def scale_and_offset_values(img, scale, offset):
boxm2_batch.init_process("vilScaleAndOffsetValuesProcess")
boxm2_batch.set_input_from_db(0, img)
boxm2_batch.set_input_float(1, scale)
boxm2_batch.set_input_float(2, offset)
boxm2_batch.run_process()
return
def read_CLIF07(indir,outdir,camnum,datatype="CLIF06") :
boxm2_batch.init_process("bilReadCLIF07DataProcess")
boxm2_batch.set_input_string(0,indir);
boxm2_batch.set_input_string(1,outdir);
boxm2_batch.set_input_int(2,camnum);
boxm2_batch.set_input_string(3,datatype);
boxm2_batch.run_process();
def get_number_of_planes(img):
boxm2_batch.init_process("vilGetNumberOfPlanesProcess");
boxm2_batch.set_input_from_db(0, img);
boxm2_batch.run_process();
(id, type) = boxm2_batch.commit_output(0);
n_planes = boxm2_batch.get_output_unsigned(id)
return n_planes;
def BGR_to_RGB(inimg):
boxm2_batch.init_process("vilBGRToRGBProcess")
boxm2_batch.set_input_from_db(0, inimg)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
out_img = dbvalue(id,type)
return out_img
def gen_tex_mesh(mesh, in_img_dir, in_cam_dir, out_dir):
batch.init_process("boxm2TextureMeshProcess")
batch.set_input_from_db(0, mesh)
batch.set_input_string(1, in_img_dir)
batch.set_input_string(2, in_cam_dir)
batch.set_input_string(3, out_dir)
batch.run_process()
def load_mesh(filename):
batch.init_process("boxm2LoadMeshProcess")
batch.set_input_string(0, filename)
batch.run_process()
(id, type) = batch.commit_output(0)
mesh = dbvalue(id, type)
return mesh
def import_point_cloud(scene, cache, in_file, min_octree_depth=2):
batch.init_process("boxm2ImportPointCloudProcess")
batch.set_input_from_db(0, scene)
batch.set_input_from_db(1, cache)
batch.set_input_string(2, in_file)
batch.set_input_unsigned(3, min_octree_depth)
batch.run_process()
def import_triangle_mesh(scene, cache, ply_filename, occupied_prob=0.99):
batch.init_process("boxm2ImportTriangleMeshProcess")
batch.set_input_from_db(0, scene)
batch.set_input_from_db(1, cache)
batch.set_input_string(2, ply_filename)
batch.set_input_float(3, occupied_prob)
batch.run_process()
def paint_mesh(scene, cache, in_file, out_file):
batch.init_process("boxm2PaintMeshProcess")
batch.set_input_from_db(0, scene)
batch.set_input_from_db(1, cache)
batch.set_input_string(2, in_file)
batch.set_input_string(3, out_file)
batch.run_process()
def export_stack(scene, cache, outdir, identifier):
batch.init_process("boxm2ExportStackImagesProcess")
batch.set_input_from_db(0, scene)
batch.set_input_from_db(1, cache)
batch.set_input_string(2, outdir)
batch.set_input_string(3, identifier)
batch.run_process()
def get_3d_point_from_index(scene, cache, block_index, index):
