Seasons · step by step

What season am I? A method, not a quiz.

Four questions, asked in the right order, get you to a likely season and its closest neighbour. Here's how to answer them at home, which photo mistakes skew the result, and when to trust what you find.

11 min read11 sources, each linkedBy the DayDrape teamLast reviewed

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The short answer

  • Ask four questions, in this order: how light or deep is your colouring, how much contrast is there between your skin, hair and eyes, how vivid or muted is it, and does it lean warm or cool?
  • Your strongest trait picks the family (Light, Deep, Bright, Soft, Warm or Cool), and the next one picks between two seasons. That gets you to one of twelve.
  • Always test the runner-up. On a public benchmark, the best computer models matched the human label only about 55% of the time, but the label was in their top two picks about 81–85% of the time.6,7 Close calls are normal.
  • Light and photos are the biggest source of error. Judge in daylight, in a mirror, and don't trust a single selfie.
  • Treat your season as a useful shortcut, not a fixed fact about you.

"What season am I?" sounds like it should have a quick answer, and most online quizzes give you one in ten taps. The trouble is that the quizzes ask you to judge your undertone first, which is the trait people are worst at judging,1 and they rarely tell you how close you came to the next season along. This guide works the other way round: easiest traits first, warmth last, and a check against your nearest neighbours at the end. If you're new to the idea, start with seasonal colour analysis, explained.

Before you start: set up the light

Every step below compares colours by eye, so the light has to stay the same throughout. Most bad results come from here.

  • Daylight from a window, facing it, on a bright but not sunny day. Not a warm bulb, not direct sun, not next to a coloured wall.
  • Bare skin. No foundation, tinted moisturiser or bronzer. Hair pulled back, and a white towel or T-shirt over your clothes.
  • Use a mirror, not your phone screen. Phones adjust brightness and colour automatically. If you do take photos to compare, turn off filters and beauty modes, and keep the same distance and angle for every shot. In one study of colour cards matched to a range of skin tones, simply changing the phone's angle shifted the measured colour by more than one CIELAB unit, and using the flash didn't generally fix it.2
  • Be extra wary of photos if your skin is deep. Cameras make larger exposure and white-balance errors on darker skin,4 and a lab study of facial skin colour found that the processed JPG files most cameras save were less stable than raw files.3

Step 1: How light or deep are you?

Start here because it's the trait people judge most consistently. In a 2024 study, individual raters agreed strongly on how light or dark skin was in a photo, even though they barely agreed on its undertone.1 Look at your skin, hair and eyes together, not just your skin. Then hold a light and a deep version of the same colour under your chin, one after the other.

  • Powder blue · navy
  • Pale pink · burgundy
  • Stone · dark brown

Illustrative pairs only, not a season palette. On-screen swatches are approximate, so use real fabric. Light is on the left of each pair.

If the light side wins clearly, Light may be your strongest trait. If the deep side wins clearly, it may be Deep. If neither wins, lightness isn't your headline trait, which is just as useful to know.

Step 2: How much contrast?

Contrast is the gap between your skin, your hair and your eyes. Very dark hair with fair skin is high contrast. Hair, skin and eyes of a similar depth are low contrast. A practitioners' trick is to take a black-and-white photo of your face in daylight: if your features jump out, you're higher contrast; if they blend, you're lower. (It's not a lab method, but greyscale removes colour, so you see only light and dark.)

Hair and eyes matter more than many people expect. In a 2026 study that modelled seasons from skin, hair and eye colour, hair and eye features told the model more than skin did. The authors note that this is specific to their dataset, and suggest uncontrolled lighting may have distorted the skin readings.7 If you dye your hair, judge contrast with your natural colour in mind, or at least note that the result may change.

Contrast doesn't name a family by itself, but it's a strong hint. High contrast points towards Deep or Bright. Low contrast points towards Light or Soft.

Step 3: How vivid or muted?

Chroma (also called clarity or saturation) is how pure a colour is, compared with a greyed version of the same hue. Hold a vivid and a muted version of the same colour against your face. You're looking at your skin, not the fabric: which one makes your face look clearer and more even, and which one seems to sit on top of you or drain you?

  • Bright teal · greyed teal
  • Pure red · dusty red
  • Emerald · sage

Illustrative pairs only, not a season palette. Vivid is on the left of each pair.

A clear win for the vivid side suggests Bright. A clear win for the muted side suggests Soft. Surroundings change how skin looks, which is why this works at all: in one study, the same faces were judged more or less even-toned depending on the colours around them.5

Step 4: Warm or cool?

