def _proc_imgs(i, warp_matrices, bndFolders, panel_irradiance, warp_md, normalize=None):
# for i in imgset.captures:
i.compute_reflectance(irradiance_list=panel_irradiance)
#i.plot_undistorted_reflectance(panel_irradiance)
cropped_dimensions, edges = imageutils.find_crop_bounds(i, warp_matrices, warp_mode=warp_md)
im_aligned = imageutils.aligned_capture(i, warp_matrices,
warp_md,
cropped_dimensions,
None, img_type="reflectance")
im_display = np.zeros((im_aligned.shape[0],im_aligned.shape[1],5), dtype=np.float32 )
for iM in range(0,im_aligned.shape[2]):
im_display[:,:,iM] = imageutils.normalize(im_aligned[:,:,iM])*65535
for k in range(0,im_display.shape[2]):
im = i.images[k]
hd, nm = os.path.split(im.path)
outdata = im_aligned[:,:,i]
outdata[outdata<0] = 0
outdata[outdata>1] = 1
outfile = os.path.join(bndFolders[k], nm)
imageio.imwrite(outfile, outdata)
cmd = ["exiftool", "-tagsFromFile", im.path, "-file:all", "-iptc:all",
"-exif:all", "-xmp", "-Composite:all", outfile,
"-overwrite_original"]
call(cmd)
def align_template(imAl, mx, reflFolder, rf, plots, warp_md):
warp_matrices, alignment_pairs = imageutils.align_capture(imAl,
ref_index=rf,
warp_mode=warp_md,
max_iterations=mx)
for x,mat in enumerate(warp_matrices):
print("Band {}:\n{}".format(x,mat))
# cropped_dimensions is of the form:
# (first column with overlapping pixels present in all images,
# first row with overlapping pixels present in all images,
# number of columns with overlapping pixels in all images,
# number of rows with overlapping pixels in all images )
dist_coeffs = []
cam_mats = []
# create lists of the distortion coefficients and camera matricies
for i,img in enumerate(imAl.images):
dist_coeffs.append(img.cv2_distortion_coeff())
cam_mats.append(img.cv2_camera_matrix())
#warp_mode = cv2.MOTION_HOMOGRAPHY #alignment_pairs[0]['warp_mode']
match_index = rf#alignment_pairs[0]['ref_index']
cropped_dimensions, edges = imageutils.find_crop_bounds(imAl,
warp_matrices,
warp_mode=warp_md)
# capture, warp_matrices, cv2.MOTION_HOMOGRAPHY, cropped_dimensions, None, img_type="reflectance",
im_aligned = imageutils.aligned_capture(imAl, warp_matrices, warp_md,
cropped_dimensions, match_index,
img_type="reflectance")
im_display = np.zeros((im_aligned.shape[0],im_aligned.shape[1],5), dtype=np.float32 )
for iM in range(0,im_aligned.shape[2]):
im_display[:,:,iM] = imageutils.normalize(im_aligned[:,:,iM])
rgb = im_display[:,:,[2,1,0]]
cir = im_display[:,:,[3,2,1]]
grRE = im_display[:,:,[4,2,1]]
prevList = [rgb, cir, grRE]
nmList = ['rgb.jpg', 'cir.jpg', 'grRE.jpg']
ootF, _ = os.path.split(reflFolder)
names = [os.path.join(ootF, pv) for pv in nmList]
for ind, p in enumerate(prevList):
#img8 = bytescale(p)
imgre = exposure.rescale_intensity(p)
with warnings.catch_warnings():
warnings.simplefilter("ignore")
img8 = util.img_as_ubyte(imgre)
imageio.imwrite(names[ind], img8)
return warp_matrices, alignment_pairs, rgb, cir, grRE#, dist_coeffs, cam_mats, cropped_dimensions
def save_capture_as_reflectance_stack(self,
outfilename,
irradiance_list=None,
warp_matrices=None,
normalize=False):
from osgeo.gdal import GetDriverByName, GDT_UInt16
self.compute_reflectance(irradiance_list)
if warp_matrices is None:
warp_matrices = self.get_warp_matrices()
cropped_dimensions, edges = imageutils.find_crop_bounds(
self, warp_matrices)
im_aligned = imageutils.aligned_capture(self,
warp_matrices,
cv2.MOTION_HOMOGRAPHY,
cropped_dimensions,
None,
img_type="reflectance")
rows, cols, bands = im_aligned.shape
driver = GetDriverByName('GTiff')
outRaster = driver.Create(outfilename, cols, rows, bands, GDT_UInt16)
if outRaster is None:
raise IOError("could not load gdal GeoTiff driver")
for i in range(0, 5):
outband = outRaster.GetRasterBand(i + 1)
outdata = im_aligned[:, :, i]
outdata[outdata < 0] = 0
outdata[outdata > 1] = 1
