def get_craters(lroc_csv_path, head_csv_path, sub_cdim, R_km):
sys.path.append('../../DeepMoon/')
import input_data_gen as igen
craters = igen.ReadLROCHeadCombinedCraterCSV(filelroc=lroc_csv_path,
filehead=head_csv_path)
craters = igen.ResampleCraters(craters, sub_cdim, None, arad=R_km)
return craters
def test_resamplecraters(self, llbd, minpix):
ctr_xlim = ((self.craters['Long'] >= llbd[0]) &
(self.craters['Long'] <= llbd[1]))
ctr_ylim = ((self.craters['Lat'] >= llbd[2]) &
(self.craters['Lat'] <= llbd[3]))
ctr_sub = self.craters.loc[ctr_xlim & ctr_ylim, :]
imgheight = int(3000. * (llbd[3] - llbd[2]) / 180.)
pixperkm = trf.km2pix(imgheight, llbd[3] - llbd[2])
minkm = minpix / pixperkm
ctr_sub = ctr_sub[ctr_sub['Diameter (km)'] >= minkm]
ctr_sub.reset_index(drop=True, inplace=True)
ctr_rs = igen.ResampleCraters(self.craters, llbd, imgheight,
minpix=minpix)
assert np.all(ctr_rs == ctr_sub)
size = comm.Get_size()
print("Thread {0} of {1}".format(rank, size))
istart = rank * amt
else:
istart = 0
# Read source image and crater catalogs.
img = Image.open(source_image_path).convert("L")
craters = igen.ReadLROCHeadCombinedCraterCSV(filehead=head_csv_path)
# Sample subset of image. Co-opt igen.ResampleCraters to remove all
# craters beyond cdim (either sub or source).
if sub_cdim != source_cdim:
img = igen.InitialImageCut(img, source_cdim, sub_cdim)
# This always works, since sub_cdim < source_cdim.
craters = igen.ResampleCraters(craters, sub_cdim, None, arad=R_km)
# Generate input images.
igen.GenDataset(img,
craters,
outhead,
rawlen_range=rawlen_range,
rawlen_dist=rawlen_dist,
ilen=ilen,
cdim=sub_cdim,
arad=R_km,
minpix=minpix,
tglen=tglen,
binary=True,
rings=True,
ringwidth=ringwidth,
def GenDataset(box_list, img, craters, outhead, arad, cdim):
truncate = True
ringwidth = 1
rings = True
binary = True
minpix = 1.
tglen = 256
ilen = 256
amt = len(box_list)
origin = "upper"
# Get craters.
igen.AddPlateCarree_XY(craters, list(img.size), cdim=cdim, origin=origin)
iglobe = ccrs.Globe(semimajor_axis=arad * 1000.,
semiminor_axis=arad * 1000.,
ellipse=None)
# Initialize output hdf5s.
[
imgs_h5, imgs_h5_inputs, imgs_h5_tgts, imgs_h5_llbd, imgs_h5_box,
imgs_h5_dc, imgs_h5_cll, craters_h5
] = init_files(outhead, amt, ilen, tglen)
for i in range(amt):
# Current image number.
img_number = "img_{:05d}".format(i)
# Determine image size to crop.
box = box_list[i]
#print("Generating {} current crop: ({})".format(img_number,box))
# Load necessary because crop may be a lazy operation; im.load() should
# copy it. See <http://pillow.readthedocs.io/en/3.1.x/
# reference/Image.html>.
im = img.crop(box)
im.load()
# Obtain long/lat bounds for coordinate transform.
ix = box[::2]
iy = box[1::2]
llong, llat = trf.pix2coord(ix,
iy,
cdim,
list(img.size),
origin=origin)
llbd = np.r_[llong, llat[::-1]]
# Downsample image.
im = im.resize([ilen, ilen], resample=Image.NEAREST)
# Remove all craters that are too small to be seen in image.
ctr_sub = igen.ResampleCraters(craters,
llbd,
im.size[1],
arad=arad,
minpix=minpix)