Last, and on purpose. Warmth is whether your colouring leans golden or rosy, and it's the hardest trait to read by eye. In the 2024 study above, individual raters agreed on red–yellow undertone only weakly (intraclass correlations of about 0.15–0.16), though averaging many raters recovered a consistent signal.1 Use warm and cool pairs (cream and pure white, camel and grey, gold and silver), and see our full guide to finding your undertone, including why the vein test misleads.

If warmth wins every pair by a mile, Warm or Cool may be your strongest trait. More often it's a lean, and warmth acts as the tie-breaker between two seasons.

Putting it together: family, then season

In a common twelve-season layout, each season is named after its strongest trait, and a second trait decides between two neighbours. So pick the trait that came through most clearly in steps 1–4, then use the next-clearest to choose between the pair.

Decision flow: from your strongest trait to one of twelve seasonsSix rows. Light: warmer leads to Light Spring, cooler to Light Summer. Deep: warmer leads to Deep (Dark) Autumn, cooler to Deep (Dark) Winter. Bright: warmer leads to Bright (Clear) Spring, cooler to Bright (Clear) Winter. Soft: warmer leads to Soft Autumn, cooler to Soft Summer. Warm: lighter or brighter leads to Warm (True) Spring, deeper or softer to Warm (True) Autumn. Cool: lighter or softer leads to Cool (True) Summer, deeper or brighter to Cool (True) Winter. Finally, test the runner-up next door. Which trait stands out most? then let the next-clearest trait choose Lightlight overallwarmer → Light Springcooler → Light Summer Deepdeep, often contrastingwarmer → Deep (Dark) Autumncooler → Deep (Dark) Winter Brightvivid, high contrastwarmer → Bright (Clear) Springcooler → Bright (Clear) Winter Softmuted, blendedwarmer → Soft Autumncooler → Soft Summer Warmclearly goldenlighter → Warm (True) Springdeeper → Warm (True) Autumn Coolclearly rosylighter → Cool (True) Summerdeeper → Cool (True) Winter then test the runner-up next door
A simplified twelve-season flow. Names vary between systems, so we give both common names. For Warm and Cool, "lighter" also covers brighter and "deeper" also covers softer. This is a way to organise what you see, not a measurement.

A few worked examples. Fair skin, light hair, low contrast and a slight rosy lean: Light first, cool second, so Light Summer. Very dark hair, deep eyes, high contrast, nothing especially golden: Deep first, cool second, so Deep (Dark) Winter. Everything blended and muted, with a golden lean: Soft first, warm second, so Soft Autumn.

Check the neighbours

Your first answer is a starting point. Every season has two close neighbours, and they're the seasons people most often confuse:

  • Same strongest trait, opposite temperature. Soft Autumn and Soft Summer are both muted first; they differ on warmth. Likewise Light Spring and Light Summer, Deep (Dark) Autumn and Deep (Dark) Winter, and Bright (Clear) Spring and Bright (Clear) Winter.
  • Same family, different strongest trait. Soft Autumn sits next to Warm (True) Autumn: both warm and muted, but in a different order of strength.

To check, run the drape pairs from the step that separates the two. If you're torn between Soft Autumn and Soft Summer, repeat the warmth pairs. If you're torn between Soft Autumn and Warm (True) Autumn, repeat the vivid-versus-muted pairs with warm colours only.

Don't worry if it stays close. On Deep Armocromia, a public benchmark of 4,920 celebrity face photos labelled with four seasons by annotators trained on expert examples, the best computer models agreed with the human label only about 55% of the time on the 912-photo test set, where guessing would score 25%. Yet the label was among their top two picks about 81–85% of the time.6,7 Those were uncontrolled photos and human labels, not measurements, but the gap suggests that many faces sit close to a neighbouring season. One 2026 model was weakest of all at spotting Springs, identifying fewer than 42% of them.7

Photo pitfalls that skew the answer

  • Warm bulbs and golden hour make almost everyone look warmer. Overcast light or a blue wall can do the opposite. Your brain partly corrects for the light, which is why two people can see the same photo differently.11
  • Filters, beauty modes and auto-enhance change skin colour and smooth away contrast. Turn them all off.
  • Angle and distance. Tilting the phone changed measured colour in the study above, and distance changed lightness.2 Shoot straight on, at arm's length, every time.
  • One photo. Cameras make their own exposure and white-balance choices, and those choices are less reliable on darker skin.4 Compare several photos, taken minutes apart in the same light, before you believe any of them.
  • Make-up, fake tan, recent sun and dyed hair all move the answer. Note them, or wait until they've faded.

