Create an action figure from the photo. It must be visualised in a realistic way. There should be accessories next to the figure like a UX designer have, Macbook Pro, a camera, drawing tablet, headset etc. Add a hole to the top of the box in the action figure. Also write the text “UX Mate” and below it “Keep Learning! Keep Designing
Use this image to create a picture of a action figure toy of a construction worker in a blister package from head to toe with accessories including a hammer, a staple gun and a ladder. The package should read “Kirk The Handy Man”
Create a realistic image of a toy action figure box. The box should be designed in a toy-equipment/action-figure style, with a cut-out window at the top like classic action figure packaging. The main color of the box and moleskine notebook should match the color of my jacket (referenced visually). Add colorful Mexican skull decorations across the box for a vibrant and artistic flair. Inside the box, include a “Your name” action figure, posed heroically. Next to the figure, arrange the following “equipment” in a stylized layout: • item 1 • item 2 … On the box, write: “Your name” (bold title font) Underneath: “Your role or anything else” The entire scene should look like a real product mockup, highly realistic, lit like a studio product photo. On the box, write: “Your name” (bold title font) Underneath: “Your role or description” The entire scene should look like a real product mockup, highly realistic, lit like a studio product photo. Prompt on Kling AI The figure steps out of its toy packaging and begins walking forward. As he continues to walk, the camera gradually zooms out in sync with his movement.
“Create image. Create a toy of the person in the photo. Let it be an action figure. Next to the figure, there should be the toy’s equipment, each in its individual blisters. 1) a book called “Tecnoforma”. 2) A 3-headed dog with a tag that says “Troika” and a bone at its feet with word “austerity” written on it. 3) a three-headed Hydra with with a tag called “Geringonça”. 4) a book titled “D. Sebastião”. Don’t repeat the equipment under any circumstance. The card holding the blister should be strong orange. Also, on top of the box, write ‘Pedro Passos Coelho’ and underneath it, ‘PSD action figure’. The figure and equipment must all be inside blisters. Visualize this in a realistic way.”
In video terms gamut is normally related to as the full range of colours and brightness that can be either captured or displayed.
Generally speaking all color gamuts recommendations are trying to define a reasonable level of color representation based on available technology and hardware. REC-601 represents the old TVs. REC-709 is currently the most distributed solution. P3 is mainly available in movie theaters and is now being adopted in some of the best new 4K HDR TVs. Rec2020 (a wider space than P3 that improves on visibke color representation) and ACES (the full coverage of visible color) are other common standards which see major hardware development these days.
To compare and visualize different solution (across video and printing solutions), most developers use the CIE color model chart as a reference.
The CIE color model is a color space model created by the International Commission on Illumination known as the Commission Internationale de l’Elcairage (CIE) in 1931. It is also known as the CIE XYZ color space or the CIE 1931 XYZ color space.
This chart represents the first defined quantitative link between distributions of wavelengths in the electromagnetic visible spectrum, and physiologically perceived colors in human color vision. Or basically, the range of color a typical human eye can perceive through visible light.
Note that while the human perception is quite wide, and generally speaking biased towards greens (we are apes after all), the amount of colors available through nature, generated through light reflection, tend to be a much smaller section. This is defined by the Pointer’s Chart.
In short. Color gamut is a representation of color coverage, used to describe data stored in images against available hardware and viewer technologies.
The CIE 1931 standard has been replaced by a CIE 1976 standard. Below we can see the significance of this.
People have observed that the biggest issue with CIE 1931 is the lack of uniformity with chromaticity, the three dimension color space in rectangular coordinates is not visually uniformed.
The CIE 1976 (also called CIELUV) was created by the CIE in 1976. It was put forward in an attempt to provide a more uniform color spacing than CIE 1931 for colors at approximately the same luminance
The CIE 1976 standard colour space is more linear and variations in perceived colour between different people has also been reduced. The disproportionately large green-turquoise area in CIE 1931, which cannot be generated with existing computer screens, has been reduced.
If we move from CIE 1931 to the CIE 1976 standard colour space we can see that the improvements made in the gamut for the “new” iPad screen (as compared to the “old” iPad 2) are more evident in the CIE 1976 colour space than in the CIE 1931 colour space, particularly in the blues from aqua to deep blue.
Despite its age, CIE 1931, named for the year of its adoption, remains a well-worn and familiar shorthand throughout the display industry. CIE 1931 is the primary language of customers. When a customer says that their current display “can do 72% of NTSC,” they implicitly mean 72% of NTSC 1953 color gamut as mapped against CIE 1931.
The way humans see the world… until we have a way to describe something, even something so fundamental as a colour, we may not even notice that something it’s there.
Ancient languages didn’t have a word for blue — not Greek, not Chinese, not Japanese, not Hebrew, not Icelandic cultures. And without a word for the colour, there’s evidence that they may not have seen it at all. https://www.wnycstudios.org/story/211119-colors
Every language first had a word for black and for white, or dark and light. The next word for a colour to come into existence — in every language studied around the world — was red, the colour of blood and wine. After red, historically, yellow appears, and later, green (though in a couple of languages, yellow and green switch places). The last of these colours to appear in every language is blue.
The only ancient culture to develop a word for blue was the Egyptians — and as it happens, they were also the only culture that had a way to produce a blue dye. https://mymodernmet.com/shades-of-blue-color-history/
True blue hues are rare in the natural world because synthesizing pigments that absorb longer-wavelength light (reds and yellows) while reflecting shorter-wavelength blue light requires exceptionally elaborate molecular structures—biochemical feats that most plants and animals simply don’t undertake.
When you gaze at a blueberry’s deep blue surface, you’re actually seeing structural coloration rather than a true blue pigment. A fine, waxy bloom on the berry’s skin contains nanostructures that preferentially scatter blue and violet light, giving the fruit its signature blue sheen even though its inherent pigment is reddish.
Similarly, many of nature’s most striking blues—like those of blue jays and morpho butterflies—arise not from blue pigments but from microscopic architectures in feathers or wing scales. These tiny ridges and air pockets manipulate incoming light so that blue wavelengths emerge most prominently, creating vivid, angle-dependent colors through scattering rather than pigment alone.
“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.”
RGBW (RGB + White) LED strip uses a 4-in-1 LED chip made up of red, green, blue, and white.
RGBWW (RGB + White + Warm White) LED strip uses either a 5-in-1 LED chip with red, green, blue, white, and warm white for color mixing. The only difference between RGBW and RGBWW is the intensity of the white color. The term RGBCCT consists of RGB and CCT. CCT (Correlated Color Temperature) means that the color temperature of the led strip light can be adjusted to change between warm white and white. Thus, RGBWW strip light is another name of RGBCCT strip.
RGBCW is the acronym for Red, Green, Blue, Cold, and Warm. These 5-in-1 chips are used in supper bright smart LED lighting products
In the retina, photoreceptors, bipolar cells, and horizontal cells work together to process visual information before it reaches the brain. Here’s how each cell type contributes to vision:
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