Refactoring: extract method

pyshared/jbcr2.py

@@ -113,3 +113,17 @@ def unslice_image(a, width, height, slices):
  col_e = col_s + sw
  I[:,col_s:col_e] = a.flat[col_s*height:col_e*height].reshape(height,sw)
  return I
+
+## slice sensor image
+
+def slice_image(I, width, height, slices):
+ # make a list of the width of each slice
+ slice_widths = [slices[1]] * slices[0] + [slices[2]]
+ assert sum(slice_widths) == width
+ # slice image
+ a = np.zeros((height, width), dtype=np.dtype('>H'))
+ for i, sw in enumerate(slice_widths):
+ col_s = sum(slice_widths[0:i])
+ col_e = col_s + sw
+ a.flat[col_s*height:col_e*height] = I[:,col_s:col_e].flat
+ return a

raw_encode.py

@@ -49,25 +49,20 @@ def main():
 
  # See raw_decode.py for color components & slicing example
 
- # obtain required parameters from RAW file
+ # read input raw file
  tiff = jbtiff.tiff_file(open(args.raw, 'rb'))
- width,height = tiff.get_sensor_size()
- slices = tiff.get_slices()
-
  # load sensor image
  I = jbtiff.pnm_file.read(open(args.input,'rb'))
+
+ # obtain required parameters from RAW file
+ width,height = tiff.get_sensor_size()
+ slices = tiff.get_slices()
+ # check input image parameters
  assert len(I.shape) == 2 # must be a one-channel image
  assert I.shape == (height,width) # image size must be exact
 
- # make a list of the width of each slice
- slice_widths = [slices[1]] * slices[0] + [slices[2]]
- assert sum(slice_widths) == width
  # first slice image
- a = np.zeros((height, width), dtype=np.dtype('>H'))
- for i, sw in enumerate(slice_widths):
- col_s = sum(slice_widths[0:i])
- col_e = col_s + sw
- a.flat[col_s*height:col_e*height] = I[:,col_s:col_e].flat
+ a = jbcr2.slice_image(I, width, height, slices)
 
  # determine color components to create
  components = []