.

I’ll also be careful not to ask ChatGPT to rewrite in the future.

Luminar :: A perspective of Skylum's AI Journey

The Luminar journey started with Macphun, a company that developed photo editing tools solely for Apple Macintosh computers. They were the original developers of Nik Collection and Snapseed, two of the more popular post-processing tools in the apple market (Mac and IPhone) at the time.

Later, Macphun shifted its focus to the Windows environment as well and started testing new simpler user interfaces. This approach eventually led to the birth of the Luminar suite. The initial versions of Luminar were standalone software that had a photo browser underneath and ran modules similar to the specific style of add-ins they had previously supplied. The software was less expensive and simpler to use, and it was popular with photography enthusiasts rather than professionals.

Macphun, became Skylum, and upgraded the software at an incredible rate compared to Adobe. Some of the upgrades introduced new approaches, which were mainly loved, but incompatibilities across updates were poorly received. The cost and frequency of upgrades meant that owning and maintaining an up-to-date version was becoming expensive. During this time, Macphun/Skylum also developed Aurora HDR in association with Trey Radcliff and included a number of AI-based techniques, specifically being able to recognize different parts of an image, such as the sky, people, buildings, and lakes.

The introduction of Luminar 4 was a significant rethink of the way photo editing was undertaken. Unfortunately, it had several incompatibilities with previous Luminar versions, and some previous tools were missing, so a lot of the previous non-destructive edits could not be reproduced. User were generally not impressed.

Not long after the Luminar 4 fiasco, Skylum released Luminar AI, which was again a new and somewhat incompatible rewrite. It still provided a comprehensive photo editing package but was based on the use of AI-trained tools exclusively to perform most functions. While it was nice to use, it wasn’t easy to figure out what was happening in the edits, and how it might be used as a start further photo enhancements. Some of these issues were quickly resolved with updates. However, some users felt that Skylum was gouging money out of their supporters by releasing new stuff that made upgrading a daunting repurchasing and relearning exercise.

Soon after Luminar AI was released, Luminar Neo was promoted as a totally new way to post-process. However, it was not really compatible with previous iterations of Luminar. While the single enhance slider was pretty amazing, the great list of "edit" tools on the right-hand side of the edit panel showed several of the same sliders, and not always getting the same result depending on which item they were run within. The tools were also grouped into similar tools, favourite, Essentials, Creativem portrait & professionals, which helps negotiate such a long list of edit tools. The fact that there was no attractive price for updating from Luminar AI also got a lot of bad press.

Despite some reservations, many users, including me, still like Luminar Neo and use it a lot. However, it is definitely not as fast on my older hardware, and the solution of buying a new faster computer and having to pay for the extensions does not appeal to me. The extensions, which are a return to the add-in single effect style of tool, can be purchased as bundles (including not yet released features) or individually, plus numerous discount offers, making pricing complex and hides the true cost of getting a full function editor. 

I've chosen to process an "ordinary" photo without surreal colour changes or adding drama (the dark side of AI tools), since it can give a better view of Luminar as a regular photo editing tool.

In conclusion, Skylum's journey with Luminar for me has been a roller coaster ride, with its ups and downs. While some users love the new AI-based approach, others are still nostalgic for the simpler, less expensive earlier versions of NIK Collection the earlier Luminars. Nevertheless, Skylum's commitment to innovation is admirable, and it will be interesting to see what new AI iterations of Luminar will come out in the future.

Sky Replacement Wars

 I consider this a relatively small digression in the Ai developments in photography. With the introduction of layers and masking in Adobe Photoshop, the ability to replace anything with something else, for example, a new sky has been possible. Albeit tedious. If the horizon was flat and only a few simple shapes against the sky made this easy. However bare deciduous trees, open foliage or fly-away hair and anything with a complex edge made this very time-consuming, especially when using the masking brush. This ability became an art form and photoshopping became a verb to describe this type of image manipulation.

I think it was Skylum's Luminar AI (a predecessor to Luminar Neo) that first added AI tools to make the sky masking fairly automatic and let you choose different skies from a library of beautiful skies. Further, it was heavily promoted, was popular and there was a lot of hype in the photo YouTube and podcast communities.

