taxonomy.py

"""
CamoNet pattern taxonomy.

Each pattern has:
  - id:       short slug used as the class label (stable, snake_case)
  - name:     human-readable display name
  - origin:   country / military of origin
  - era:      rough date range of issue
  - family:   visual family (woodland / desert / arid / digital / brushstroke / blob / multi-terrain)
  - notes:    short blurb for the model card

Keep this list curated, not exhaustive. ~40 patterns is the sweet spot:
big enough to be impressive, small enough to actually train with limited data.
"""

from dataclasses import dataclass
from typing import Literal

Family = Literal[
    "woodland", "desert", "arid", "digital", "brushstroke",
    "blob", "multi-terrain", "winter", "urban", "naval"
]


@dataclass(frozen=True)
class Pattern:
    id: str
    name: str
    origin: str
    era: str
    family: Family
    notes: str


PATTERNS: list[Pattern] = [
    # --- United States ---
    Pattern("us_erdl", "ERDL", "United States", "1948-1980s", "woodland",
            "Early US 4-color woodland pattern, used in Vietnam."),
    Pattern("us_m81_woodland", "M81 Woodland", "United States", "1981-2006", "woodland",
            "Iconic 4-color US woodland; the BDU pattern."),
    Pattern("us_dcu_chocolate_chip", "Chocolate Chip (DBDU)", "United States", "1981-1991", "desert",
            "6-color desert with pebble-like spots; Gulf War era."),
    Pattern("us_dcu_3color", "3-Color Desert (DCU)", "United States", "1990-2000s", "desert",
            "Coffee-stain pattern that replaced Chocolate Chip."),
    Pattern("us_marpat_woodland", "MARPAT Woodland", "USMC", "2002-present", "digital",
            "USMC digital woodland; first widely-issued pixelated camo."),
    Pattern("us_marpat_desert", "MARPAT Desert", "USMC", "2002-present", "digital",
            "USMC digital desert variant of MARPAT."),
    Pattern("us_ucp", "UCP (ACU)", "US Army", "2004-2019", "digital",
            "Universal Camo Pattern; grey-green digital, controversially ineffective."),
    Pattern("us_multicam", "MultiCam", "United States (Crye)", "2010-present", "multi-terrain",
            "Crye Precision blended multi-environment pattern; OEF-CP, OCP."),
    Pattern("us_ocp_scorpion", "OCP Scorpion W2", "US Army", "2015-present", "multi-terrain",
            "Army's MultiCam-derivative replacement for UCP."),
    Pattern("us_aor1", "AOR1", "US Navy/NSW", "2010-present", "desert",
            "NSW desert digital, MARPAT-derived."),
    Pattern("us_aor2", "AOR2", "US Navy/NSW", "2010-present", "digital",
            "NSW woodland digital, MARPAT-derived."),
    Pattern("us_tigerstripe", "Tiger Stripe", "South Vietnam / US SF", "1962-1975", "brushstroke",
            "Asymmetric horizontal-stripe pattern; many regional variants."),

    # --- United Kingdom ---
    Pattern("uk_dpm_woodland", "DPM Woodland", "United Kingdom", "1968-2011", "brushstroke",
            "British Disruptive Pattern Material; brush-stroke 4-color."),
    Pattern("uk_dpm_desert", "DPM Desert", "United Kingdom", "1990-2011", "desert",
            "2-color desert DPM."),
    Pattern("uk_mtp", "MTP (Multi-Terrain Pattern)", "United Kingdom", "2010-present", "multi-terrain",
            "British MultiCam-derivative with DPM brush-stroke shapes."),

    # --- Germany ---
    Pattern("de_flecktarn", "Flecktarn", "Germany (Bundeswehr)", "1990-present", "blob",
            "5-color blob pattern; one of the most effective in temperate forest."),
    Pattern("de_tropentarn", "Tropentarn", "Germany (Bundeswehr)", "1990s-present", "desert",
            "3-color arid Flecktarn variant."),
    Pattern("de_splittertarn", "Splittertarn", "Germany (Wehrmacht)", "1931-1945", "blob",
            "WW2-era angular splinter pattern."),

