chuanqi/cq2_sdk/scripts/find_button.py

"""Pixel-analysis of the gameupdate window screenshot to find button regions.

Buttons in Chinese game launchers are distinct-colored rectangles. Detect:
  1. Horizontal color bands distinct from background
  2. Rectangular regions of uniform color
Then print candidate click coordinates (client coords).
"""
from pathlib import Path

from PIL import Image

img = Image.open("gameupdate2.png").convert("RGB")
w, h = img.size
print(f"image: {w}x{h}")

# 1. Sample a color histogram (quantized) to find dominant + accent colors
colors: dict[tuple[int, int, int], int] = {}
px = img.load()
for y in range(0, h, 2):
    for x in range(0, w, 2):
        c = px[x, y]
        q = (c[0] // 32, c[1] // 32, c[2] // 32)
        colors[q] = colors.get(q, 0) + 1

total = sum(colors.values())
print("\ntop colors (quantized to 32):")
for c, n in sorted(colors.items(), key=lambda kv: -kv[1])[:8]:
    print(f"  RGB~({c[0]*32},{c[1]*32},{c[2]*32})  {n/total:.1%}")

# 2. Row bands: average color per row → find rows that differ from neighbors (button rows)
print("\nrow bands (rows where avg color changes sharply):")
prev = None
for y in range(h):
    rs = gs = bs = 0
    for x in range(0, w, 4):
        r, g, b = px[x, y]
        rs += r; gs += g; bs += b
    n = max(1, w // 4)
    avg = (rs // n, gs // n, bs // n)
    if prev and (abs(avg[0]-prev[0]) + abs(avg[1]-prev[1]) + abs(avg[2]-prev[2]) > 60):
        print(f"  y={y}: {prev} -> {avg}")
    prev = avg

# 3. Detect bright/saturated rectangles (buttons are usually brightest or most saturated)
print("\nsaturated/bright pixel clusters (candidate buttons):")
from collections import defaultdict

clusters = defaultdict(int)
for y in range(0, h, 3):
    for x in range(0, w, 3):
        r, g, b = px[x, y]
        sat = max(r, g, b) - min(r, g, b)
        bright = (r + g + b) / 3
        if sat > 80 or bright > 200:  # strongly colored or very bright
            clusters[(x // 40, y // 40)] += 1

# find dense clusters
dense = sorted(clusters.items(), key=lambda kv: -kv[1])[:10]
if dense:
    for (cx, cy), n in dense:
        # cluster center in client coords
        x = cx * 40 + 20
        y = cy * 40 + 20
        print(f"  cluster @ ({x},{y}) density={n}")
else:
    print("  no saturated clusters; window may be grayscale/gray button")

# 4. Dump a coarse ASCII map of brightness to see the layout
print("\nbrightness map (#=dark, .=light), 8px cells:")
for y in range(0, h, 8):
    row = ""
    for x in range(0, w, 8):
        r, g, b = px[x, y]
        v = (r + g + b) / 3
        row += "#" if v < 80 else ("+" if v < 160 else ".")
    print(f"  {y:3d} {row}")