Other software developers quickly followed, some in a few weeks, with a variety of outcomes. So sky replacement became a very big issue comparing software offerings. How well the sky matched into the rest of the photo became important, as did being able to build and organize your own cloud image library.

The complexity of fiddly edges in the masking was helped as masking AI improvements where made. Also the methods applied to blend other aspects of the photo such as the reflection of the sky on water or wet surface or adding matching atmosphere effects.

In the illustrations here I have used simple “one-click” sky comparisons on two complex situations, the complex interconnecting lines of power cables and electricity transmission towers, and the bare tree branch silhouette. Comparing such sky replacement in current versions of Luminar Neo and On1 Photo RAW 2022, The results are good but not perfect. Both packages do offer other tools such as refining the mask edges and better colour balance etc.

The hype has faded but pretty well all the dominant software editing suites now offer AI assisted sky replacement.

From an Also Ran to a Thoughbred

I first started using Onone perfect Effects products as add-ins to lightroom, so long ago that I can’t reliably remember. They were great little tools that did simple things but with beautiful results. However, they suffered from the round trip of exporting from lightroom and then re-importing the result. There were all those temporary files. Still, they brought magic to the art of post-processing and Lightroom and Onone made a great team.

OnOne Effects were improved in several steps and started to offer a lot of advanced tools/effect that made it progressively more competitive with Photoshop, including some masking and layer features. They were still add-ins to Lightroom.

Sometime later Onone rebranded to On1. In the shape of things to come On1 Effects was released as a standalone photo editor. Not long afterwards On1 bought out a RAW rendering feature and then the ability to browse that meant it no longer needed lightroom. So it had become a standalone photo editing suite, with the ability for advanced photo editing features and particularly layers. People soon realized it was not only a competitor to lightroom, but also to the lightroom/photoshop combination. The biggest difference was that  On1 Photo RAW was a lot simpler to learn and use than the adobe products without the need to do a round trip, saving time. I stopped using Lightroom around this time.

At each upgrade various AI functions were introduced, starting with context-sensitive retouching, refinements to Masking, and especially a number of Portrait AI tools (which could find and differentiate eyes, lips, teeth, hair & skin etc). it all seemed very magical.

Next came the sky replacement wars. On1 may not have been the first but its AI-driven features made it a standout choice. I’m not sure why there was so much hype around this feature. It was easy and fun to use but I haven’t used it much. This is the time that AI tools became important additions to any serious photo editing and management package (Adobe have been doing a fair bit of catch-up) and there was significant improvement being added with each upgrade (but the upgrades were also becoming more expensive!

The latest version of On1 Photoraw 2023.1 is now out (I haven’t pushed the upgraded button just yet) and it really appears loaded with the sort of feature I have been looking for around better segmenting photos and refining masks. Even an adaptive preset feature knows what segments can be altered in different photos.

The Elusive One-Click Instant Fix

From the very earliest days of digital photo editing software, developers have been trying to create the ultimate instant fix button. Whether it's labelled “quick fix”. “auto-correct” or “auto-balance”, google had “I’m feeling lucky” and later “auto-awesome”, the goal has always been the same: to make photo editing as simple and effortless as possible. However, despite numerous attempts, none of these one-click fixes have truly lived up to their promise.

The trouble is, while digital cameras have improved significantly over the years, they still can't cover every situation. And even when they do capture a great shot, there are often still some focus and exposure issues that need to be addressed. This is where photo editing software comes in, but finding the perfect balance between automated fixes and manual editing can be a challenge and all too often very tedious.

Over time, I started to warm up to auto-fix tools and even created my own preset for Lightroom called SDR+. However, I didn't use it much, as I found it was often quicker and more trustworthy to just fiddle with the exposure sliders manually.

It wasn't until I started experimenting with Macphun's Aurora HDR that I really began to see the potential of what AI (Artificial Intelligence, in the form of Neural Networks) could do. This software used the networks to segment the image into different areas, such as the sky, foreground, background, buildings, and foliage, and potentially correct those areas separately. However, this information wasn't shown to the user. It would have been nicer to have access to it through prebuilt masks. Just be patient that feature would eventually come.

However, the developers' approach was somewhat arrogantly more focused on "we’ll do it better than you" and releasing regular updates for users and expecting them to sit back and enthusiastically pay for what they were being fed.

