Photography has a lot of rules that are really just principles. Most of them are useful guidelines worth understanding, not edicts to be followed to the letter. In this photography fundamentals series, we’re going to look at when you should follow the rules—and when you should consider breaking them. First, though, we need to cover some of the most important fundamentals of photography composition.

Related: How to take good pictures in bright sunlight

The rule of thirds

The rule of thirds is one of the most common—and most misunderstood—fundamentals of photography composition. The idea is that you divide your frame into thirds both vertically and horizontally. The important elements of your image should then be placed on one of these third lines or better yet, at one or more of the four intersections of both vertical and horizontal third lines, like the truck in the image above. 

While not itself the secret to wonderful images, the rule of thirds is a great way to avoid some big compositional mistakes. If you follow it, you normally place the most important elements of your image nicely in the frame without them being too centered. 

If you’ve got a reason to ignore the rule of thirds, go right ahead. Otherwise, it’s a handy starting compositional principle to work from. 

The golden ratio

The golden ratio or golden spiral is similar to the rule of thirds, compositionally speaking, but with more mysticism and mathematics thrown in.

While the rule of thirds splits the frame into three equal sections, the golden ratio, also known as the Fibonacci Spiral, places a vertical frame line closer to the center of the frame, splitting it into one slightly smaller and one slightly larger quadrant. Each time the frame is split horizontally, the smaller section is then split vertically using the same ratio. This process is repeated, breaking the frame into smaller and smaller chunks, as shown above.

However, even though the ratio appears often in both great works of art and nature, we’ve yet to see an image where it creates a significantly stronger composition than the rule of thirds (they’re just so darn similar). So, while it can be fun to play around with, it’s certainly not a compositional rule that you should obsess over.

Symmetry

Symmetry can make for incredibly eye-catching images. It’s often easy to create symmetrical compositions with reflections, like from surface water, or using man-made structures, as shown below.

Symmetry is also one of the most fun compositional principles to break. Images with a mix of symmetrical and asymmetrical elements can be incredibly compelling. 

Complementary colors

Think back to your earliest art class, remember the color wheel? Well, the same principles that apply to painting and drawing also apply to photography. Colors opposite each other on the wheel, when placed side-by-side or near one another, often appear brighter. So, photos with reds and greens, yellows and blues, or purples and oranges, for instance, will look extra vibrant and punchy. Use this knowledge to your advantage.

Leading lines

Our eyes are drawn to strong lines in images. This makes things like guide rails of a bridge or even just a road through a landscape, a great way to guide (or lead) your viewers’ gaze to the most important parts of your photo. 

Leading lines isn’t so much a compositional rule you should break, as something you should be aware of if you don’t want to use it. If your image has strong lines, it will draw viewers’ attention. If you don’t want them looking where the lines lead, you will have to reframe your shot. 

Fill the frame

Filling the frame is a compositional approach that says your subject or subjects’ should take up as much of the image as possible. With a portrait, this generally means cropping in so that the subject’s face or body completely fills the frame. This removes the background and as a result, the context of the scene from the subject, often leading to some pretty dramatic results. The same approach to can be applied to a crowd, as shown above.

While a useful stylistic approach for many kinds of photography, there are plenty of times when you shouldn’t fill the frame with your subject. For example, if you are trying to show size by situating your subject in its environment, or trying to create a sense of isolation, filling the frame will undermine your intent.

Don’t cut things off

A common principle recommended in many photography books is to avoid cutting limbs, torsos, and other crucial parts of the image with the edge of your frame. It’s easy to understand why; most people look silly with half their hand chopped off. However, it can be tricky to pull off in practice, especially when you’re shooting street or travel scenes. 

At a fixed point, the photograph ends but the world continues. While it is worth thinking about what is getting cut out of the image by the frame, you will always have to make a decision that cuts something out. (Just try to keep as many limbs in the image as possible.)

Keep the action going into the frame

Especially for sports and other kinds of action photography, a good principle is to keep the action going into the frame. This means that if your subject is running to the right, then they should be positioned to the left of the image so they are running into the open space. 

