dsh/generate_calibration_group1.py

#!/usr/bin/env python3
"""
根据 PTZ 扫描的 pan/tilt 角度直接生成校准文件。
假设全景图水平方向与 PTZ pan 角度成线性对应：
    x_ratio = (360 - pan) / 180   (pan=180 -> x=1, pan=360 -> x=0)
竖直方向使用 config/camera.py 中的 tilt 曲线反推 y_ratio。
"""
import json
import math
from pathlib import Path
from typing import List, Tuple, Dict, Any

import numpy as np


def tilt_to_y(tilt: float, y0: float = 13.0, y1: float = -5.0, power: float = 0.8) -> float:
    """根据 tilt 曲线反推 y_ratio"""
    denom = y0 - y1
    if abs(denom) < 1e-9:
        return 0.5
    if tilt >= y0:
        return 0.0
    if tilt <= y1:
        return 1.0
    return ((y0 - tilt) / denom) ** (1.0 / power)


def main():
    base = Path('/Users/wenhongquan/Desktop/阿里云同步/项目/dnn/德胜河 AI/dsh/calibration_scan_180_360_z1')
    raw_path = base / 'mapping_raw.json'
    out_path = base / 'calibration_group1.json'

    with open(raw_path, 'r', encoding='utf-8') as f:
        raw = json.load(f)

    records = raw['records']
    pano_w = raw['panorama_size']['width']
    pano_h = raw['panorama_size']['height']

    points: List[Dict[str, float]] = []
    for r in records:
        pan = float(r['pan'])
        tilt = float(r['tilt'])

        # pan 180~360 线性映射到 x 1~0
        x_ratio = (360.0 - pan) / 180.0
        x_ratio = float(np.clip(x_ratio, 0.0, 1.0))

        # 根据配置 tilt 曲线反推 y
        y_ratio = tilt_to_y(tilt)
        y_ratio = float(np.clip(y_ratio, 0.0, 1.0))

        points.append({
            'pan': pan,
            'tilt': tilt,
            'x_ratio': round(x_ratio, 4),
            'y_ratio': round(y_ratio, 4),
            'panorama_x': int(round(x_ratio * pano_w)),
            'panorama_y': int(round(y_ratio * pano_h)),
        })

    # 拟合 pan = offset + scale_x * x + scale_y * y
    X = np.array([[1.0, p['x_ratio'], p['y_ratio']] for p in points])
    pans = np.array([p['pan'] for p in points])
    tilts = np.array([p['tilt'] for p in points])
    pan_params, _, _, _ = np.linalg.lstsq(X, pans, rcond=None)
    tilt_params, _, _, _ = np.linalg.lstsq(X, tilts, rcond=None)

    # 构建 pan_lookup：按 x 排序，同一 x 取平均 pan
    x_to_pans: Dict[float, List[float]] = {}
    for p in points:
        x_to_pans.setdefault(p['x_ratio'], []).append(p['pan'])
    pan_lookup = sorted(
        [[x, float(np.mean(ps))] for x, ps in x_to_pans.items()],
        key=lambda item: item[0]
    )

    # 构建 tilt_lookup：按 y 分桶取中位数
    grid = 0.05
    y_to_tilts: Dict[float, List[float]] = {}
    for p in points:
        key = round(p['y_ratio'] / grid) * grid
        y_to_tilts.setdefault(key, []).append(p['tilt'])
    tilt_lookup = sorted(
        [[y, float(np.median(ts))] for y, ts in y_to_tilts.items()],
        key=lambda item: item[0]
    )

    # 重叠区间：直接使用扫描范围
    overlap_ranges = [{
        'pan_start': 180.0,
        'pan_end': 360.0,
        'tilt_start': -35.0,
        'tilt_end': 45.0,
        'match_count': len(points),
    }]

    calibration = {
        'pan_offset': float(pan_params[0]),
        'pan_scale_x': float(pan_params[1]),
        'pan_scale_y': float(pan_params[2]),
        'tilt_offset': float(tilt_params[0]),
        'tilt_scale_x': float(tilt_params[1]),
        'tilt_scale_y': float(tilt_params[2]),
        'rms_error': 0.0,
        'overlap_ranges': overlap_ranges,
        'pan_lookup': pan_lookup,
        'tilt_lookup': tilt_lookup,
        'mount_type': 'wall',
        'tilt_flip': False,
        'pan_flip': False,
        'generated_from': 'ptz_pan_angle_linear_mapping',
        'note': 'x_ratio=(360-pan)/180, y_ratio 由 config tilt 曲线反推',
    }

    with open(out_path, 'w', encoding='utf-8') as f:
        json.dump(calibration, f, indent=2, ensure_ascii=False)

    print(f'Generated {out_path}')
    print(f'  points: {len(points)}')
    print(f'  pan fit: {pan_params[0]:.2f} + {pan_params[1]:.2f}*x + {pan_params[2]:.2f}*y')
    print(f'  tilt fit: {tilt_params[0]:.2f} + {tilt_params[1]:.2f}*x + {tilt_params[2]:.2f}*y')
    print(f'  pan_lookup entries: {len(pan_lookup)}')
    print(f'  tilt_lookup entries: {len(tilt_lookup)}')

    # 保存 human readable CSV
    csv_path = base / 'calibration_group1_points.csv'
    with open(csv_path, 'w', encoding='utf-8') as f:
        f.write('pan,tilt,x_ratio,y_ratio,panorama_x,panorama_y\n')
        for p in points:
            f.write(f"{p['pan']},{p['tilt']},{p['x_ratio']},{p['y_ratio']},{p['panorama_x']},{p['panorama_y']}\n")
    print(f'  CSV: {csv_path}')


if __name__ == '__main__':
    main()