爱因斯坦雕像尺寸与 UV 展开量化方法

import cv2
import numpy as np
import open3d as o3d
import copy

photo_path = r"标定照片路径"
mesh_in_path = r"对应模型路径"
scaled_mesh_out = r"输出缩放后的Mesh路径"

A4_W, A4_H = 210.0, 297.0

def order_quad_points(pts):
    s = pts.sum(axis=1)
    rect = np.zeros((4,2), dtype="float32")
    rect[0], rect[2] = pts[np.argmin(s)], pts[np.argmax(s)]
    diff = np.diff(pts, axis=1)
    rect[1], rect[3] = pts[np.argmin(diff)], pts[np.argmax(diff)]
    return rect

def detect_a4_corners(img_bgr):
    gray = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2GRAY)
    gray = cv2.equalizeHist(gray)
    blur = cv2.GaussianBlur(gray,(5,5),0)
    edges = cv2.Canny(blur,50,200)
    contours,_ = cv2.findContours(edges,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
    best, best_score = None, 1e9
    h_img, w_img = gray.shape
    for cnt in contours:
        peri = cv2.arcLength(cnt,True)
        if peri < 100: continue
        approx = cv2.approxPolyDP(cnt,0.02*peri,True).reshape(4,2).astype(np.float32)
        area = abs(cv2.contourArea(approx))
        if area < (w_img*h_img)*0.0005: continue
        d = [np.linalg.norm(approx[i]-approx[(i+1)%4]) for i in range(4)]
        ratio = max(d)/min(d) if min(d)>0 else 1e9
        score = abs(ratio-1.414)/np.sqrt(area)
        if score < best_score:
            best_score = score
            best = approx.copy()
    if best is None: raise RuntimeError("未检测到 A4 纸")
    return order_quad_points(best)

def compute_px_per_mm(a4_ordered):
    w_px = np.linalg.norm(a4_ordered[1]-a4_ordered[0])
    h_px = np.linalg.norm(a4_ordered[2]-a4_ordered[1])
    return (w_px/A4_W + h_px/A4_H)/2.0

def auto_scale_mesh_by_height(mesh_path, out_path, desired_height_mm):
    mesh = o3d.io.read_triangle_mesh(mesh_path)
    vertices = np.asarray(mesh.vertices)
    y_range, z_range = vertices[:,1].max()-vertices[:,1].min(), vertices[:,2].max()-vertices[:,2].min()
    height_model = z_range if y_range<1e-6 else y_range
    scale_factor = desired_height_mm/height_model
    centroid = mesh.get_center()
    mesh_scaled = copy.deepcopy(mesh)
    mesh_scaled.translate(-centroid)
    mesh_scaled.scale(scale_factor, center=(0,0,0))
    mesh_scaled.translate(centroid)
    o3d.io.write_triangle_mesh(out_path,mesh_scaled)
    return out_path, scale_factor, height_model

# UV 量化分析代码
import os
import numpy as np
from PIL import Image
import csv
from tqdm import tqdm
import matplotlib.pyplot as plt

OBJ_PATH = r""       
UV_IMAGE_PATH = r"" 
OUTPUT_DIR = r""  
DISTORTION_THRESHOLD = 3.0
HEATMAP_COLORMAP = "jet"

os.makedirs(OUTPUT_DIR, exist_ok=True)

# 这里省略具体函数，可直接使用你提供的完整 UV 分析代码