This is another rule that works in a lot of situations, but can readily be broken when you have cause to do so. For example, if you are shooting a 100m sprint and want to show the gap between first and second-place runners. 

Useful rules, but not laws

Photography is a wonderful mix of science and art. While the process of capturing an image relies on the laws of physics and mathematics, composing a photograph is a pure art. Although the fundamentals of photography composition include some fantastic rules, they are best viewed as starting points that will stop you from making mistakes, rather than laws that can’t be broken. 

In the next article in the series, we’ll look at how to do just that.

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Flickr announced this week that it will be adding a new category to its platform: virtual photography. “Photographs” captured in video games or other virtual platforms like Second Life will now have a place on Flickr alongside other photos, illustrations and artworks, and screenshots. It’s a big sign that the once-niche genre is on the rise. 

What is virtual photography?

As modern video games have become more visually impressive and photorealistic, developers have added photo modes to let players show off the beauty of the world around them. This has created an increasingly popular photographic sub-genre called virtual photography (or just video game photography). 

Related: ’35mm’ is a photography-themed videogame set in a post-apocalyptic world

Some games, like Horizon Zero Dawn, The Last of Us Part 2, Spider-Man: Miles Morales, and Red Dead Redemption 2, enable the player to pause the game, position the camera anywhere, adjust camera settings like the depth of field, and even pose the character how they like. It allows for a huge amount of creativity, and it’s what separates virtual photography from simple screenshots. 

What does this mean for Flickr users?

Until now, virtual photography didn’t fit neatly into any of Flickr’s categories. Virtual photographs aren’t really photos, nor are they quite digital artworks or screenshots. 

Flickr created the new virtual photography category with two types of works in mind: video game photography and “content shared by the Second Life community.” Although users are free to categorize their work how they like, the virtual photography category is now a handy option for video game photographers as it allows their work to be found, shared, and seen for what it is.

In its announcement, Flickr highlights the fact that virtual photographers will now be able to search the site to see video game photographs from other artists, without having to look at “real-world photography or other art and illustration”.

A genre on the rise

Flickr’s announcement isn’t the only bit of big news for virtual photography this week. Ubisoft has just announced a new in-game photography contest and exhibition called PHOTOMODE. Players can enter virtual photographs from “any Ubisoft game that features Photomode” including Assassin’s Creed Valhalla, Far Cry 6, and Steep.

Related: Someone hacked a Game Boy Camera to shoot with Canon DSLR lenses

Like any other photo contest, there are multiple categories including Portrait, Outdoors, and Action, and some pretty cool prizes. The top 20 entries will get fine art prints of their work and will be displayed in a gallery exhibition in New York, while the three overall winners will also receive an invitation to the exhibition opening and an MSI Raider laptop. 

You can enter from now until October 16. The winners will be announced in November. 

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Sony has unveiled what it’s calling the world’s first pan-tilt-zoom (PTZ) camera with a full-frame sensor, interchangeable lenses, and remote shooting. Dubbed the ILME-FR7, this new addition to Sony’s Cinema Line is essentially an existing FX6 cinema camera affixed to an advanced PTZ mount. It’s designed to allow cinematographers to produce high-quality cinematic footage remotely, whether it’s for live broadcast or because there is a limited crew.

A full full-frame camera

Related: Best cinema cameras

The FR7 has a 10.3-megapixel back-illuminated 35mm full-frame Exmor R CMOS image sensor. It’s not really designed for stills but rather is optimized for 4K video performance at up to 120fps. (It can also shoot 1080p FHD video at 240 fps). 

The sensor has more than 15 stops of dynamic range and the ISO can be expanded up to 409,600, so it should be capable of capturing great footage in any lighting conditions. In Cine El mode, the base sensitivity can be set to either ISO 800 or ISO 12,800 to minimize noise while keeping a consistent visual appearance. 

