COMPOSITION
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HuggingFace ai-comic-factory – a FREE AI Comic Book CreatorRead more: HuggingFace ai-comic-factory – a FREE AI Comic Book Creatorhttps://huggingface.co/spaces/jbilcke-hf/ai-comic-factory this is the epic story of a group of talented digital artists trying to overcame daily technical challenges to achieve incredibly photorealistic projects of monsters and aliens 
DESIGN
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Kristina Kashtanova – “This is how GPT-4 sees and hears itself”Read more: Kristina Kashtanova – “This is how GPT-4 sees and hears itself”“I used GPT-4 to describe itself. Then I used its description to generate an image, a video based on this image and a soundtrack. Tools I used: GPT-4, Midjourney, Kaiber AI, Mubert, RunwayML This is the description I used that GPT-4 had of itself as a prompt to text-to-image, image-to-video, and text-to-music. I put the video and sound together in RunwayML. GPT-4 described itself as: “Imagine a sleek, metallic sphere with a smooth surface, representing the vast knowledge contained within the model. The sphere emits a soft, pulsating glow that shifts between various colors, symbolizing the dynamic nature of the AI as it processes information and generates responses. The sphere appears to float in a digital environment, surrounded by streams of data and code, reflecting the complex algorithms and computing power behind the AI” 
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AI Dresses by MaryAnnaRead more: AI Dresses by MaryAnnahttps://www.linkedin.com/feed/update/urn:li:activity:7015985798567067648 Created by Discord user: @MaryAnna 
COLOR
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Colour – MacBeth Chart Checker DetectionRead more: Colour – MacBeth Chart Checker Detectiongithub.com/colour-science/colour-checker-detection A Python package implementing various colour checker detection algorithms and related utilities.  
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The 7 key elements of brand identity design + 10 corporate identity examplesRead more: The 7 key elements of brand identity design + 10 corporate identity exampleswww.lucidpress.com/blog/the-7-key-elements-of-brand-identity-design 1. Clear brand purpose and positioning 2. Thorough market research 3. Likable brand personality 4. Memorable logo 5. Attractive color palette 6. Professional typography 7. On-brand supporting graphics 
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Stefan Ringelschwandtner – LUT Inspector toolRead more: Stefan Ringelschwandtner – LUT Inspector toolIt lets you load any .cube LUT right in your browser, see the RGB curves, and use a split view on the Granger Test Image to compare the original vs. LUT-applied version in real time — perfect for spotting hue shifts, saturation changes, and contrast tweaks. https://mononodes.com/lut-inspector/  
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Brett Jones / Phil Reyneri (Lightform) / Philipp7pc: The study of Projection Mapping through ProjectorsRead more: Brett Jones / Phil Reyneri (Lightform) / Philipp7pc: The study of Projection Mapping through ProjectorsVideo Projection Tool Software 
 https://hcgilje.wordpress.com/vpt/https://www.projectorpoint.co.uk/news/how-bright-should-my-projector-be/ http://www.adwindowscreens.com/the_calculator/ heavym 
 https://heavym.net/en/MadMapper 
 https://madmapper.com/
LIGHTING
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7 Easy Portrait Lighting SetupsRead more: 7 Easy Portrait Lighting SetupsButterfly Loop Rembrandt Split Rim Broad Short 
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Beeble Switchlight’s Plugin for Foundry NukeRead more: Beeble Switchlight’s Plugin for Foundry Nukehttps://www.cutout.pro/learn/beeble-switchlight/ https://www.switchlight-api.beeble.ai/pricing https://www.switchlight-api.beeble.ai https://github.com/beeble-ai/SwitchLight-Studio https://beeble.ai/terms-of-use https://www.switchlight-api.beeble.ai/docs 
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Photography basics: Exposure Value vs Photographic Exposure vs Il/Luminance vs Pixel luminance measurementsRead more: Photography basics: Exposure Value vs Photographic Exposure vs Il/Luminance vs Pixel luminance measurementsAlso see: https://www.pixelsham.com/2015/05/16/how-aperture-shutter-speed-and-iso-affect-your-photos/ 
 In photography, exposure value (EV) is a number that represents a combination of a camera’s shutter speed and f-number, such that all combinations that yield the same exposure have the same EV (for any fixed scene luminance). The EV concept was developed in an attempt to simplify choosing among combinations of equivalent camera settings. Although all camera settings with the same EV nominally give the same exposure, they do not necessarily give the same picture. EV is also used to indicate an interval on the photographic exposure scale. 1 EV corresponding to a standard power-of-2 exposure step, commonly referred to as a stop 
 EV 0 corresponds to an exposure time of 1 sec and a relative aperture of f/1.0. If the EV is known, it can be used to select combinations of exposure time and f-number.Note EV does not equal to photographic exposure. Photographic Exposure is defined as how much light hits the camera’s sensor. It depends on the camera settings mainly aperture and shutter speed. Exposure value (known as EV) is a number that represents the exposure setting of the camera. 