# Warning, you probably shouldn't be doing this!
batch.init_process("boxm2CppGet3dPointFromIndexProcess")
batch.set_input_from_db(0, scene)
batch.set_input_from_db(1, cache)
batch.set_input_int(2, block_index[0])
batch.set_input_int(3, block_index[1])
batch.set_input_int(4, block_index[2])
batch.set_input_int(5, index)
batch.run_process()
(id, type) = batch.commit_output(0)
x = batch.get_output_float(id)
batch.remove_data(id)
(id, type) = batch.commit_output(1)
y = batch.get_output_float(id)
batch.remove_data(id)
(id, type) = batch.commit_output(2)
z = batch.get_output_float(id)
batch.remove_data(id)
(id, type) = batch.commit_output(3)
xs = batch.get_output_float(id)
batch.remove_data(id)
(id, type) = batch.commit_output(4)
ys = batch.get_output_float(id)
batch.remove_data(id)
(id, type) = batch.commit_output(5)
zs = batch.get_output_float(id)
batch.remove_data(id)
(id, type) = batch.commit_output(6)
leaf = batch.get_output_int(id)
batch.remove_data(id)
return ((x, y, z), (xs, ys, zs), leaf)
def histogram_equalize(img):
boxm2_batch.init_process("vilHistogramEqualizeProcess");
boxm2_batch.set_input_from_db(0, img);
boxm2_batch.run_process();
(id, type) = boxm2_batch.commit_output(0);
img_equalized = dbvalue(id, type);
return img_equalized;
def debayer(img):
boxm2_batch.init_process("vilDebayerBGGRToRGBProcess")
boxm2_batch.set_input_from_db(0,img);
boxm2_batch.run_process();
(id, type) = boxm2_batch.commit_output(0);
outimg = dbvalue(id,type);
return outimg;
def batch_synoptic_function(self):
""" Create synoptic function (cubic function) at each voxel """
# write image identifiers to file
image_id_fname = self.model_dir + "/image_list.txt"
fd = open(image_id_fname, "w")
print >> fd, 2 * len(self.imgList)
for i, img in enumerate(self.imgList):
print >> fd, "img_%05d" % i
for i, img in enumerate(self.imgList):
print >> fd, "viewdir_%05d" % i
fd.close()
type_id_fname = self.model_dir + "/type_names_list.txt"
fd2 = open(type_id_fname, "w")
print >> fd2, 4
print >> fd2, "aux0"
print >> fd2, "aux1"
print >> fd2, "aux2"
print >> fd2, "aux3"
fd2.close()
# open the stream cache, this is a read-only cache
batch.init_process("boxm2OclBatchSynopticFunctionProcess")
batch.set_input_from_db(0, self.device)
batch.set_input_from_db(1, self.scene)
batch.set_input_from_db(2, self.opencl_cache)
batch.set_input_unsigned(3, len(self.imgList))
batch.set_input_string(4, image_id_fname)
batch.set_input_float(5, 0.09)
batch.run_process()
def read_CLIF07(indir, outdir, camnum, datatype="CLIF06"):
boxm2_batch.init_process("bilReadCLIF07DataProcess")
boxm2_batch.set_input_string(0, indir)
boxm2_batch.set_input_string(1, outdir)
boxm2_batch.set_input_int(2, camnum)
boxm2_batch.set_input_string(3, datatype)
boxm2_batch.run_process()
def create_stream_cache(self, imgs, interval=1, types="", max_gb=6.0):
# write image identifiers to file
# imgRange = range(0, len(imgs), interval);
# num_imgs = len(imgRange);
image_id_fname = self.model_dir + "/image_list.txt"
fd = open(image_id_fname, "w")
print >> fd, len(imgs)
# for i in imgRange:
# print >>fd, "img_%05d"%i
for img in imgs:
fname, fextension = os.path.splitext(img)
bname = os.path.basename(fname)
print >> fd, bname
fd.close()
# write type identifiers into file
type_id_fname = self.model_dir + "/type_names_list.txt"
fd2 = open(type_id_fname, "w")
print >> fd2, 4
print >> fd2, "aux0"
print >> fd2, "aux1"
print >> fd2, "aux2"
print >> fd2, "aux3"
fd2.close()
# open the stream cache, this is a read-only cache
batch.init_process("boxm2CreateStreamCacheProcess")
batch.set_input_from_db(0, self.scene)
batch.set_input_string(1, type_id_fname)
batch.set_input_string(2, image_id_fname)
batch.set_input_float(3, max_gb)
batch.run_process()
(cache_id, cache_type) = batch.commit_output(0)
self.str_cache = dbvalue(cache_id, cache_type)
def debayer(img):
boxm2_batch.init_process("vilDebayerBGGRToRGBProcess")
boxm2_batch.set_input_from_db(0, img)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
outimg = dbvalue(id, type)
return outimg