The FR7 uses Sony’s E-mount lenses. It’s compatible with all of them, though for the larger, heavier lenses—including the 100-400mm f/4.5-5.6 GM, 200-600mm f/5.6-6.3 G, 400mm f/2.8 GM, and 600mm f/4 GM—the pan/tilt must be locked. Sony is selling the FE PZ 28-135mm f/4 G OSS cinema lens alongside the FR7 as a kit.

From P to Z

Given Sony’s pedigree, the FR7 is obviously going to be an extremely capable cinema camera, which is why the PTZ mount is so interesting. 

“The cinematic look and feel is rapidly becoming the norm in broadcasting and live production as it opens up new ways to tell a narrative,” said Yang Cheng, Vice President, Imaging Solutions, Sony Electronics Inc. in the press release. “In parallel, over the last two years, we’ve seen a steep rise in content created remotely or in small locations where access is difficult.”

Cheng claims the Sony FR7 “combines the flexibility of a standard PTZ camera with stunning visuals through advanced cinematic features,” and the specs suggest it pulls it off. 

The camera can pan between -170º to +170º and tilt between -30º to +195º as slow as 0.02 degrees per second and as fast as 60 degrees per second, enabling a wide array of different camera moves. It can memorize up to 100 different camera positions—including camera direction, zoom, and focus—that can be triggered at the touch of a button. 

Related: Best cameras for filmmaking on a budget

There’s also a built-in web application as well as an optional remote control so operators can control the camera from a distance. (It also integrates with Sony’s other cinema camera control products.)

Additional features of the Sony FR7

Perhaps most impressively, the FR7 supports Sony’s Fast Hybrid AF and Real-time Eye AF, and even allows for real-time tracking with the PTZ mount. According to Sony, the integrated BIONZ XR engine is able to lock onto a subject’s eye even when the camera is shooting from a steep angle. 

There’s also a built-in electronically controlled variable ND filter that allows for both manual adjustments, and automatic adjustments that compensate for changing light. 

The Sony FR7 supports CFexpress Type A and SDXC memory cards.

Pricing & availability

The Sony FR7 is available for preorder now for $9699.99. The kit including the FE PZ 28-135mm f/4 G OSS lens can also be preordered now for $12,199.99. Units should ship in November.

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This article originally appeared on Popular Science.

Open AI, developers of the AI text-to-image generator DALL-E 2, have just announced a new feature for the app called “outpainting”. It allows users to extend existing images and works of art with AI-generated content. It’s pretty exciting, and hugely expands the capabilities of the tool. 

Related: AI-generated image wins art contest, ‘actual’ artists irate

What are text-to-image generators? And how do they work?

DALL-E 2 is one of the most popular text-to-image generators available at the moment. With more than a million users, it’s no wonder that content created by it seems to be everywhere. (A lot of other text-to-image generators are either in a closed beta, like Stable Diffusion, are not available to the public, like Google’s Imagen, or are much more limited in scope, like Craiyon.) 

DALL-E 2 takes a text prompt, like “an astronaut riding a horse in the style of Andy Warhol,” and generates nine 1,024-pixel by 1,024-pixel images that illustrate it. It uses a process called “diffusion” where it starts with randomly generated noise and then edits it to match the salient features of the prompt as closely as possible. 

Until now, users were limited with the size and aspect ratio of what they could create with DALL-E 2. The AI program could only generate 1,024-pixel by 1,024-pixel squares—anything larger or a different shape was out of the question.

DALL-E 2 does offer a feature called “inpainting” to modify details in existing artworks, but to actually create a bigger canvas involved manually stitching different sections together using an app like Photoshop. (For different aspect ratios, you could crop your image, but that reduced the overall resolution.)

DALL-E image extender

Now with “outpainting,” the only limit users face—other than the content filters—are the number of credits they have. (Everyone gets 50 free generation credits during their first month and 15 to use every month after that. Blocks of 115 additional credits can be purchased for $15.) Generating an initial image takes one credit, as does every additional outpainted section. 