 Thus, strictly, EV is not a measure of luminance (indirect or reflected exposure) or illuminance (incidentl exposure); rather, an EV corresponds to a luminance (or illuminance) for which a camera with a given ISO speed would use the indicated EV to obtain the nominally correct exposure. Nonetheless, it is common practice among photographic equipment manufacturers to express luminance in EV for ISO 100 speed, as when specifying metering range or autofocus sensitivity.
 The exposure depends on two things: how much light gets through the lenses to the camera’s sensor and for how long the sensor is exposed. The former is a function of the aperture value while the latter is a function of the shutter speed. Exposure value is a number that represents this potential amount of light that could hit the sensor. It is important to understand that exposure value is a measure of how exposed the sensor is to light and not a measure of how much light actually hits the sensor. The exposure value is independent of how lit the scene is. For example a pair of aperture value and shutter speed represents the same exposure value both if the camera is used during a very bright day or during a dark night.
 Each exposure value number represents all the possible shutter and aperture settings that result in the same exposure. Although the exposure value is the same for different combinations of aperture values and shutter speeds the resulting photo can be very different (the aperture controls the depth of field while shutter speed controls how much motion is captured).
 EV 0.0 is defined as the exposure when setting the aperture to f-number 1.0 and the shutter speed to 1 second. All other exposure values are relative to that number. Exposure values are on a base two logarithmic scale. This means that every single step of EV – plus or minus 1 – represents the exposure (actual light that hits the sensor) being halved or doubled.Formulas(more…)
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Narcis Calin’s Galaxy Engine – A free, open source simulation softwareRead more: Narcis Calin’s Galaxy Engine – A free, open source simulation softwareThis 2025 I decided to start learning how to code, so I installed Visual Studio and I started looking into C++. After days of watching tutorials and guides about the basics of C++ and programming, I decided to make something physics-related. I started with a dot that fell to the ground and then I wanted to simulate gravitational attraction, so I made 2 circles attracting each other. I thought it was really cool to see something I made with code actually work, so I kept building on top of that small, basic program. And here we are after roughly 8 months of learning programming. This is Galaxy Engine, and it is a simulation software I have been making ever since I started my learning journey. It currently can simulate gravity, dark matter, galaxies, the Big Bang, temperature, fluid dynamics, breakable solids, planetary interactions, etc. The program can run many tens of thousands of particles in real time on the CPU thanks to the Barnes-Hut algorithm, mixed with Morton curves. It also includes its own PBR 2D path tracer with BVH optimizations. The path tracer can simulate a bunch of stuff like diffuse lighting, specular reflections, refraction, internal reflection, fresnel, emission, dispersion, roughness, IOR, nested IOR and more! I tried to make the path tracer closer to traditional 3D render engines like V-Ray. I honestly never imagined I would go this far with programming, and it has been an amazing learning experience so far. I think that mixing this knowledge with my 3D knowledge can unlock countless new possibilities. In case you are curious about Galaxy Engine, I made it completely free and Open-Source so that anyone can build and compile it locally! You can find the source code in GitHub https://github.com/NarcisCalin/Galaxy-Engine 
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DiffusionLight: HDRI Light Probes for Free by Painting a Chrome BallRead more: DiffusionLight: HDRI Light Probes for Free by Painting a Chrome Ballhttps://diffusionlight.github.io/ https://github.com/DiffusionLight/DiffusionLight https://github.com/DiffusionLight/DiffusionLight?tab=MIT-1-ov-file#readme https://colab.research.google.com/drive/15pC4qb9mEtRYsW3utXkk-jnaeVxUy-0S “a simple yet effective technique to estimate lighting in a single input image. Current techniques rely heavily on HDR panorama datasets to train neural networks to regress an input with limited field-of-view to a full environment map. However, these approaches often struggle with real-world, uncontrolled settings due to the limited diversity and size of their datasets. To address this problem, we leverage diffusion models trained on billions of standard images to render a chrome ball into the input image. Despite its simplicity, this task remains challenging: the diffusion models often insert incorrect or inconsistent objects and cannot readily generate images in HDR format. Our research uncovers a surprising relationship between the appearance of chrome balls and the initial diffusion noise map, which we utilize to consistently generate high-quality chrome balls. We further fine-tune an LDR difusion model (Stable Diffusion XL) with LoRA, enabling it to perform exposure bracketing for HDR light estimation. Our method produces convincing light estimates across diverse settings and demonstrates superior generalization to in-the-wild scenarios.”  
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