295 lines
11 KiB
Python
295 lines
11 KiB
Python
#!/usr/bin/env python3
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"""
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相机标定工具 - 为车间人脸识别系统生成ROI和三分区参数
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Usage:
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python calibrate_camera.py --height 5.0 --pitch 45 --report
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python calibrate_camera.py --height 4.5 --pitch 40 --focal-estimate 2000 -o cam.json
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Output:
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生成可直接复制到配置文件的params参数
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"""
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import json
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import argparse
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import numpy as np
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from dataclasses import dataclass
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from typing import List, Tuple, Dict
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import sys
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@dataclass
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class CameraParams:
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"""相机参数"""
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height: float # 安装高度(m)
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pitch_deg: float # 俯仰角(°)
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focal_px: float # 像素焦距(px)
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img_w: int # 图像宽度
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img_h: int # 图像高度
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class CameraCalibrator:
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"""相机标定器 - 计算ROI和三分区参数"""
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def __init__(self, p: CameraParams):
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self.p = p
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self.cy = p.img_h // 2
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self.cx = p.img_w // 2
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self.theta = np.radians(p.pitch_deg)
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self._build_lut()
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def _build_lut(self):
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"""预计算距离查找表 LUT[y] = distance(m)"""
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self.lut = np.zeros(self.p.img_h, dtype=np.float32)
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for y in range(self.p.img_h):
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dy = y - self.cy
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angle = self.theta + np.arctan2(dy, self.p.focal_px)
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if abs(angle) > 1e-6 and np.tan(angle) > 0:
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self.lut[y] = self.p.height / np.tan(angle)
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else:
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self.lut[y] = np.inf
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def pixel_to_distance(self, y: int) -> float:
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"""像素y坐标 -> 距离(m)"""
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if 0 <= y < self.p.img_h:
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return float(self.lut[y])
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return np.inf
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def distance_to_pixel(self, d: float) -> int:
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"""距离(m) -> 像素y坐标"""
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if d <= 0:
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return self.cy
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angle = np.arctan2(self.p.height, d)
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offset = self.p.focal_px * np.tan(angle - self.theta)
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return int(np.clip(self.cy + offset, 0, self.p.img_h - 1))
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def calculate_roi(self, min_d: float = 3.0, max_d: float = 9.0,
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margin: int = 20) -> Dict:
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"""计算ROI裁剪区域
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Args:
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min_d: 最近检测距离（米）
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max_d: 最远检测距离（米）
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margin: 边界余量（像素）
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"""
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# 注意：距离越远，y坐标越大（画面下方）
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y_min = self.distance_to_pixel(max_d) # 远距在下
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y_max = self.distance_to_pixel(min_d) # 近距在上
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# 添加边界余量
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y_min = max(0, y_min - margin)
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y_max = min(self.p.img_h, y_max + margin)
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saving = 1 - (y_max - y_min) / self.p.img_h
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return {
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"crop": {
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"x": 0,
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"y": int(y_min),
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"w": self.p.img_w,
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"h": int(y_max - y_min)
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},
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"saving_percent": round(saving * 100, 1),
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"y_min": int(y_min),
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"y_max": int(y_max)
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}
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def get_zone_boundaries(self, boundaries_m: List[float]) -> List[int]:
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"""获取分区边界像素坐标
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Args:
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boundaries_m: 分界线距离列表，如[5.0, 7.0]
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"""
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return [self.distance_to_pixel(d) for d in boundaries_m]
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def estimate_face_size(self, distance: float, real_width: float = 0.16) -> float:
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"""估算给定距离的人脸像素大小"""
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if distance <= 0:
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return 0
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return self.p.focal_px * real_width / distance
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def generate_config(self, min_d: float = 3.0, max_d: float = 9.0,
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boundaries_m: List[float] = None) -> Dict:
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"""生成配置文件
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Returns:
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包含params和meta的配置字典
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"""
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if boundaries_m is None:
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boundaries_m = [5.0, 7.0] # 默认5米和7米分界线
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roi = self.calculate_roi(min_d, max_d)
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boundaries_y = self.get_zone_boundaries(boundaries_m)
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# 生成可直接复制到instances params的配置
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config = {
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"params": {
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"camera_pitch": self.p.pitch_deg,
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"roi_enabled": True,
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"roi_y": roi["crop"]["y"],
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"roi_h": roi["crop"]["h"],
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"zones_enabled": True,
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"zone_boundary_5m": boundaries_y[0],
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"zone_boundary_7m": boundaries_y[1],
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# 320模型缩放因子
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"zone_scale_near": 1.0,
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"zone_scale_mid": 1.3,
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"zone_scale_far": 1.8
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},
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"meta": {
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"height": self.p.height,
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"pitch": self.p.pitch_deg,
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"focal_px": self.p.focal_px,
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"image_size": [self.p.img_w, self.p.img_h],
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"roi_saving": roi["saving_percent"],
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"zone_boundaries_m": boundaries_m,
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"zone_boundaries_y": boundaries_y,
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"detection_range": [min_d, max_d]
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}
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}
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return config
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def print_report(self, min_d: float = 3.0, max_d: float = 9.0,
