COMPOSITION
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Mastering Camera Shots and Angles: A Guide for Filmmakers
Read more: Mastering Camera Shots and Angles: A Guide for Filmmakershttps://website.ltx.studio/blog/mastering-camera-shots-and-angles
1. Extreme Wide Shot

2. Wide Shot

3. Medium Shot

4. Close Up

5. Extreme Close Up

DESIGN
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Disco Diffusion V4.1 Google Colab, Dall-E, Starryai – creating images with AI
Read more: Disco Diffusion V4.1 Google Colab, Dall-E, Starryai – creating images with AIDisco Diffusion (DD) is a Google Colab Notebook which leverages an AI Image generating technique called CLIP-Guided Diffusion to allow you to create compelling and beautiful images from just text inputs. Created by Somnai, augmented by Gandamu, and building on the work of RiversHaveWings, nshepperd, and many others.
Phone app: https://www.starryai.com/
docs.google.com/document/d/1l8s7uS2dGqjztYSjPpzlmXLjl5PM3IGkRWI3IiCuK7g
colab.research.google.com/drive/1sHfRn5Y0YKYKi1k-ifUSBFRNJ8_1sa39
Colab, or “Colaboratory”, allows you to write and execute Python in your browser, with
– Zero configuration required
– Access to GPUs free of charge
– Easy sharinghttps://80.lv/articles/a-beautiful-roman-villa-made-with-disco-diffusion-5-2/

COLOR
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colorhunt.co
Read more: colorhunt.coColor Hunt is a free and open platform for color inspiration with thousands of trendy hand-picked color palettes.

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No one could see the colour blue until modern times
Read more: No one could see the colour blue until modern timeshttps://www.businessinsider.com/what-is-blue-and-how-do-we-see-color-2015-2

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-colorsEvery 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.
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Composition – cinematography Cheat Sheet
Read more: Composition – cinematography Cheat Sheet
Where is our eye attracted first? Why?
Size. Focus. Lighting. Color.
Size. Mr. White (Harvey Keitel) on the right.
Focus. He’s one of the two objects in focus.
Lighting. Mr. White is large and in focus and Mr. Pink (Steve Buscemi) is highlighted by
a shaft of light.
Color. Both are black and white but the read on Mr. White’s shirt now really stands out.
(more…)
What type of lighting? -
SecretWeapons MixBox – a practical library for paint-like digital color mixing
Read more: SecretWeapons MixBox – a practical library for paint-like digital color mixingInternally, Mixbox treats colors as real-life pigments using the Kubelka & Munk theory to predict realistic color behavior.
https://scrtwpns.com/mixbox/painter/
https://scrtwpns.com/mixbox.pdf
https://github.com/scrtwpns/mixbox
https://scrtwpns.com/mixbox/docs/
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Photography Basics : Spectral Sensitivity Estimation Without a Camera
Read more: Photography Basics : Spectral Sensitivity Estimation Without a Camerahttps://color-lab-eilat.github.io/Spectral-sensitivity-estimation-web/
A number of problems in computer vision and related fields would be mitigated if camera spectral sensitivities were known. As consumer cameras are not designed for high-precision visual tasks, manufacturers do not disclose spectral sensitivities. Their estimation requires a costly optical setup, which triggered researchers to come up with numerous indirect methods that aim to lower cost and complexity by using color targets. However, the use of color targets gives rise to new complications that make the estimation more difficult, and consequently, there currently exists no simple, low-cost, robust go-to method for spectral sensitivity estimation that non-specialized research labs can adopt. Furthermore, even if not limited by hardware or cost, researchers frequently work with imagery from multiple cameras that they do not have in their possession.
To provide a practical solution to this problem, we propose a framework for spectral sensitivity estimation that not only does not require any hardware (including a color target), but also does not require physical access to the camera itself. Similar to other work, we formulate an optimization problem that minimizes a two-term objective function: a camera-specific term from a system of equations, and a universal term that bounds the solution space.
Different than other work, we utilize publicly available high-quality calibration data to construct both terms. We use the colorimetric mapping matrices provided by the Adobe DNG Converter to formulate the camera-specific system of equations, and constrain the solutions using an autoencoder trained on a database of ground-truth curves. On average, we achieve reconstruction errors as low as those that can arise due to manufacturing imperfections between two copies of the same camera. We provide predicted sensitivities for more than 1,000 cameras that the Adobe DNG Converter currently supports, and discuss which tasks can become trivial when camera responses are available.

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RawTherapee – a free, open source, cross-platform raw image and HDRi processing program
Read more: RawTherapee – a free, open source, cross-platform raw image and HDRi processing program5.10 of this tool includes excellent tools to clean up cr2 and cr3 used on set to support HDRI processing.
Converting raw to AcesCG 32 bit tiffs with metadata.
LIGHTING
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Convert between light exposure and intensity
Read more: Convert between light exposure and intensityimport math,sys def Exposure2Intensity(exposure): exp = float(exposure) result = math.pow(2,exp) print(result) Exposure2Intensity(0) def Intensity2Exposure(intensity): inarg = float(intensity) if inarg == 0: print("Exposure of zero intensity is undefined.") return if inarg < 1e-323: inarg = max(inarg, 1e-323) print("Exposure of negative intensities is undefined. Clamping to a very small value instead (1e-323)") result = math.log(inarg, 2) print(result) Intensity2Exposure(0.1)Why Exposure?
Exposure is a stop value that multiplies the intensity by 2 to the power of the stop. Increasing exposure by 1 results in double the amount of light.
Artists think in “stops.” Doubling or halving brightness is easy math and common in grading and look-dev.
Exposure counts doublings in whole stops:- +1 stop = ×2 brightness
- −1 stop = ×0.5 brightness
This gives perceptually even controls across both bright and dark values.
Why Intensity?
Intensity is linear.
It’s what render engines and compositors expect when:- Summing values
- Averaging pixels
- Multiplying or filtering pixel data
Use intensity when you need the actual math on pixel/light data.
Formulas (from your Python)
- Intensity from exposure: intensity = 2**exposure
- Exposure from intensity: exposure = log₂(intensity)
Guardrails:
- Intensity must be > 0 to compute exposure.
- If intensity = 0 → exposure is undefined.
- Clamp tiny values (e.g.
1e−323) before using log₂.
Use Exposure (stops) when…
- You want artist-friendly sliders (−5…+5 stops)
- Adjusting look-dev or grading in even stops
- Matching plates with quick ±1 stop tweaks
- Tweening brightness changes smoothly across ranges
Use Intensity (linear) when…
- Storing raw pixel/light values
- Multiplying textures or lights by a gain
- Performing sums, averages, and filters
- Feeding values to render engines expecting linear data
Examples
- +2 stops → 2**2 = 4.0 (×4)
- +1 stop → 2**1 = 2.0 (×2)
- 0 stop → 2**0 = 1.0 (×1)
- −1 stop → 2**(−1) = 0.5 (×0.5)
- −2 stops → 2**(−2) = 0.25 (×0.25)
- Intensity 0.1 → exposure = log₂(0.1) ≈ −3.32
Rule of thumb
Think in stops (exposure) for controls and matching.
Compute in linear (intensity) for rendering and math.
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