1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199

use crate::opbasics::*;

#[derive(Copy, Clone, Debug, Serialize, Deserialize)]
pub struct OpGoFloat {
  pub crop_top: usize,
  pub crop_right: usize,
  pub crop_bottom: usize,
  pub crop_left: usize,
  pub is_cfa: bool,
  pub blacklevels: [f32;4],
  pub whitelevels: [f32;4],
}

fn from_int4(arr: [u16;4]) -> [f32;4] {
  [arr[0] as f32, arr[1] as f32, arr[2] as f32, arr[3] as f32]
}

impl OpGoFloat {
  pub fn new(img: &ImageSource) -> OpGoFloat {
    match img {
      ImageSource::Raw(img) => {
        // Calculate the resulting width/height and top-left corner after crops
        OpGoFloat{
          crop_top:    img.crops[0],
          crop_right:  img.crops[1],
          crop_bottom: img.crops[2],
          crop_left:   img.crops[3],
          is_cfa: img.cfa.is_valid(),
          blacklevels: from_int4(img.blacklevels),
          whitelevels: from_int4(img.whitelevels),
        }
      },
      ImageSource::Other(_) => {
        OpGoFloat{
          crop_top:    0,
          crop_right:  0,
          crop_bottom: 0,
          crop_left:   0,
          is_cfa: false,
          blacklevels: [0.0, 0.0, 0.0, 0.0],
          whitelevels: [65535.0, 65535.0, 65535.0, 65535.0],
        }
      }
    }
  }
}

impl<'a> ImageOp<'a> for OpGoFloat {
  fn name(&self) -> &str {"gofloat"}
  fn run(&self, pipeline: &PipelineGlobals, _buf: Arc<OpBuffer>) -> Arc<OpBuffer> {
    match &pipeline.image {
      ImageSource::Raw(img) => {
        self.run_raw(img)
      },
      ImageSource::Other(img) => {
        self.run_other(img)
      }
    }
  }
}

impl OpGoFloat {
  fn run_raw(&self, img: &RawImage) -> Arc<OpBuffer> {
    // Calculate the levels
    let mins = self.blacklevels;
    let ranges = self.whitelevels.iter().enumerate().map(|(i, &x)| {
      x - mins[i]
    }).collect::<Vec<f32>>();

    // Calculate x/y/width/height making sure we get at least a 10x10 "image" to not trip up
    // reasonable assumptions in later ops
    let x = cmp::min(self.crop_left, img.width-10);
    let y = cmp::min(self.crop_top, img.height-10);
    let width = img.width - cmp::min(self.crop_left + self.crop_right, img.width-10);
    let height = img.height - cmp::min(self.crop_top + self.crop_bottom, img.height-10);