Outpainting works as an extension to DALL-E 2. Users select a 1,024-pixel by 1,024-pixel square area where they want to extend the image to and can specify any additional prompts to guide the AI. For example, to add more of a background to the astronaut on a horse, you could change the prompt to “an astronaut riding a horse on the moon with stars in the background in the style of Andy Warhol.” 

For each outpainted section, DALL-E 2 will offer up four possibilities for users to select. If none of them work for the image, you can get it to try again. 

Most impressively, outpainting “takes into account the image’s existing visual elements—including shadows, reflections, and textures.” This means that any details added “maintain the context” of the image and can really look like part of a coherent whole. 

Extending Girl with a Pearl Earring

In DALL-E 2’s announcement of outpainting, there’s a timelapse showing Girl with a Pearl Earring by Johannes Vermeer being extended to around 20 times its original size. Instead of a simple portrait, it shows a young woman standing in a cluttered house. It’s fascinating to see because so long as you don’t look too closely, it really does look like an extension of the original painting. The overall style and mood are spot on. It’s almost like an imaginary behind-the-scenes shot.

If you want to try outpainting, you will need to sign up to DALL-E 2. Open AI is currently operating a rolling waitlist. If you want to sign up, you can do so here. 

The post Peer ‘behind-the-scenes’ of famous paintings with the help of AI appeared first on Popular Photography.

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After announcing a $69 50mm f/2 mirrorless lens six weeks ago, TTArtisan is kicking off fall with a new $55 25mm f/2 lens. This budget-friendly, all-manual prime is available for a wide range of crop-sensor mirrorless systems (unlike the 50mm, which was a full-frame lens). And you can get one right now from TTArtisan’s online store.

Who it’s for

Related: You can 3D print a surprisingly capable 163mm f/2.4 telephoto for $13

With it’s 25mm focal length—equivalent to a slightly odd 37.5mm field of view—TTArtisan’s new lens sits at the wide-end of the “normal” focal range. In the marketing material, the company highlights this, saying it’s “close to the natural field of human eyesight.” 

Combined with the manual focus and manual aperture setting, this lens screams street and travel photography to us here at PopPhoto. You can set it to f/8, focus at around the 5-meter mark, and snap away confident that most of what’s happening in front of your camera will be captured sharply. And, if the light starts to fall or you turn down a shady street, open up the aperture and keep shooting away. (I love the now-discontinued Canon EF 40mm f/2.8 for this as well and use it all the time.)

The TTArtisan 25mm f/2 is available for the same lens mounts as its 50mm sibling: Canon RF, Canon M, Fujifilm X, Leica/Sigma/Panasonic L, Nikon Z, and Sony E-mount. Of course, if you use it with a full-frame camera you will need to use crop mode or face heavy vignetting. It’s also available for Micro Four Thirds, which will translate to a handy 50mm equivalent field of view.

Design & optics

Optically, the TTArtisan 25mm f/2 is almost as simple as the 50mm. It uses seven elements arranged in five groups, instead of six elements in five groups. It takes the same 43mm filter thread and the lens can focus as close as around 10 inches. For close-up work, it could be surprisingly impressive.

Everything about the lens is manual. The aperture ring has a range of f/2 to f/16. TTArtisan mentions that the lens is suitable for “pursuing beautiful bokeh” though, with only a seven-blade aperture diaphragm, we suspect they might be a bit choppy. If you want bokeh, the 50mm will give better results. 

The focus ring is at the rear of the lens. And it has hyperfocal distance markings, which should make getting those street shots easier. 

Though TTArtisan again doesn’t specify, we assume the lens is almost certainly built of plastic and not weather-sealed. That said, the lens mount does appear to be metal which is a big plus. The size and weight vary slightly by mount, though at around 1.2-inches long and 2.35-inches in diameter on all cameras, this thing is pretty tiny. All versions of it weigh less than 7 ounces, so you will barely notice it in your bag. 

Price & availability 

The TTArtisan 25mm f/2 is a little cheaper than the 50mm at just $55, regardless of which mount you choose. It’s available today for all its compatible lens mounts. 