    # --- USSR / Russia ---
    Pattern("ru_klmk", "KLMK", "USSR", "1968-1990s", "brushstroke",
            "Soviet 'silver leaf' sun-ray 2-color oversuit pattern."),
    Pattern("ru_ttsko", "TTsKO (Butan)", "USSR", "1984-2000s", "blob",
            "Three-color Soviet computer-generated pattern."),
    Pattern("ru_vsr_93", "VSR-93 (Flora)", "Russia", "1993-2000s", "brushstroke",
            "Vertical brush-stroke 'Flora' pattern."),
    Pattern("ru_emr_digital_flora", "EMR (Digital Flora)", "Russia", "2008-present", "digital",
            "Russian Armed Forces digital pattern; pixelated greens."),
    Pattern("ru_surpat", "SURPAT", "Russia (Survival Corps)", "2010s-present", "digital",
            "Commercial Russian multi-terrain digital."),
    Pattern("ru_partizan", "Partizan / Spectre", "Russia (SSO)", "2000s-present", "multi-terrain",
            "SSO Tactical 'leaf' pattern; layered foliage shapes."),

    # --- Other NATO / Western ---
    Pattern("ca_cadpat_tw", "CADPAT TW", "Canada", "1997-present", "digital",
            "Canadian Disruptive Pattern; first issued digital camo (predates MARPAT)."),
    Pattern("ca_cadpat_ar", "CADPAT AR", "Canada", "2000s-present", "desert",
            "Arid CADPAT variant."),
    Pattern("fr_cce", "CCE F1", "France", "1991-2010s", "woodland",
            "Centre Europe; French M81-style woodland."),
    Pattern("fr_daguet", "Daguet", "France", "1991-2010s", "desert",
            "French desert pattern, Gulf War era."),
    Pattern("it_vegetata", "Vegetata", "Italy", "2004-present", "woodland",
            "Italian 4-color fractal-style woodland."),
    Pattern("au_auscam", "AUSCAM (DPCU)", "Australia", "1982-2014", "blob",
            "Australian 'hearts and bunnies' 5-color blob pattern."),
    Pattern("au_amcu", "AMCU", "Australia", "2014-present", "multi-terrain",
            "Australian MultiCam-derivative replacement for DPCU."),
    Pattern("se_m90", "M90", "Sweden", "1990-present", "blob",
            "Swedish angular 4-color splinter; very distinctive."),
    Pattern("ch_taz_90", "TAZ 90", "Switzerland", "1990-present", "blob",
            "Swiss 5-color leaf/blob pattern."),
    Pattern("no_m75", "M75", "Norway", "1975-2000s", "blob",
            "Norwegian 3-color blob pattern."),

    # --- Asia ---
    Pattern("cn_type07_universal", "Type 07 Universal", "China (PLA)", "2007-present", "digital",
            "Chinese Type 07 woodland-leaning digital."),
    Pattern("cn_type07_desert", "Type 07 Desert", "China (PLA)", "2007-present", "digital",
            "Type 07 arid variant."),
    Pattern("kr_granite", "ROK Granite", "South Korea", "2014-present", "digital",
            "Korean digital pattern with granite-like color blocks."),
    Pattern("jp_jgsdf", "JGSDF Type II", "Japan", "1991-present", "blob",
            "Japan Ground SDF pinkish-brown tinted blob pattern."),

    # --- Commercial / specialty ---
    Pattern("commercial_kryptek_mandrake", "Kryptek Mandrake", "United States (commercial)", "2012-present", "multi-terrain",
            "Commercial layered reptilian-scale pattern."),
    Pattern("commercial_atacs_au", "A-TACS AU", "United States (commercial)", "2009-present", "arid",
            "Commercial arid-urban 'pixelated organic' pattern."),
]


PATTERN_BY_ID: dict[str, Pattern] = {p.id: p for p in PATTERNS}
LABELS: list[str] = [p.id for p in PATTERNS]
LABEL2ID: dict[str, int] = {label: i for i, label in enumerate(LABELS)}
ID2LABEL: dict[int, str] = {i: label for i, label in enumerate(LABELS)}
NUM_LABELS: int = len(LABELS)


if __name__ == "__main__":
    print(f"CamoNet taxonomy: {NUM_LABELS} patterns across {len(set(p.family for p in PATTERNS))} families")
    for fam in sorted(set(p.family for p in PATTERNS)):
        members = [p for p in PATTERNS if p.family == fam]
        print(f"  {fam:15s} ({len(members):2d}): {', '.join(m.id for m in members)}")