def generate(image_path, per_band_transformation, last_band_alpha=False):
'''Applies a set of linear transformations to a gimage
:param str image_path: The path to an image
:param list per_band_transformation: A list of of LinearTransformations
(length equal to the number of bands in the image)
:param output: A gimage that represents input_gimage with transformations
applied
'''
img_ds, img_alpha, band_count = _open_image_and_get_info(
image_path, last_band_alpha)
img_metadata = gimage.read_metadata(img_ds)
_assert_consistent(band_count, per_band_transformation)
output_bands = []
for band_no, transformation in zip(range(1, band_count + 1),
per_band_transformation):
band = gimage.read_single_band(img_ds, band_no)
output_bands.append(normalize.apply(band, transformation))
return gimage.GImage(output_bands, img_alpha, img_metadata)
def test_read_metadata(self):
gdal_ds = gdal.Open(self.test_photometric_alpha_image)
test_metadata = gimage.read_metadata(gdal_ds)
self.assertEqual(test_metadata, self.metadata)
candidate_path = os.path.join(wd_local, candidate_fn)
reference_path = os.path.join(wd_local, reference_fn)
result_fn = candidate_fn[0:-13] + '_R_10m_clip.tif'
result_path = os.path.join(wd_sync, result_fn)
print candidate_path, reference_path, result_path
parameters = pif.pca_options(threshold=100)
combined_alpha = [1, 2, 3, 7]
pif_mask = pif_wrapper.generate(candidate_path, reference_path, method='filter_PCA', last_band_alpha=False, method_options=parameters)
## OPTIONAL - Save out the PIF mask
candidate_ds = gdal.Open(candidate_path)
print candidate_ds
metadata = gimage.read_metadata(candidate_ds)
print metadata
pif_gimg = gimage.GImage([pif_mask], numpy.ones(pif_mask.shape, dtype=numpy.bool), metadata)
# gimage.save(pif_gimg, 'PIF_pixels_3bands.tif')
##
# transformations = transformation_wrapper.generate(candidate_path, reference_path, pif_mask, method='linear_relationship', last_band_alpha=True)
transformations = transformation_wrapper.generate(candidate_path, reference_path, pif_mask, method='linear_relationship', last_band_alpha=False)
## OPTIONAL - View the transformations
print transformations
normalised_gimg = normalize_wrapper.generate(candidate_path, transformations, last_band_alpha=False)
gimage.save(normalised_gimg, result_path)
# ## OPTIONAL - View the effect on the pixels (SLOW)
# from radiometric_normalization.wrappers import display_wrapper