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The demand for silver increased 19 percent last year, according to the World Silver Survey 2022. Part of this increase is due to a 3 percent uptick in demand for silver from the broader photography industry. While a big driver is medical X-rays, the popularity of amateur film photography also played a small role. 

Photography in flux

Falling sales, declining demand, and general photographic doom and gloom get a lot of coverage in the photography press. The industry has, for some time, been going through a smartphone-driven decline along with a seismic shift to mirrorless cameras.

Related: 5 reasons digital photographers should try film

Despite the flux, photography, as a medium, continues to explode in popularity. And not just smartphone photography but film photography, too. So, it’s fascinating to see the latter have a meaningful, if small, impact on the international silver market.

Medical X-rays are probably the real story

According to the report, photographic demand for silver “nudged upwards” 3 percent last year “bucking the long-term trend of decline.” This isn’t entirely down to the return of traditional film photography (which relies on silver-halides to work), unfortunately, as medical X-rays are also included in the same set of figures. 

The report stresses that “rather than representing a meaningful gain” the rise is more to do with the “depth of the COVID-related slump in 2020” and the resulting backlog of delayed X-rays that the medical community had to work through.

Despite this, sales of instant films have apparently almost fully rebounded from the “pandemic-related hiccup.”

Things are a little less rosey with regular film. According to the report, the “total demand for consumer and professional film and paper fell again last year, as travel still proved extremely difficult.” A big part of this was likely the motion picture industry which “posted another year of decline”. (A single Hollywood production presumably gets through a lot more 35mm frames than any number of amateurs.)

Still, with travel resuming and the 35mm devotees in Hollywood “staunchly committed” to the medium, the report predicts there will continue to be a “strong core of demand” for film photography. As such, it only predicts a 1 percent dip in demand for 2022. 

Silver linings (sorry)

In an article for Silver News, Don Franz, the editor of Photo Imaging News, paints the above figures in the best light possible.

Franz argues that “although the cost for processing film is increasing,” it does not seem to be deterring photographers as “additional labs are starting and restarting film processing lines.” Similarly, young consumers shooting instant film, the growing demand for single-use cameras, and the rising market for premium silver-halide paper for things like photobooks are all (small) signs of film photography’s comeback. 

Is Franz overstating the role of amateur photography in the silver market? Absolutely. It’s only when we looked at the report we saw that the demand for film had declined last year. But is it fun to acknowledge that it drives enough of the international silver market that it gets discussed in industry publications and mentioned in reports? Absolutely. 

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In a paper published in Scientific Reports earlier this year, researchers at Radboud University in the Netherlands, led by PHD candidate Thirza Dado, combined non-invasive brain imaging and AI-learning models in an attempt to read peoples’ minds—or at least recreate the image they’re looking at. It’s a fascinating experiment, though it’s easy to overstate its success. Still, mind-reading AI might not be as far off as we think.

fMRI and AI imaging

Functional magnetic resonance imaging (fMRI) is a noninvasive technique used to detect brain activity by measuring changes in blood flow to different areas of the brain. It’s been used for the last few decades to identify which parts of the brain are responsible for which functions. 

In this study, Dado’s team went a step further. They used an AI model (specifically a Generative Adversarial Network, or GAN) to attempt to interpret the fMRI results and convert the readings back into an image. The results are pretty impressive.

A trained AI

In the study, Dado’s team showed participants undergoing an fMRI 36 generated faces repeated 14 times for the test set and 1,050 generated faces for the training set (over nine sessions). 

Using the fMRI data from the 1,050 unique faces, they trained the AI model to convert the brain imaging results into actual images. (It works like a more primitive version of DALL-E 2 or Stable Diffusion.)

The results of the study, then, are based on the AI model’s interpretation of the fMRI data from the 36 faces in the test set. You can see a sample of them above. The image in the first column is the target image, and the images in the second and third columns are the AI-generated results from the two subjects. 

Is this mind reading?

