The Camera Filename Trick That Makes AI Images Look Like Real Photos (Midjourney V7 and FLUX Guide)

If you have been trying to get photorealistic results from Midjourney V7 or FLUX and everything still looks a little too polished, too perfect, too obviously AI, there is a deceptively simple trick that has been making the rounds in the AI art community. It involves adding a camera filename to the beginning of your prompt. That is it. And the results are genuinely startling.

The technique was popularized by Min Choi on X (formerly Twitter), who published a thread of AI-generated images that were nearly indistinguishable from real photographs. His secret was simple: prepend a standard digital camera filename like IMG_7384.CR2 to the beginning of the prompt.

How the Camera Filename Trick Works

The basic formula is straightforward. Instead of writing a normal prompt, you start with a camera filename:

IMG_7249.CR2 casual selfie at home

IMG_4358.CR2 woman walking through a farmers market in summer

IMG_02202021.HEIC couple sitting at a cafe in Paris

The number after IMG_ can be anything you want. The extension (.CR2, .HEIC, .JPG) matters more than the number. Canon RAW files (.CR2) and Apple HEIC files (.HEIC) tend to produce the best results, though standard .JPG works too.

You can even enter just a filename into Midjourney V7 with no additional prompt at all, and it will generate a random but photorealistic-looking image each time. The filename alone is enough to push the model toward realism.

Why This Works: Training Data Breadcrumbs

AI image generators like Midjourney are trained on millions of real photographs scraped from the internet. Those real photos almost always retain their default camera filenames: IMG_0023.JPG, DSC_4521.NEF, DSCF1234.JPG. When you include a similar filename string in your prompt, the model recognizes the pattern from its training data and activates the portions of its learned representations most strongly associated with real, unedited photography.

One technical explanation describes this as "latent spelunking," where the filename acts as an anchor token that forces the model into a specific slice of its latent space. The model's pattern-matching essentially says: "I have seen thousands of images associated with this token pattern, and they were all real photographs, so I should produce something that matches those characteristics."

The filenames are basically breadcrumbs back to a curated subset of the training data that consists entirely of real camera output. Natural lighting imperfections, realistic skin textures, authentic compositions, the kind of slight messiness that real photos have and AI images typically lack.

Camera Filename Formats That Work

Different camera brands use different filename conventions. Here are the most common ones and how to use them:

Prefix	Camera Brand	Extensions	Example
IMG_	Canon / Apple iPhone	.CR2, .JPG, .HEIC	IMG_7384.CR2
DSC_	Nikon	.NEF, .JPG	DSC_0001.JPG
DSCF	Fujifilm	.RAF, .JPG	DSCF1234.JPG
DSC0	Sony	.ARW, .JPG	DSC00001.JPG
_DSC	Nikon (Adobe RGB)	.NEF, .JPG	_DSC0001.JPG

All of these follow the DCIM standard (Design rule for Camera File system), where filenames consist of a 4-character prefix followed by a 4-digit number ranging from 0001 to 9999. Swapping between extensions freely is recommended, as variety prevents "repetition artifacts" in your outputs.

Leveling Up: The Extended Prompt Structure

Min Choi also shared an extended version of the technique that adds social media context for even more realism:

phone photo of {subject and location} posted to {social media platform}
in {some time frame} --style raw --s 0 --ar {vertical aspect ratio}

For example:

IMG_7249.CR2 phone photo of a woman at a coffee shop posted to
Instagram in 2024 --style raw --s 0 --ar 9:16

Adding a platform name (Reddit, Instagram, Facebook) with a year gives the output a specific aesthetic, as if it were a real photo shared on that platform. Instagram photos tend to come out warmer and more composed. Reddit photos have a more candid, unfiltered quality.

Key Midjourney Parameters for Photorealism

Beyond Filenames: Stacking Realism Cues

The camera filename trick works great on its own, but you can stack additional realism cues for even more convincing results:

Specify real camera models: Instead of writing "realistic photo," name the actual camera. "Shot on Canon EOS R5," "shot on Sony a7R V," or "Fujifilm GFX100S" all push the model toward the visual characteristics of those specific cameras.

Include lens and aperture: "85mm f/1.8" or "50mm lens, f/2.8" adds authentic depth-of-field characteristics. Different focal lengths produce different bokeh patterns and perspectives.

Add EXIF-style metadata: Including technical specs like "f/2.8 1/125s ISO 400" in your prompt acts as additional anchor tokens that pull the model deeper into its real-photography latent space.

Reference film stocks for vintage looks: "Kodak Portra 400" or "Fuji Superia" gives a warm, analog feel that screams authenticity.

For realistic skin and textures: Add language like "visible pores, subtle skin texture, age-appropriate fine lines, natural skin finish without excessive smoothing." AI models tend to over-smooth skin by default, and this explicitly counteracts that tendency.

This Works on FLUX Too

The camera filename technique is not limited to Midjourney. It has been confirmed to work on FLUX 1.1 Pro as well, with results described as "nearly indistinguishable from actual photos." On FLUX, the numbered sequence format (like 1237162761.png) also works alongside the standard camera filename formats.

A Word About Responsible Use

As AI images become harder and harder to distinguish from real photographs, it is worth thinking about how you use these techniques. The camera filename trick produces results that many people genuinely cannot tell apart from real photos. That is powerful, and it is also a responsibility. Always be transparent about AI-generated content, especially when sharing images publicly. The tools are incredible, and they deserve to be used honestly.

Happy creating!