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| isp:sample_awb_implementation_in_c [2018/06/15 01:09] – [Constructor AWB::AWB] Igor Yefmov | isp:sample_awb_implementation_in_c [2018/06/16 03:41] – [AWB::_correctGains()] Igor Yefmov | ||
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| Line 194: | Line 194: | ||
| <code c++>void AWB:: | <code c++>void AWB:: | ||
| { | { | ||
| - | const int gainG = m_ov[Val::GAIN_G]; | + | const int gainG = m_ov[Val::gain_g]; |
| - | const int gainR = m_ov[Val::GAIN_R]; | + | const int gainR = m_ov[Val::gain_r]; |
| if(gainR > gainG){ | if(gainR > gainG){ | ||
| const auto diff = (gainG - gainR) * 5 / 8; // 62.5% closer to green gain value | const auto diff = (gainG - gainR) * 5 / 8; // 62.5% closer to green gain value | ||
| - | m_ov[Val::GAIN_R] = gainR + diff; | + | m_ov[Val::gain_r] = gainR + diff; |
| } | } | ||
| }</ | }</ | ||
| Line 212: | Line 212: | ||
| assert(m_vars.op == Action:: | assert(m_vars.op == Action:: | ||
| - | const auto limit = m_ov.getLimit(Val:: | + | const auto limit = m_ov.getLimit(Val:: |
| const double precision = 0.1; | const double precision = 0.1; | ||
| Line 220: | Line 220: | ||
| // | // | ||
| const auto gb = m_vars.avgB == 0 ? 0 : m_vars.avgG / m_vars.avgB; | const auto gb = m_vars.avgB == 0 ? 0 : m_vars.avgG / m_vars.avgB; | ||
| - | const int gainB = _box(m_ov[Val:: | + | const int gainB = _box(m_ov[Val:: |
| - | m_ov[Val::GAIN_B] = gainB; | + | m_ov[Val::gain_b] = gainB; |
| } | } | ||
| if(abs(m_vars.avgV) > precision){ | if(abs(m_vars.avgV) > precision){ | ||
| const auto gr = m_vars.avgR == 0 ? 0 : m_vars.avgG / m_vars.avgR; | const auto gr = m_vars.avgR == 0 ? 0 : m_vars.avgG / m_vars.avgR; | ||
| - | const int gainR = _box(m_ov[Val:: | + | const int gainR = _box(m_ov[Val:: |
| - | m_ov[Val::GAIN_R] = gainR; | + | m_ov[Val::gain_r] = gainR; |
| } | } | ||
| } | } | ||