While it’s easy to cherry-pick a few examples where the image (re)created by the AI closely matches the target image, it’s hard to call this mind reading. The results of the study measured the accuracy of the AI in matching the gender, age, and pose, as well as whether the generated face was wearing eyeglasses, and whether the generated face was smiling, not whether or not the generated face was recognizable as the target. 

It’s also important to note that the AI was trained on fMRI data from the test subjects. If you or I were to hop into an fMRI machine, the results would likely be incredibly scattershot. We’re still a long way from being able to accurately read anyone’s mind—with or without a car-sized scientific instrument. Still, it’s fascinating to see how AI tools and machine learning can play a role in other areas—rather than just winning fine art competitions.

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Lexar just released its awkwardly titled Lexar Professional CFexpress Type B Card Diamond Series line of flash memory cards, which were first announced back in April.  It’s billing them as “the World’s fastest” CFexpress Type B cards with “blazing fast speeds of up to 1900MB/s read and 1700MB/s write.” There’s a lot to unpack here, so let’s dig in.

CFexpress Type A vs. B vs. C

CFexpress cards are the latest generation of flash memory cards for professional cameras. The name should sound a little familiar to most photographers. They are the successor to CompactFlash and CFast cards, rather than SD cards. (The high-speed successor to SD cards, SD Express, was “pretty much dead on arrival”.)

CFexpress cards use the PCIe 3.0 interface—basically, what your computer uses to transfer data to its solid-state drive—which allows for much faster transfer speeds than SD cards. They come in three sizes: Type A, Type B, and Type C. 

CFexpress Type A cards measure 20mm x 28mm x 2.8mm and have just one PCIe lane. As such, they’re the smallest and slowest (though with a theoretical maximum transfer speed of 1000 MB/s, still much faster than SD cards). Lexar also announced a new line of CFexpress Type A cards a few weeks back. 

CFexpress Type B cards measure 38.5mm x 29.66mm x 3.8mm (the same size as an XQD card) and have two PCIe lanes. They are the most common CFexpress card used in professional cameras and have a theoretical maximum transfer speed of 2,000 MB/s. This is what Lexar announced this week.

CFexpress Type C cards measure 54mm x 74mm x 4.8mm and have four PCIe lanes. They aren’t on the market yet, but will likely be limited to high-end cinema cameras that could potentially make use of the theoretical maximum transfer speed of 4,000 MB/s.

What cameras use CFexpress cards?

The following cameras all have one or more CFexpress slots. Some of these cameras launched with XQD support, which was upgraded to CFexpress Type B support with a firmware update as the two cards are identical in physical design. We’ve also included the two Sony bodies with CFexpress Type A slots.

• Canon EOS R3 (Type B)
• Canon EOS R5 (Type B)
• Canon EOS-1D X Mark III (Type B)
• Nikon Z6/Z6 II (Type B)
• Nikon Z7/Z7 II (Type B)
• Nikon D6 (Type B)
• Nikon D850 (Type B)
• Panasonic S1/S1R (Type B)
• Sony A1 (Type A)
• Sony A7S III (Type A)

Is the Lexar CFexpress Type B diamond card really the world’s fastest?

Lexar announced its new cards with a lot of superlatives and bold claims. The card’s “blazing fast” 1,900 MB/s peak read and 1,700 MB/s peak write speeds are very close to the 2,000 MB/s theoretical maximum of a Type B CFexpress card. And while we don’t doubt that Lexar achieved these speeds in a lab test, they aren’t indicative of the performance photographers will see in the real world. 

Our colleagues at PetaPixel put the new cards through their paces and while they’re fast, they don’t quite match up to Lexar’s claims—except in one key area. 

In PetaPixel’s tests, the Diamond Series Series cards averaged peak write speeds of 833 MB/s and peak read speeds of 794.5 MB/s—enough for second place to Sony Tough cards. Its sustained performance was worse, averaging 499.5 MB/s—that’s eighth-place in the cards tested, but PetaPixel points out that everything over 400 MB/s is likely indistinguishable in the real world. 