def transform_to_scene(self, to_scene, trans, rot, scale):
if self.opencl_cache.type == "boxm2_opencl_cache_sptr":
print("transforming scene")
batch.init_process("boxm2VecfOclTransformSceneProcess")
batch.set_input_from_db(0, self.scene)
batch.set_input_from_db(1, to_scene)
batch.set_input_from_db(2, self.opencl_cache)
batch.set_input_double(3, trans[0])
batch.set_input_double(4, trans[1])
batch.set_input_double(5, trans[2])
batch.set_input_double(6, rot[0][0])
batch.set_input_double(7, rot[0][1])
batch.set_input_double(8, rot[0][2])
batch.set_input_double(9, rot[1][0])
batch.set_input_double(10, rot[1][1])
batch.set_input_double(11, rot[1][2])
batch.set_input_double(12, rot[2][0])
batch.set_input_double(13, rot[2][1])
batch.set_input_double(14, rot[2][2])
batch.set_input_double(15, scale[0])
batch.set_input_double(16, scale[1])
batch.set_input_double(17, scale[2])
return batch.run_process()
else:
print "ERROR: Cache type not recognized: ", self.opencl_cache.type
return False
def fill_holes(img):
boxm2_batch.init_process("vilFillHolesInRegionsProcess")
boxm2_batch.set_input_from_db(0, img)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
outimg = dbvalue(id, type)
return outimg
def export_points_and_normals(scene,
cache,
file_out,
save_aux=True,
prob_thresh=0.0,
vis_thresh=0.0,
nmag_thresh=0.0,
exp_thresh=0.0,
bbox_file=""):
if cache.type == "boxm2_cache_sptr":
print("Exporting to oriented point cloud")
batch.init_process("boxm2ExportOrientedPointCloudProcess")
batch.set_input_from_db(0, scene)
batch.set_input_from_db(1, cache)
batch.set_input_string(2, file_out)
# output aux (prob, vis, normal magnitdue)
batch.set_input_bool(3, save_aux)
batch.set_input_float(4, vis_thresh) # vis threshold
batch.set_input_float(5, nmag_thresh) # nmag threshold
batch.set_input_float(6, prob_thresh) # prob threshold
# batch.set_input_float(7,exp_thresh); #exp threshold
# batch.set_input_string(8, bbox_file); #bb filename
batch.set_input_string(7, bbox_file) # bb filename
return batch.run_process()
else:
print "ERROR: Cache type not recognized: ", cache.type
return False
def get_3d_point_from_index(scene, cache, block_index, index):
# Warning, you probably shouldn't be doing this!
batch.init_process("boxm2CppGet3dPointFromIndexProcess")
batch.set_input_from_db(0, scene)
batch.set_input_from_db(1, cache)
batch.set_input_int(2, block_index[0])
batch.set_input_int(3, block_index[1])
batch.set_input_int(4, block_index[2])
batch.set_input_int(5, index)
batch.run_process()
(id, type) = batch.commit_output(0)
x = batch.get_output_float(id)
batch.remove_data(id)
(id, type) = batch.commit_output(1)
y = batch.get_output_float(id)
batch.remove_data(id)
(id, type) = batch.commit_output(2)
z = batch.get_output_float(id)
batch.remove_data(id)
(id, type) = batch.commit_output(3)
xs = batch.get_output_float(id)
batch.remove_data(id)
(id, type) = batch.commit_output(4)
ys = batch.get_output_float(id)
batch.remove_data(id)
(id, type) = batch.commit_output(5)
zs = batch.get_output_float(id)
batch.remove_data(id)
(id, type) = batch.commit_output(6)
leaf = batch.get_output_int(id)
batch.remove_data(id)
return ((x, y, z), (xs, ys, zs), leaf)
def load_mesh(filename):
batch.init_process("boxm2LoadMeshProcess")
batch.set_input_string(0, filename)
batch.run_process()
(id, type) = batch.commit_output(0)
mesh = dbvalue(id, type)
return mesh
def fill_holes(img):
boxm2_batch.init_process("vilFillHolesInRegionsProcess")
boxm2_batch.set_input_from_db(0,img)
boxm2_batch.run_process()
(id,type) = boxm2_batch.commit_output(0)
outimg = dbvalue(id, type);
return outimg
def gen_tex_mesh(mesh, in_img_dir, in_cam_dir, out_dir):
batch.init_process("boxm2TextureMeshProcess")
batch.set_input_from_db(0, mesh)
batch.set_input_string(1, in_img_dir)
batch.set_input_string(2, in_cam_dir)
batch.set_input_string(3, out_dir)
batch.run_process()
def import_point_cloud(scene, cache, in_file, min_octree_depth=2):
batch.init_process("boxm2ImportPointCloudProcess")
batch.set_input_from_db(0, scene)