    Arc::new(match img.data {
      RawImageData::Integer(ref data) => {
        if img.cpp == 1 && !self.is_cfa {
          // We're in a monochrome image so turn it into RGB
          let mut out = OpBuffer::new(width, height, 4, true);
          out.mutate_lines(&(|line: &mut [f32], row| {
            for (o, i) in line.chunks_exact_mut(4).zip(data[img.width*(row+y)+x..].chunks_exact(1)) {
              let val = ((i[0] as f32 - mins[0]) / ranges[0]).min(1.0);
              o[0] = val;
              o[1] = val;
              o[2] = val;
              o[3] = 0.0;
            }
          }));
          out
        } else if img.cpp == 3 {
          // We're in an RGB image, turn it into four channel
          let mut out = OpBuffer::new(width, height, 4, false);
          out.mutate_lines(&(|line: &mut [f32], row| {
            for (o, i) in line.chunks_exact_mut(4).zip(data[(img.width*(row+y)+x)*3..].chunks_exact(3)) {
              o[0] = ((i[0] as f32 - mins[0]) / ranges[0]).min(1.0);
              o[1] = ((i[1] as f32 - mins[1]) / ranges[1]).min(1.0);
              o[2] = ((i[2] as f32 - mins[2]) / ranges[2]).min(1.0);
              o[3] = 0.0;
            }
          }));
          out
        } else {
          let mut out = OpBuffer::new(width, height, img.cpp, false);
          out.mutate_lines(&(|line: &mut [f32], row| {
            for (o, i) in line.chunks_exact_mut(1).zip(data[img.width*(row+y)+x..].chunks_exact(1)) {
              o[0] = ((i[0] as f32 - mins[0]) / ranges[0]).min(1.0);
            }
          }));
          out
        }
      },
      RawImageData::Float(ref data) => {
        if img.cpp == 1 && !self.is_cfa {
          // We're in a monochrome image so turn it into RGB
          let mut out = OpBuffer::new(width, height, 4, true);
          out.mutate_lines(&(|line: &mut [f32], row| {
            for (o, i) in line.chunks_exact_mut(4).zip(data[img.width*(row+y)+x..].chunks_exact(1)) {
              let val = ((i[0] as f32 - mins[0]) / ranges[0]).min(1.0);
              o[0] = val;
              o[1] = val;
              o[2] = val;
              o[3] = 0.0;
            }
          }));
          out
        } else if img.cpp == 3 {
          // We're in an RGB image, turn it into four channel
          let mut out = OpBuffer::new(width, height, 4, false);
          out.mutate_lines(&(|line: &mut [f32], row| {
            for (o, i) in line.chunks_exact_mut(4).zip(data[(img.width*(row+y)+x)*3..].chunks_exact(3)) {
              o[0] = ((i[0] as f32 - mins[0]) / ranges[0]).min(1.0);
              o[1] = ((i[1] as f32 - mins[1]) / ranges[1]).min(1.0);
              o[2] = ((i[2] as f32 - mins[2]) / ranges[2]).min(1.0);
              o[3] = 0.0;
            }
          }));
          out
        } else {
          let mut out = OpBuffer::new(width, height, img.cpp, false);
          out.mutate_lines(&(|line: &mut [f32], row| {
            for (o, i) in line.chunks_exact_mut(1).zip(data[img.width*(row+y)+x..].chunks_exact(1)) {
              o[0] = ((i[0] as f32 - mins[0]) / ranges[0]).min(1.0);
            }
          }));
          out
        }
      },
    })
  }

  fn run_other(&self, img: &OtherImage) -> Arc<OpBuffer> {
    // Calculate the levels
    let mins = self.blacklevels;
    let ranges = self.whitelevels.iter().enumerate().map(|(i, &x)| {
      x - mins[i]
    }).collect::<Vec<f32>>();

    // For now just convert to 16bit RGB all images but in the future treating
    // the cases individually could save some copying.
    // It's probably simpler to just wait for the image crate to support f32
    // channels and then just do the conversion with that.
    let img = img.to_rgb16();

    // Calculate x/y/width/height making sure we get at least a 10x10 "image" to not trip up
    // reasonable assumptions in later ops
    let owidth = img.width() as usize;
    let oheight = img.height() as usize;
    let x = cmp::min(self.crop_left, owidth-10);
    let y = cmp::min(self.crop_top, oheight-10);
    let width = owidth - cmp::min(self.crop_left + self.crop_right, owidth-10);
    let height = oheight - cmp::min(self.crop_top + self.crop_bottom, oheight-10);
    let data = img.into_raw();

    // Create complete lookup tables to speed up the transformation
    let mut lookupr = vec![0.0; 1 << 16];
    let mut lookupg = vec![0.0; 1 << 16];
    let mut lookupb = vec![0.0; 1 << 16];
    for i in 0..1<<16 {
      lookupr[i] = expand_srgb_gamma(((i as f32 - mins[0]) / ranges[0]).min(1.0));
      lookupg[i] = expand_srgb_gamma(((i as f32 - mins[1]) / ranges[1]).min(1.0));
      lookupb[i] = expand_srgb_gamma(((i as f32 - mins[2]) / ranges[2]).min(1.0));
    }

    // Finally create the RGBA buffer from it
    let mut out = OpBuffer::new(width, height, 4, false);
    out.mutate_lines(&(|line: &mut [f32], row| {
      for (o, i) in line.chunks_exact_mut(4).zip(data[(owidth*(row+y)+x)*3..].chunks_exact(3)) {
        o[0] = lookupr[i[0] as usize];
        o[1] = lookupg[i[1] as usize];
        o[2] = lookupb[i[2] as usize];
        o[3] = 0.0;
      }
    }));

    Arc::new(out)
  }
}