Where the Diamond Series cards really stood out was the burst speed test with a Canon EOS R5. Lexar’s card was able to sustain the highest burst speed for over 30 seconds. The second-best card only made it to 19 seconds. 

So, while “fastest in the world” is a very bold claim, Lexar’s new cards are definitely up there. 

Where to buy a Lexar CFexpress Type B Diamond Series card

Lexar CFexpress Type B Diamond Series cards are available now. The 128GB version is $199.99; the 256GB version is $329.99.

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Just four months after launching, Snap (the company formerly known as Snapchat) has grounded its Pixy selfie drone. The diminutive $230 drone got middling reviews and suffered from low presales. Somewhat understandably, given the current economic climate, Snap CEO Evan Spiegel told staff that future development was being halted as “part of broader reprioritization of company resources”.

Related: Pixy is a tiny, $230 selfie drone built for Snapchat

But the Pixy’s swift crash from grace got us all thinking here at PopPhoto about other products that were announced with great fanfare and then—just didn’t do much. Some are pure vaporware and never even launched, others were just colossal flops. These are some of our favorite defunct photo gadgets.

Light L16

The Light L16, announced in 2015, crammed 16 different smartphone cameras into one super-sized smartphone-sized package. It could take 52-megapixel images with a full-frame equivalent focal length of between 35mm and 150mm. Because every image was a composite of the 16 cameras, the resulting depth map made it possible to adjust the focus and depth-of-field in post. Light claimed the L16 offered DSLR-like image quality and great low light performance—though the reviews (when it finally launched in 2017) said otherwise, and considered some of the user experience “a chore”. 

Instead of working on a follow-up, Light took a huge $121 million funding round from SoftBank and established partnerships with mobile phone companies like Nokia. 

That didn’t work out either, and in 2020 the company abandoned consumer imaging to focus on the automotive industry. It was quietly acquired by John Deere earlier this year. Presumably, there is no plan to release a consumer camera. 

GoPro Karma Drone

For action camera company GoPro, the drone market must have seemed like a gimme. Plenty of drones were (and still are) using its Hero line of cameras to capture aerial footage, so why not cut out the middleman and release its own drone?

When the GoPro Karma launched in 2016 the reviews were fine. It wasn’t as feature-filled as DJI’s offerings, but the removable stabilizer grip was considered a clever touch. Then they started falling out of the sky. GoPro had to issue a recall and then re-released it a few months later. 

Understandably after that fiasco, consumers weren’t that interested in the Karma, and with sales also poor for the company’s other products, the company was restructured and scrapped its entire drone division in 2018. 

Lytro in general

Unlike many companies on this list, Lytro managed to launch two products that actually did what they claimed to. Unfortunately, the underlying light-field technology—while undeniably impressive—just didn’t really deliver in the real world. 

Lytro’s schtick was that its cameras took photographs at multiple depths. The resulting merged image could have the focus and depth-of-field edited in post. This genuinely worked with both 2012’s Lytro Light Field Camera and 2014’s Lytro Illum—but the user experience left a lot to be desired. 

Photographers, it seemed, preferred having a nice-to-use, high-resolution camera, even if it meant handling focusing and aperture themselves. 

Lytro pivoted to VR, flailed around a bit, and was then sold to Google in 2018—who promptly shut it down. 

Kodak’s “New” Super8 camera

In 2018, Kodak announced a brand new Super8 camera. Despite shooting film, it had a few digital touches like an LCD viewfinder and an SD card slot. It was due out later that year and we even got some test footage.

And then… nothing. 

So you can imagine how surprised we were when researching this article to find that, at least according to Kodak’s website, it’s still in development. Sure, it doesn’t look like it’s been updated since 2018, but there is a reservation form where you can sign up to purchase a camera—should they ever materialize. 

Nikon DL series 

In 2016, Nikon announced the DL series of 4K compact cameras designed to go head to head with Sony’s RX100 series. There would be three models with different zoom ranges: the DL 18-50, DL 24-85, and the DL 24-500. All were due to cost less than $1,000 and, at least from a spec perspective, looked like they could be a great option for street and travel photography. 