batch.set_input_from_db(1, cache)
batch.set_input_string(2, in_file)
batch.set_input_unsigned(3, min_octree_depth)
batch.run_process()
def import_triangle_mesh(scene, cache, ply_filename, occupied_prob=0.99):
batch.init_process("boxm2ImportTriangleMeshProcess")
batch.set_input_from_db(0, scene)
batch.set_input_from_db(1, cache)
batch.set_input_string(2, ply_filename)
batch.set_input_float(3, occupied_prob)
batch.run_process()
def create_stream_cache(self, imgs, interval=1, types="", max_gb=6.0):
# write image identifiers to file
# imgRange = range(0, len(imgs), interval);
# num_imgs = len(imgRange);
image_id_fname = self.model_dir + "/image_list.txt"
fd = open(image_id_fname, "w")
print >> fd, len(imgs)
# for i in imgRange:
# print >>fd, "img_%05d"%i
for img in imgs:
fname, fextension = os.path.splitext(img)
bname = os.path.basename(fname)
print >> fd, bname
fd.close()
# write type identifiers into file
type_id_fname = self.model_dir + "/type_names_list.txt"
fd2 = open(type_id_fname, "w")
print >>fd2, 4
print >>fd2, "aux0"
print >>fd2, "aux1"
print >>fd2, "aux2"
print >>fd2, "aux3"
fd2.close()
# open the stream cache, this is a read-only cache
batch.init_process("boxm2CreateStreamCacheProcess")
batch.set_input_from_db(0, self.scene)
batch.set_input_string(1, type_id_fname)
batch.set_input_string(2, image_id_fname)
batch.set_input_float(3, max_gb)
batch.run_process()
(cache_id, cache_type) = batch.commit_output(0)
self.str_cache = dbvalue(cache_id, cache_type)
def paint_mesh(scene, cache, in_file, out_file):
batch.init_process("boxm2PaintMeshProcess")
batch.set_input_from_db(0, scene)
batch.set_input_from_db(1, cache)
batch.set_input_string(2, in_file)
batch.set_input_string(3, out_file)
batch.run_process()
def batch_synoptic_function(self):
""" Create synoptic function (cubic function) at each voxel """
# write image identifiers to file
image_id_fname = self.model_dir + "/image_list.txt"
fd = open(image_id_fname, "w")
print >> fd, 2 * len(self.imgList)
for i, img in enumerate(self.imgList):
print >> fd, "img_%05d" % i
for i, img in enumerate(self.imgList):
print >> fd, "viewdir_%05d" % i
fd.close()
type_id_fname = self.model_dir + "/type_names_list.txt"
fd2 = open(type_id_fname, "w")
print >>fd2, 4
print >>fd2, "aux0"
print >>fd2, "aux1"
print >>fd2, "aux2"
print >>fd2, "aux3"
fd2.close()
# open the stream cache, this is a read-only cache
batch.init_process("boxm2OclBatchSynopticFunctionProcess")
batch.set_input_from_db(0, self.device)
batch.set_input_from_db(1, self.scene)
batch.set_input_from_db(2, self.opencl_cache)
batch.set_input_unsigned(3, len(self.imgList))
batch.set_input_string(4, image_id_fname)
batch.set_input_float(5, 0.09)
batch.run_process()
def transform_to_scene(self, to_scene, trans, rot, scale):
if self.opencl_cache.type == "boxm2_opencl_cache_sptr":
print("transforming scene")
batch.init_process("boxm2VecfOclTransformSceneProcess")
batch.set_input_from_db(0, self.scene)
batch.set_input_from_db(1, to_scene)
batch.set_input_from_db(2, self.opencl_cache)
batch.set_input_double(3, trans[0])
batch.set_input_double(4, trans[1])
batch.set_input_double(5, trans[2])
batch.set_input_double(6, rot[0][0])
batch.set_input_double(7, rot[0][1])
batch.set_input_double(8, rot[0][2])
batch.set_input_double(9, rot[1][0])
batch.set_input_double(10, rot[1][1])
batch.set_input_double(11, rot[1][2])
batch.set_input_double(12, rot[2][0])
batch.set_input_double(13, rot[2][1])
batch.set_input_double(14, rot[2][2])
batch.set_input_double(15, scale[0])
batch.set_input_double(16, scale[1])
batch.set_input_double(17, scale[2])
return batch.run_process()
else:
print "ERROR: Cache type not recognized: ", self.opencl_cache.type
return False
def export_stack(scene, cache, outdir, identifier):
batch.init_process("boxm2ExportStackImagesProcess")
batch.set_input_from_db(0, scene)
batch.set_input_from_db(1, cache)
batch.set_input_string(2, outdir)
batch.set_input_string(3, identifier)
batch.run_process()
def scale_and_offset_values(img,scale,offset):
