PROJECT NAME: RA1 VISION AI
SYSTEM STATUS: [ UNDER DEVELOPMENT ]
HARDWARE: RTX 4060 PYTHON 3.14

CORE VISION STRATEGY NO MEMORY HOOKS

OPERATING VIA DIRECT SCREEN-CAPTURE AND HARDWARE MOUSE/KEYBOARD DISPATCH. ZERO MEMORY INJECTION.

1. PERCEPTION
MSS / DXCAM (1280x720)
2. BRAIN
OPENCV + CUDA YOLO NANO
3. EXECUTION
DIRECTINPUT DRIVERS

SYSTEM ARCHITECTURE & PIPELINE LATENCY TARGET: < 15MS

FRAME SPLITTING & ROIs

TACTICAL VIEWPORT (0,0 → 0.78W) IS ISOLATED FROM COMMAND SIDEBAR (0.78W → 1.0W) TO PREVENT FALSE-POSITIVE TEMPLATE MATCHES.

HYBRID INFERENCE ENGINE

OPENCV NORMED MATCHING FOR UI SYMBOLS (< 2MS ON CPU); CUDA YOLOv11-NANO FOR VIEWPORT UNITS (~4MS ON RTX 4060).

RADAR MINIMAP PARSER

HSV COLOR-MASKING SEPARATES UNEXPLORED SHROUD (BLACK), FRIENDLY UNITS (GREEN), HOSTILES (RED), AND ORE DEPOSITS (GOLD).

SPATIAL CONTROL LOOP

DETECTED BOUNDING CENTERS ARE MAPPED TO DESKTOP SCREEN COORD: X_SCR = LEFT + X_REL, Y_SCR = TOP + Y_REL.

LINE OF THOUGHT & ROADMAP

► PHASE 1:
DETERMINISTIC BASICS (ACTIVE)

UNPACK MCV, PARSE SIDEBAR UI, BUILD POWER PLANT & BARRACKS.

► PHASE 2:
TACTICAL VISUAL RECOGNITION

TRAIN YOLO WEIGHTS ON LOCAL GPU FOR MOBILE UNITS AND ORE FIELDS.

► PHASE 3:
ONLINE HUMAN BENCHMARK

LOG MATCH METRICS AGAINST HUMAN LOBBIES TO EVOLVE MODEL CAPABILITY.

TACTICAL BLUEPRINT SCHEMATIC
Mammoth Tank Blueprint

MILESTONES

SCREEN GRABBER 100%
TEMPLATE MATCHING 60%
[✓] BASE UNPACK & BUILD LOOP
[✓] SIDEBAR ICON MATCHING
[ ] YOLO OBJECT DETECTION
[ ] MINIMAP RADAR PARSER
[ ] ONLINE HUMAN MATCHMAKING
VISION HUD OVERLAY
Tactical Vision HUD
PIPELINE CONFIG
DEPLOYMENT: CLOUDFLARE PAGES
REPOSITORY: GITHUB AUTO-SYNC