But then there were problems. An issue with the integrated image processing circuits caused a delay. And that delay turned into a full-blown cancellation in 2017 without even a single unit sold. 

(Nikon’s KeyMission foray into action cameras was equally misguided, but at least the cameras made it to market.)

What about you?

Have you got any favorite defunct photo gadgets? Think we missed a spectacular flop? Then let us know at info@popphoto.com.

The post 5 defunct photo gadgets that were supposed to ‘change everything’ appeared first on Popular Photography.

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Romanian photographer and artist Aurel Manea has used a new text-to-image AI to create beautiful, almost-photorealistic, landscape images. 

First noticed by PetaPixel, Manea used Stability AI’s Stability Diffusion—a DALL-E 2-like text-to-image generation tool—to make the series of incredible landscape “photographs.” By using prompts like “landscape photography by Marc Adamus, glacial lake, sunset, dramatic lighting, mountains, clouds, beautiful” he was able to create the shots of entirely made-up places. (You can also see other photorealistic images generated by the AI in the Stability Diffusion Facebook group.)

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A post shared by Aurel Manea (@aurel_m_m)

However, unlike DALL-E 2, Stability Diffusion has limited content filters. That’s partly why it is able to create such realistic scenes, but it also raises a few troubling concerns.

How do these AIs work?

Most of the text-to-image generation AIs that are popular at the moment, like DALL-E 2, Google’s Imagen, and even TikTok’s AI Greenscreen feature, are based on the same underlying technique: diffusion models. The deep-down mathematics are complicated, but the general idea is pretty simple. 

Diffusion models work by tapping huge databases of images paired with text descriptions. Stable Diffusion, for example, uses more than five billion image-text pairs from the LAOIN-5B database. When given a prompt, the models start with a field of random noise and gradually edit it until it begins to resemble the written target. The random nature of the initial noise is part of what allows each model to generate multiple results for the same prompt. 

In other words, every pixel in an image created by one of these models is original. They’re not copying and pasting random parts of different images in a database to generate something, but subtly shaping random noise to resemble a target prompt. This is why so many objects often appear swirly or slightly misshapen—even Van Gogh-esque.

The problem with no filters

Most text-to-image generation models either have high level content filters—like DALL-E 2—or are limited to researchers—like Imagen. What’s most unusual about Stable Diffusion is that it has relatively limited content filters, and Stability AI plans to make it available to the general public. This raises a couple of potential issues. 

To prevent DALL-E 2 from being used to generate misinformation, Open AI blocks people from creating images of real people. Stable Diffusion has no such filter. Over on TechCrunch you can see images of Barack Obama, Boris Johnson (the soon-to-be-former British Prime Minister) wielding various weapons, and a portrait of Hitler. While they aren’t quite photorealistic yet, the technology is going that way and could soon be open to abuse. 

The other issue is bias. Every machine learning tool is at the mercy of its dataset. DALL-E 2 has had its issues and, most recently, Meta had to shutdown its chatbot after it started spouting antisemitic election fraud conspiracies. TechCrunch notes that the LAOIN-400M database, the precursor to the one Stable Diffusion uses, “was known to contain depictions of sex, slurs and harmful stereotypes.”

To counter that, Stability AI has created the LAOIN-Aesthetics database, but it is unclear yet if it is truly free from bias.

Are these even photos?

For the past while at PopPhoto, we’ve been discussing how computational photography changes the nature of photographs. These types of generated images are just another outgrowth of the same kinds of research. The question here in particular is: If an AI can one day generate a realistic image of a real place—or even of an imagined place—then what does it mean for landscape photography? 

Obviously we don’t know yet, but we’re going to have fun discussing and debating it from here on out. 

How can I try Stable Diffusion?

If you want to try Stable Diffusion, you can apply on Stability AI’s website. Right now, it’s just open to researchers and beta testers.

The post These landscape ‘photos’ were generated by an AI appeared first on Popular Photography.

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