Jules NényandClaude Opus 5.5
731531dbe2
pipeline/axo : extraction du Rhino, recalage sur la planche (1:640), maisons, arbres (positions réelles des blocs, couleurs de la planche), scène en mètres, sols depuis le PDF Illustrator vectoriel (calques pilotés), bulles de la page 15, planche de l'eau nettoyée. prototypes/axo-test : la page de test et son assembleur. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
56 lines
2.6 KiB
Python
56 lines
2.6 KiB
Python
import json, numpy as np
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from PIL import Image, ImageDraw
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R = json.load(open("rhino.json"))
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img = np.asarray(Image.open("base100-1.png").convert("RGB")).astype(int)
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H, W, _ = img.shape
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r, g, b = img[..., 0], img[..., 1], img[..., 2]
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bleu = ((b - r) > 30) & (b > 150) # eau
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vert = ((g - r) > 6) & ((g - b) > 25) & (g > 170) # limites de parcelles (vert pâle)
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cible = (bleu * 2.0 + vert * 1.0).astype(np.float32)
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print("pixels bleus", bleu.sum(), "verts", vert.sum())
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eau = [c for c in R["courbes"] if c["l"] == "B_EAU noues" and c["f"]]
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parc = [c for c in R["courbes"] if c["l"] == "PARCELLES"]
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allp = np.array([p for c in parc for p in c["p"]])
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x0, y1 = allp[:, 0].min(), allp[:, 1].max()
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def raster(s, shape):
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im = Image.new("F", (shape[1], shape[0]), 0); d = ImageDraw.Draw(im)
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for c in eau:
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d.polygon([((x - x0) * s, (y1 - y) * s) for x, y in c["p"]], fill=2.0)
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for c in parc:
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d.line([((x - x0) * s, (y1 - y) * s) for x, y in c["p"]], fill=1.0, width=max(1, int(s * 1.2)))
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return np.asarray(im, dtype=np.float32)
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def correl(a, bimg):
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P = (2 * H, 2 * W)
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Fa = np.fft.rfft2(a, P); Fb = np.fft.rfft2(bimg, P)
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c = np.fft.irfft2(Fa * np.conj(Fb), P)
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k = np.unravel_index(np.argmax(c), c.shape)
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return c[k], k
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best = None
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for s in np.arange(2.0, 9.0, 0.05):
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rs = raster(s, (H, W))
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v, k = correl(cible, rs)
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v = v / (np.sqrt((rs ** 2).sum()) + 1e-6)
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if best is None or v > best[0]: best = (v, s, k)
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v, s, k = best
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dy = k[0] if k[0] < H else k[0] - 2 * H
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dx = k[1] if k[1] < W else k[1] - 2 * W
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print("grossier : s=%.3f px/m dx=%d dy=%d score=%.1f" % (s, dx, dy, v))
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# affinage
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best2 = None
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for s2 in np.arange(s - 0.06, s + 0.06, 0.005):
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rs = raster(s2, (H, W)); v2, k2 = correl(cible, rs); v2 /= (np.sqrt((rs ** 2).sum()) + 1e-6)
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if best2 is None or v2 > best2[0]: best2 = (v2, s2, k2)
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v, s, k = best2
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dy = k[0] if k[0] < H else k[0] - 2 * H
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dx = k[1] if k[1] < W else k[1] - 2 * W
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print("fin : s=%.4f px/m à 100 dpi dx=%d dy=%d" % (s, dx, dy))
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# transformation mètres -> pixels (100 dpi) : px = (x - x0)*s + dx ; py = (y1 - y)*s + dy
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T = {"dpi": 100, "s": float(s), "x0": float(x0), "y1": float(y1), "dx": int(dx), "dy": int(dy)}
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json.dump(T, open("transfo.json", "w"))
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# contrôle visuel : géométrie Rhino en rouge par-dessus le dessin
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ov = Image.open("base100-1.png").convert("RGB"); d = ImageDraw.Draw(ov)
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f = lambda x, y: ((x - x0) * s + dx, (y1 - y) * s + dy)
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for c in parc: d.line([f(*p) for p in c["p"]], fill=(220, 30, 30), width=1)
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for c in eau: d.line([f(*p) for p in c["p"]] + [f(*c["p"][0])], fill=(200, 0, 200), width=2)
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ov.save("controle-recalage.png")
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