outband.WriteArray(outdata * 32768)
outband.FlushCache()
if bands == 6:
outband = outRaster.GetRasterBand(6)
outdata = (
im_aligned[:, :, 5] + 273.15
) * 100 # scale data from float degC to back to centi-Kelvin to fit into uint16
outdata[outdata < 0] = 0
outdata[outdata > 65535] = 65535
outband.WriteArray(outdata)
outband.FlushCache()
outRaster = None
def _proc_stack(i, warp_matrices, bndFolders, panel_irradiance, reflFolder,
warp_md, rf):
i.compute_reflectance(irradiance_list=panel_irradiance)
#i.plot_undistorted_reflectance(panel_irradiance)
cropped_dimensions, edges = imageutils.find_crop_bounds(i,
warp_matrices,
warp_mode=warp_md)
im_aligned = imageutils.aligned_capture(i,
warp_matrices,
cropped_dimensions,
warp_md,
match_index=rf,
img_type="reflectance")
im_display = np.zeros((im_aligned.shape[0], im_aligned.shape[1], 5),
dtype=np.float32)
rows, cols, bands = im_display.shape
# driver = gdal.GetDriverByName('GTiff')
im = i.images[1].path
hd, nm = os.path.split(im[:-6])
filename = os.path.join(reflFolder,
nm + '.tif') #blue,green,red,nir,redEdge
#
# outRaster = driver.Create(filename, cols, rows, 5, gdal.GDT_Byte)
# normalize = False
# Output a 'stack' in the same band order as RedEdge/Alutm
# Blue,Green,Red,NIR,RedEdge[,Thermal]
# NOTE: NIR and RedEdge are not in wavelength order!
i.compute_reflectance(panel_irradiance + [0])
i.save_capture_as_reflectance_stack(filename, normalize=True)
# for i in range(0,5):
# outband = outRaster.GetRasterBand(i+1)
# if normalize:
# outband.WriteArray(imageutils.normalize(im_aligned[:,:,i])*65535)
# else:
# outdata = im_aligned[:,:,i]
# outdata[outdata<0] = 0
# outdata[outdata>1] = 1
#
# outband.WriteArray(outdata*65535)
# outband.FlushCache()
#
# if im_aligned.shape[2] == 6:
# outband = outRaster.GetRasterBand(6)
# outdata = im_aligned[:,:,5] * 100 # scale to centi-C to fit into uint16
# outdata[outdata<0] = 0
# outdata[outdata>65535] = 65535
# outband.WriteArray(outdata)
# outband.FlushCache()
# outRaster = None
cmd = [
"exiftool", "-tagsFromFile", im, "-file:all", "-iptc:all", "-exif:all",
"-xmp", "-Composite:all", filename, "-overwrite_original"
]
call(cmd)
def _proc_imgs_comp(i, warp_matrices, bndFolders, panel_irradiance, warp_md,
rf):
i.compute_reflectance(irradiance_list=panel_irradiance)
#i.plot_undistorted_reflectance(panel_irradiance)
cropped_dimensions, edges = imageutils.find_crop_bounds(i, warp_matrices)
im_aligned = imageutils.aligned_capture(i,
warp_matrices,
warp_md,
cropped_dimensions,
match_index=rf,
img_type="reflectance")
im_display = np.zeros((im_aligned.shape[0], im_aligned.shape[1], 5),
dtype=np.float32)
for iM in range(0, im_aligned.shape[2]):
im_display[:, :,
iM] = imageutils.normalize(im_aligned[:, :, iM]) * 32768
rgb = im_display[:, :, [2, 1, 0]]
#cir = im_display[:,:,[3,2,1]]
RRENir = im_display[:, :, [4, 3, 2]]
# cir = im_display[:,:,[3,2,1]]
#
# grRE = im_display[:,:,[4,2,1]]
#
# imoot = [rgb, RRENir]
del im_display
imtags = ["RGB.tif", "RRENir.tif"] #, "GRNir.tif", "GRRE.tif"]
im = i.images[1]
hd, nm = os.path.split(im.path[:-6])
#cmdList = []
def _writeim(image, folder, nametag, im):
#for ind, k in enumerate(bndFolders):
#img8 = bytescale(imoot[ind])
#imgre = exposure.rescale_intensity(image, out_range='uint16')
#with warnings.catch_warnings():
#warnings.simplefilter("ignore")
img16 = np.uint16(np.round(image, decimals=0))
del image
outFile = os.path.join(folder, nm + '.tif')
#imageio.imwrite(outfile, img8)
#imOut = Image.fromarray(img16)
#imOut.save(outFile)
imageio.imwrite(outFile, img16)
del img16
cmd = [
"exiftool", "-tagsFromFile", im.path, "-file:all", "-iptc:all",
"-exif:all", "-xmp", "-Composite:all", outFile,
"-overwrite_original"
]
call(cmd)
_writeim(rgb, bndFolders[0], imtags[0], im)
del rgb
_writeim(RRENir, bndFolders[1], imtags[1], im)
del RRENir #,