單元 12 · 鏡頭陰影校正（LSC）

# 固定曝光、AWB off，多拍幾張不同亮度
rpicam-still --shutter 20000 --gain 1 --awb off -o lsc1.png
rpicam-still --shutter 40000 --gain 1 --awb off -o lsc2.png
# 用 libcamera / 社群 calibration 工具產生網格 → tuning

python3 - <<'EOF'
import cv2, numpy as np
img = cv2.imread('lsc_check.png', 0)   # 均勻灰拍出的圖
h, w = img.shape
c = img[h//2, w//2]
corners = [img[50,50], img[50,w-50], img[h-50,50], img[h-50,w-50]]
print('center:', c)
print('corners:', corners)
print('暗角比:', min(corners)/c)     # 目標 >0.9（均勻）
EOF

{ "LensShading": {
    "meshes": [
      { "size": [17, 13],          # 網格維度
        "type": "sector",          # 資料型態
        "reference": [...],        # 參考網格
        "r": [...], "gr": [...], "gb": [...], "b": [...] }
    ] } }

python3 - <<'EOF'
import rawpy, numpy as np
raw = rawpy.imread('lsc.dng').raw_image.astype(float)
h, w = raw.shape
# 以中心為基準，算每一格對中心的比例 → 倒數為增益
center = raw[h//2 - 50:h//2+50, w//2-50:w//2+50].mean()
grid = 13
gh, gw = h//grid, w//grid
print('增益圖（中心=1，四周>1）:')
for gy in range(grid):
    row = []
    for gx in range(grid):
        cell = raw[gy*gh:(gy+1)*gh, gx*gw:(gx+1)*gw].mean()
        row.append(f'{center/cell:.2f}')
    print(' '.join(row))
EOF

# 均勻灰拍圖
center = 中央區平均
corner = 四角平均
暗角比 = corner / center
# 目標：校正後 > 0.9（原可能 0.7 甚至更低）

python3 - <<'EOF'
import rawpy, numpy as np
raw = rawpy.imread('white_wall.dng').raw_image.astype(float)
h, w = raw.shape
grid_h, grid_w = 13, 17  # libcamera 標準網格
cell_h, cell_w = h // grid_h, w // grid_w
center_roi = raw[h//2-50:h//2+50, w//2-50:w//2+50]
center_val = center_roi.mean()

print(f"{'':>8}", end="")
for gx in range(grid_w):
    print(f"col{gx:2d}", end=" ")
print()

for gy in range(grid_h):
    print(f"row{gy:2d}: ", end="")
    for gx in range(grid_w):
        cell = raw[gy*cell_h:(gy+1)*cell_h, gx*cell_w:(gx+1)*cell_w].mean()
        gain = center_val / cell if cell > 0 else 99
        print(f"{gain:5.2f}", end=" ")
    print()

print(f"\n中心值: {center_val:.1f}")
print(f"最暗角落增益: {center_val / raw[20:80, 20:80].mean():.2f}")
EOF

#!/bin/bash
# 1. 拍均勻灰（白牆/積分球）固定參數
rpicam-still --raw --shutter 20000 --gain 1 \
  --awb off --awbgains 1,1 -o lsc_src.dng

# 2. 分通道算網格增益（以中央為 1.0）
python3 - <<'EOF'
import rawpy, numpy as np
raw = rawpy.imread('lsc_src.dng').raw_image.astype(float)
h, w = raw.shape
gh, gw = 13, 17                      # libcamera 標準網格
ch, cw = h//gh, w//gw
center = raw[h//2-50:h//2+50, w//2-50:w//2+50].mean()
print("角落/中心 暗角比 =", round(raw[20:80,20:80].mean()/center, 3))
# 對每格輸出增益（此處以整體亮度示意，實作需分 RGGB）
for gy in range(gh):
    row = []
    for gx in range(gw):
        cell = raw[gy*ch:(gy+1)*ch, gx*cw:(gx+1)*cw].mean()
        row.append(f"{center/cell:.3f}")
    print(" ".join(row))
EOF
# 3. 將網格填入 tuning JSON 的 LensShading 區塊 → v2_lsc.json

# 套用新 tuning 重拍均勻灰
rpicam-still --raw --tuning-file v2_lsc.json --shutter 20000 \
  --gain 1 --awb off --awbgains 1,1 -o lsc_after.dng
python3 - <<'EOF'
import rawpy, numpy as np
raw = rawpy.imread('lsc_after.dng').raw_image.astype(float)
c = raw[800:1200, 1100:1500].mean()
corn = [raw[50,50],raw[50,-51],raw[-51,50],raw[-51,-51]]
print("中央:", round(c,1), " 四角:", [round(x,1) for x in corn])
print("暗角比:", round(min(corn)/c, 3), "(目標 >0.9)")
EOF