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boundaries_m: List[float] = None):
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"""打印标定报告"""
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if boundaries_m is None:
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boundaries_m = [5.0, 7.0]
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roi = self.calculate_roi(min_d, max_d)
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boundaries_y = self.get_zone_boundaries(boundaries_m)
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print("=" * 70)
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print("相机标定报告")
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print("=" * 70)
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print(f"\n【相机参数】")
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print(f" 安装高度 H: {self.p.height}m")
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print(f" 俯仰角 θ: {self.p.pitch_deg}°")
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print(f" 像素焦距 f: {self.p.focal_px}px")
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print(f" 图像尺寸: {self.p.img_w}x{self.p.img_h}")
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print(f"\n【ROI配置】(检测范围 {min_d}-{max_d}m)")
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print(f" 裁剪区域: y={roi['crop']['y']}, h={roi['crop']['h']}")
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print(f" 算力节省: {roi['saving_percent']}%")
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print(f"\n【三分区配置】(RetinaFace_320)")
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print(f" 分界线y坐标: 5m={boundaries_y[0]}px, 7m={boundaries_y[1]}px")
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# y坐标：画面上方（y小）= 远距离，画面下方（y大）= 近距离
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by5, by7 = boundaries_y[0], boundaries_y[1]
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if by5 > by7:
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# 5米分界线在下方（y大），7米在上方（y小）
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print(f" 画面分布: 上方(y小)=远距离, 下方(y大)=近距离")
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print(f" 近区(3-5m): y>{by5}, scale=1.0x (画面下方)")
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print(f" 中区(5-7m): {by7}<y≤{by5}, scale=1.3x (画面中部)")
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print(f" 远区(7-9m): y≤{by7}, scale=1.8x (画面上方)")
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else:
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print(f" 近区(3-5m): y<{by5}, scale=1.0x")
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print(f" 中区(5-7m): {by5}≤y<{by7}, scale=1.3x")
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print(f" 远区(7-9m): y≥{by7}, scale=1.8x")
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print(f"\n【距离-像素-人脸大小映射】")
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print(f" {'距离':>6} | {'像素y':>6} | {'原始人脸':>10} | {'320输入':>9} | {'区域':>6}")
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print(f" {'-'*60}")
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for d in [3, 4, 5, 6, 7, 8, 9]:
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y = self.distance_to_pixel(d)
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face_orig = self.estimate_face_size(d)
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# 确定区域和320输入大小
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zone_idx = 0
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if d >= boundaries_m[1]:
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zone_idx = 2
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elif d >= boundaries_m[0]:
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zone_idx = 1
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scales = [1.0, 1.3, 1.8]
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face_320 = face_orig * scales[zone_idx]
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zone_name = ["近", "中", "远"][zone_idx]
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print(f" {d:>6.0f}m | {y:>6} | {face_orig:>9.0f}px | {face_320:>9.0f}px | {zone_name:>6}")
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print(f"\n【320模型说明】")
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print(f" - 320最佳检测范围：25-35px（占320输入的8-11%）")
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print(f" - 8-9米检测率可能降至70%，如不满足可升级到640模型")
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print(f" - 升级只需改：model_path + scales=[0.7,1.0,1.4]")
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print("\n" + "=" * 70)
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def main():
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parser = argparse.ArgumentParser(
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description='相机标定工具 - 生成ROI和三分区参数',
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog="""
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示例:
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# 基础标定（推荐）
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python calibrate_camera.py --height 5.0 --pitch 45 --report
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# 自定义参数并保存
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python calibrate_camera.py --height 4.5 --pitch 40 --focal-estimate 2000 -o cam.json --report
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# 调整分区边界
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python calibrate_camera.py --height 5.0 --zones 4.5 6.5 --report
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"""
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)
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parser.add_argument('--height', type=float, required=True,
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help='相机安装高度（米），如 5.0')
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parser.add_argument('--pitch', type=float, default=45,
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help='俯仰角（度），默认45')
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parser.add_argument('--focal-estimate', type=float, default=2200,
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help='像素焦距估算值，默认2200（2.5K相机4-6mm镜头）')
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parser.add_argument('--image-size', type=int, nargs=2,
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default=[2560, 1440],
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help='图像尺寸 宽 高，默认 2560 1440')
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parser.add_argument('--range', type=float, nargs=2,
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default=[3.0, 9.0],
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help='检测范围 最小距离 最大距离，默认 3.0 9.0')
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parser.add_argument('--zones', type=float, nargs=2,
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default=[5.0, 7.0],
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help='分区边界距离（米），默认 5.0 7.0（形成3-5,5-7,7-9三区）')
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parser.add_argument('-o', '--output', default='camera_calib.json',
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help='输出文件路径，默认 camera_calib.json')
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parser.add_argument('--report', action='store_true',
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help='打印详细报告')
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args = parser.parse_args()
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# 创建标定器
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params = CameraParams(
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height=args.height,
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pitch_deg=args.pitch,
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focal_px=args.focal_estimate,
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img_w=args.image_size[0],
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img_h=args.image_size[1]
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)
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calib = CameraCalibrator(params)
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config = calib.generate_config(
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args.range[0],
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args.range[1],
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list(args.zones)
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)
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# 保存配置
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with open(args.output, 'w', encoding='utf-8') as f:
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json.dump(config, f, indent=2, ensure_ascii=False)
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print(f"[OK] 配置已保存: {args.output}")
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# 打印报告
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if args.report:
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calib.print_report(args.range[0], args.range[1], list(args.zones))
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print(f"\n【可直接复制到配置文件的 params】")
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print(json.dumps(config["params"], indent=2, ensure_ascii=False))
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else:
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# 简洁输出关键参数
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print(f"\n关键参数:")
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print(f" roi_y: {config['params']['roi_y']}")
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print(f" roi_h: {config['params']['roi_h']}")
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print(f" zone_boundary_5m: {config['params']['zone_boundary_5m']}")
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print(f" zone_boundary_7m: {config['params']['zone_boundary_7m']}")
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if __name__ == '__main__':
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main()
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