# Convert Plate Carree to Orthographic.
[imgo, ctr_xy, distortion_coefficient,
clonglat_xy] = (igen.PlateCarree_to_Orthographic(im,
llbd,
ctr_sub,
iglobe=iglobe,
ctr_sub=True,
arad=arad,
origin=origin,
rgcoeff=1.2,
slivercut=0.5))
if imgo is None:
print("Discarding narrow image")
continue
imgo_arr = np.asanyarray(imgo)
assert imgo_arr.sum() > 0, ("Sum of imgo is zero! There likely was "
"an error in projecting the cropped "
"image.")
# Make target mask. Used Image.BILINEAR resampling because
# Image.NEAREST creates artifacts. Try Image.LANZCOS if BILINEAR still
# leaves artifacts).
tgt = np.asanyarray(
imgo.resize((tglen, tglen), resample=Image.BILINEAR))
mask = igen.make_mask(ctr_xy,
tgt,
binary=binary,
rings=rings,
ringwidth=ringwidth,
truncate=truncate)
# Output everything to file.
output_to_file(img_number, i, imgs_h5_inputs, imgo_arr, imgs_h5_tgts,
mask, imgs_h5_box, box, imgs_h5_llbd, llbd, imgs_h5_dc,
distortion_coefficient, imgs_h5_cll, clonglat_xy,
craters_h5, ctr_xy, imgs_h5)
imgs_h5.close()
craters_h5.close()
def test_gendataset(self, tmpdir, ringwidth):
amt = 10
zeropad = 2
outhead = str(tmpdir.join('gentest'))
igen.GenDataset(self.img, self.craters, outhead,
rawlen_range=[300, 1000], rawlen_dist='log',
ilen=self.imlen, tglen=self.imlen, cdim=self.cdim,
minpix=1, ringwidth=ringwidth, amt=amt, istart=0,
seed=self.seed)
imgs_h5 = h5py.File(outhead + '_images.hdf5', 'r')
craters_h5 = pd.HDFStore(outhead + '_craters.hdf5', 'r')
for i in range(amt):
# Find image number.
img_number = "img_{i:0{zp}d}".format(i=i, zp=zeropad)
# Load box.
box = np.array(imgs_h5['pix_bounds'][img_number][...])
im = self.img.crop(box)
im.load()
# Obtain long/lat bounds for coordinate transform.
ix = box[::2]
iy = box[1::2]
llong, llat = trf.pix2coord(ix, iy, self.cdim, list(self.img.size),
origin='upper')
llbd = np.r_[llong, llat[::-1]]
# Downsample image.
im = im.resize([self.imlen, self.imlen], resample=Image.NEAREST)
# Remove all craters that are too small to be seen in image.
ctr_sub = igen.ResampleCraters(self.craters, llbd, im.size[1],
minpix=1)
# Convert Plate Carree to Orthographic.
[imgo, ctr_xy, distortion_coefficient, clonglat_xy] = (
igen.PlateCarree_to_Orthographic(
im, llbd, ctr_sub, iglobe=self.iglobe, ctr_sub=True,
slivercut=0.5))
imgo_arr = np.asanyarray(imgo)
# Make target mask.
tgt = np.asanyarray(imgo.resize((self.imlen, self.imlen),
resample=Image.BILINEAR))
mask = igen.make_mask(ctr_xy, tgt, binary=True, rings=True,
ringwidth=ringwidth, truncate=True)
assert np.all(imgo_arr == imgs_h5['input_images'][i, ...])
assert np.all(mask == imgs_h5['target_masks'][i, ...])
assert np.all(llbd == imgs_h5['longlat_bounds'][img_number][...])
assert (distortion_coefficient ==
imgs_h5['pix_distortion_coefficient'][img_number][0])
assert np.all(clonglat_xy[["x", "y"]] ==
imgs_h5['cll_xy'][img_number][...])
assert np.all(ctr_xy == craters_h5[img_number])
imgs_h5.close()
craters_h5.close()