When to trust your result

Trust it more when the same answer comes up on different days, in the same daylight set-up, and when the drape pairs agree with each other. Trust it less when the answer changes with the room you're in, or when you've only judged one photo.

It's also worth remembering what a season is. The seasons are labels for combinations of traits, and the systems don't fully agree with each other. A 1986 thesis comparing published colour-analysis books found "few similarities in color recommendations even among authors using the same name categories".8 A 2026 study of influencer-assigned labels found that a simple warm/cool split was much easier to predict than the four seasons, which overlapped heavily.9 So if you land between two seasons, the honest answer is "between two seasons", and you can borrow from both.

How DayDrape works it out

We're building DayDrape to run this same method with measurements instead of guesswork. The app checks your light before you start, takes three photos that must agree with each other before it gives a result, and can use a plain sheet of white paper as a reference if you have one (it's optional). It measures lightness, contrast, chroma and warmth in CIELAB,10 then shows your season alongside the runner-up, with the measurements behind both. It's still in development.

Sources

  1. Branigan, A. R., Nunez, J. G., Khan, M. A. & Gordon, R. A. (2024). Variation in skin red and yellow undertone: reliability of ratings and relevance for perceived social experiences. Social Psychology Quarterly. pmc.ncbi.nlm.nih.gov
  2. Cronin, A., Tkaczyk, E. R., Hussain, I., Bowden, A. & Saknite, I. (2023). Effect of camera distance and angle on color of diverse skin tone-based standards in smartphone photos. Journal of Biophotonics, 16(6), e202200381. doi.org/10.1002/jbio.202200381 (open access: PMC10247498)
  3. He, R., Xiao, K., Pointer, M., Bressler, Y., Liu, Z. & Lu, Y. (2022). Development of an image-based measurement system for human facial skin colour. Color Research & Application, 47(2), 288–300. doi.org/10.1002/col.22737
  4. Borek, M., Schwartz, A. & Spooner, A. (2024). Evaluating camera performance in face-present scenes with diverse skin tones. Electronic Imaging, 36(9). doi.org/10.2352/EI.2024.36.9.IQSP-260
  5. Batres, C. & Russell, R. (2026). Perceived skin evenness is influenced by background color and hair color. Perception. doi.org/10.1177/03010066261474995
  6. Stacchio, L., Paolanti, M., Spigarelli, F. & Frontoni, E. (2025). Deep Armocromia: a novel dataset for face seasonal color analysis and classification. In Computer Vision – ECCV 2024 Workshops, Lecture Notes in Computer Science 15623, 352–367. Springer. doi.org/10.1007/978-3-031-91569-7_22. Four-season results (FaRL64: accuracy 0.554, top-two 0.808) as reported in the authors' ECCV 2024 poster.
  7. Ou, N. Y. P. & Chan, J. H. (2026). Lumina: seasonal color analysis system with explainable machine learning. Proceedings of the 14th International Conference on Advances in Information Technology (IAIT '26), Article 24, 1–6. ACM. doi.org/10.1145/3816713.3818796. Tuned XGBoost: accuracy 0.552, top-two 0.843; ensemble: 0.556, top-two 0.850; Spring recall below 0.42.
  8. Collin, E. E. (1986). Development of a methodology for analyzing the color content of a selected group of printed color analysis systems. MSc thesis, Oregon State University. ir.library.oregonstate.edu
  9. Kawase, A., Adachi, J. & Nagashima, K. (2026). Personal colour between perceptual space and social practice. Colour Turn, 2(1). journal.colourturn.net
  10. Ly, B. C. K., Dyer, E. B., Feig, J. L., Chien, A. L. & Del Bino, S. (2020). Research techniques made simple: cutaneous colorimetry. Journal of Investigative Dermatology, 140(1), 3–12. doi.org/10.1016/j.jid.2019.11.003
  11. Brainard, D. H. & Hurlbert, A. C. (2015). Colour vision: understanding #TheDress. Current Biology, 25(13), R551–R554. doi.org/10.1016/j.cub.2015.05.020

This article is general styling information. Your season is a styling shortcut, not a fixed or medical fact about you. We link every source we rely on; if you spot an error, tell us and we'll correct it.

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