Игорь Федосеев
ca62db53e9
- Billiards: add native Russian Pyramid & American Eight-Ball pool with physics prediction, controls, and regression tests - Scratch Tickets: add dedicated counter, mat presentation, elliptical coin scraping, 4 ticket types, and payout effects - First-Person Dice: add native dice scene, hand anchor frames, throwing animation, and table perspective - City Wake & Weather: add arrival cutscene, alley geometry, weather/rain effects, and lighter/rocker animation - World Dressing: add hall paintings, furniture packs, hall lighting, and scene regression tests - Build & Tooling: update build.bat for modern MSVC toolchain, update launcher hash, and refresh shipping binaries
66 lines
2.7 KiB
Python
66 lines
2.7 KiB
Python
"""Offline hand normalization; dice geometry and all animation remain MASM."""
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from pathlib import Path
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import struct
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import json
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from collections import deque
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from PIL import Image
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from pack_city_wake import figures
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ROOT = Path(__file__).resolve().parents[2]
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def dice_bounds(frame):
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points = {(x,y) for y in range(frame.height) for x in range(frame.width)
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if (lambda p: p[3] == 255 and p[0] > 210 and p[1] > 200 and p[2] > 180)(frame.getpixel((x,y)))}
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cubes = []
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while points:
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start = points.pop()
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queue = deque([start])
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body = [start]
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while queue:
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x,y = queue.popleft()
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for at in ((x-1,y),(x+1,y),(x,y-1),(x,y+1)):
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if at in points:
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points.remove(at)
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queue.append(at)
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body.append(at)
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if len(body) >= 100:
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xs,ys = zip(*body)
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cubes.append((min(xs),min(ys),max(xs)+1,max(ys)+1))
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assert len(cubes) == 2, cubes
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return sorted(cubes)
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def main():
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# Reuse the connected-silhouette recovery without nominal grid clipping.
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import pack_city_wake
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pack_city_wake.SRC = ROOT / "assets/sprites/dice"
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bodies = figures("hands-v2.png")
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scale = min(240/max(b.width for b in bodies),300/max(b.height for b in bodies))
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frames = []
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for body in bodies:
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body = body.resize((round(body.width*scale),round(body.height*scale)),Image.Resampling.NEAREST)
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frame = Image.new("RGBA",(256,320))
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frame.paste(body,(256-body.width,320-body.height))
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frames.append(frame)
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data = b"".join(f.tobytes("raw","BGRA") for f in frames)
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(ROOT / "assets/animations/dice/hands-v2.bin").write_bytes(struct.pack("<4s4I",b"ANM1",256,320,16,len(data))+data)
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frames[0].save(ROOT / "build/dice/hand-ready.png")
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bounds = [dice_bounds(f) for f in frames[:4]]
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# Release geometry starts at the centres of the last held pose, in the
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# same logical coordinate system as the MASM cube renderer.
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anchors = [((320+(b[0]+b[2])//2)//2,(90+(b[1]+b[3])//2)//2) for b in bounds[-1]]
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source = "; Generated by pack_dice_assets.py from the last held pose.\n"
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for i,(x,y) in enumerate(anchors,1):
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source += f"DICE_RELEASE_X{i} EQU {x}\nDICE_RELEASE_Y{i} EQU {y}\n"
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(ROOT / "src_graphics/dice_anchors.inc").write_text(source,encoding="ascii")
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(ROOT / "build/dice/held-bounds.json").write_text(json.dumps(bounds,indent=2))
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sheet = Image.new("RGBA",(1024,1280))
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for i,frame in enumerate(frames):
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sheet.paste(frame,((i%4)*256,(i//4)*320))
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sheet.save(ROOT / "build/dice/hands-normalized.png")
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print("Packed sixteen full-cuff poses, two palm-contact dice and measured release anchors",anchors)
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if __name__ == "__main__":
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main()
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