Skylum’s Photo Lemur showed great promise when I was invited to beta test it. Having previously tested Nic's Collection and Snapseed when they were still Macphun, and also looking at a pre-release Windows version of Luminar, I could see that the big difference with Photo Lemur was its simplicity and ability to batch process many files in a reasonable amount of time. It did a good job, although not outstanding, especially for social media where post-processing excellence would go unnoticed. It's biggest appeal that you don’t have to do anything was also its biggest weakness, you really can not control anything. Still I bought it straight away and still occasionally use it.

Macphun became Skylum and their software creations Aurora HDR and Photo Lemur were great examples of how AI can enhance the editing experience and made it easier and more efficient for photographers to create beautiful images.

Looking back AI within photo editing was still in its early stages, slowly making small incremental steps usually with room for improvement. The really rapid expansion of the tasks AI could perform and the rate of improvement were about to explode

What about AI in Photography

Artificial intelligence (AI) has been making its way into various industries, including photography, for some time now. While I've previously written about generative AI art, I haven't given much attention to the role of AI in photography. So in this next series of blog posts, I'd like to explore how AI has been used in photography and how it has impacted the industry.

Firstly, it's important to note that AI in photography is not a new concept. In fact, AI has been used to assist with photo post-processing tasks for the past decade. Most photo editing and management software nowadays utilize some form of AI-based tasks to automate more tedious tasks. For instance, programs like Adobe Lightroom use AI to automatically adjust exposure, colour temperature, and contrast.

AI has also been added to computational photography, mainly limited to higher-end smartphones and some mirrorless cameras. With the help of AI, smartphones can produce images with shallow depth of field, low light performance, and enhanced HDR. These AI-based features allow users to take high-quality photos without the need for expensive camera equipment or extensive post-processing.

As someone who enjoys photography, I've been using AI-based tools to enhance my photos for some time now. My favourite AI tools at the moment are ON1 Photo RAW and Skylum’s Neo. They utilize machine learning to automate many of the tedious post-processing tasks. Both have a similar range of features, including sky replacement, portrait retouching, and object removal, which can significantly speed up my post-processing without compromising quality.

In conclusion, AI has already established itself in the world of photography, and it's likely that you're already using some form of AI-based tool without even realizing it. The role of AI in photography is only set to grow in the coming years, as more and more innovative solutions emerge. While AI-based tools may not appeal to those who enjoy tweaking individual images and playing with sliders, they can certainly make the process of photo editing more efficient and accessible for everyone.

Exploring the Capabilities of Diffusion-Based AIart: OUTpainting

This will be the last post in my AIart series for now. I have been investigating the use of artificial intelligence (AI) to create stunning works of art. In particular, diffusion-based AI art has been gaining traction due to its ability to create realistic and artistic images.

Two additional features have became available under the diffusion process, INpainting and OUTpainting. INpainting involves removing a section of an image and replacing it with something that blends into the space. It is similar to context-sensitive replacement, as used in Adobe's software. On the other hand, OUTpainting involves adding extra areas outside the reference image in such a way that they seamlessly blend onto the image.

OUTpainting is particularly appealing to me here as it allows for the expansion of tightly cropped reference images. Expanding the image to a more classic still-life composition, playing with shadows and lighting to create a more realistic image. For instance, adding two full shadows, to give the image more depth and dimension.

I used Dall.E 2, at the openai website, as it is the most up-to-date version, which can add in extra objects to the image, such as a vase of flowers or a bowl of fruit etc, while still maintaining the original image's aesthetic.  Futher, Dall.E produces more photo-realistic images than some of the other diffusion-based AIart.

So my conclusion, text-to-image and particularly diffusion-based AIart is opening up new possibilities as a great tool/media for artists and enthusiasts alike. It's not a magic one-click to a masterpiece. It might be a shiny new toy for the wanna-bee celebrity artist, NFT worshippers or even those just wanting more likes on Instagram, The shine will soon wear off. By understanding and utilizing INpainting and OUTpainting features, we will all be able to create stunning and realistic images that were previously very difficult if not impossible to achieve. With technology continuing to advance, it will be interesting to see what other features will become available under the diffusion process or next AI advancement, and how they will be utilized in the world of art. I don't think the sky is falling in.