boxm2_batch.init_process("vilScaleAndOffsetValuesProcess")
boxm2_batch.set_input_from_db(0,img)
boxm2_batch.set_input_float(1,scale)
boxm2_batch.set_input_float(2,offset)
boxm2_batch.run_process()
return
def median_filter_image(img, neighborhood_radius):
boxm2_batch.init_process("vilMedianFilterProcess")
boxm2_batch.set_input_from_db(0, img)
boxm2_batch.set_input_int(1, neighborhood_radius)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
filt_img = dbvalue(id, type)
return filt_img
def image_mean(img):
boxm2_batch.init_process("vilImageMeanProcess")
boxm2_batch.set_input_from_db(0, img)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
mean_val = boxm2_batch.get_output_float(id)
boxm2_batch.remove_data(id)
return mean_val
def img_sum(img, plane_index=0):
boxm2_batch.init_process("vilImageSumProcess")
boxm2_batch.set_input_from_db(0, img)
boxm2_batch.set_input_unsigned(1, plane_index)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
value = boxm2_batch.get_output_double(id)
return value
def convert_image(img, type="byte"):
boxm2_batch.init_process("vilConvertPixelTypeProcess")
boxm2_batch.set_input_from_db(0, img)
boxm2_batch.set_input_string(1, type)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
cimg = dbvalue(id, type)
return cimg
def detect_shadow_rgb(img, threshold):
boxm2_batch.init_process("vilShadowDetectionProcess")
boxm2_batch.set_input_from_db(0, img)
boxm2_batch.set_input_float(1, threshold)
boxm2_batch.run_process()
(o_id, o_type) = boxm2_batch.commit_output(0)
region_img = dbvalue(o_id, o_type)
return region_img
def query_cell_data(scene, cache, point):
batch.init_process("boxm2CppQueryCellDataProcess")
batch.set_input_from_db(0, scene)
batch.set_input_from_db(1, cache)
batch.set_input_float(2, point[0])
batch.set_input_float(3, point[1])
batch.set_input_float(4, point[2])
batch.run_process()
def fuse_based_orientation(device, sceneA, sceneB, opencl_cache):
print("Updating Dot product")
batch.init_process("boxm2OclFuseBasedOrientationProcess")
batch.set_input_from_db(0, device)
batch.set_input_from_db(1, sceneA)
batch.set_input_from_db(2, sceneB)
batch.set_input_from_db(3, opencl_cache)
return batch.run_process()
def max_threshold_image(img, threshold):
boxm2_batch.init_process("vilThresholdMaxImageProcess")
boxm2_batch.set_input_from_db(0, img)
boxm2_batch.set_input_float(1, threshold)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
mask = dbvalue(id, type)
return mask
def query_cell_data(scene, cache, point):
batch.init_process("boxm2CppQueryCellDataProcess")
batch.set_input_from_db(0, scene)
batch.set_input_from_db(1, cache)
batch.set_input_float(2, point[0])
batch.set_input_float(3, point[1])
batch.set_input_float(4, point[2])
batch.run_process()
def aggregate_normal_from_filter_vector(scene, cache, device, filter_vector):
""" compute normals based on response of filter vector """
batch.init_process("boxm2_ocl_aggregate_normal_from_filter_vector_process")
batch.set_input_from_db(0, device)
batch.set_input_from_db(1, scene)
batch.set_input_from_db(2, cache)
batch.set_input_from_db(3, filter_vector)
return batch.run_process()
def image_mean(img):
boxm2_batch.init_process("vilImageMeanProcess")
boxm2_batch.set_input_from_db(0,img)
boxm2_batch.run_process()
(id,type) = boxm2_batch.commit_output(0)
mean_val = boxm2_batch.get_output_float(id)
boxm2_batch.remove_data(id)
return mean_val
def fuse_based_surface_density(device, sceneA, sceneB, opencl_cache):
print("Fuse two models using Surface Density")
batch.init_process("boxm2OclFuseSurfaceDensityProcess")
batch.set_input_from_db(0, device)
batch.set_input_from_db(1, sceneA)
batch.set_input_from_db(2, sceneB)
batch.set_input_from_db(3, opencl_cache)
return batch.run_process()
def max_threshold_image(img, threshold):
boxm2_batch.init_process("vilThresholdMaxImageProcess")
boxm2_batch.set_input_from_db(0,img)
boxm2_batch.set_input_float(1,threshold)
boxm2_batch.run_process()
(id,type) = boxm2_batch.commit_output(0)
mask = dbvalue(id,type)
return mask
def combine_eo_ir(eo_img, ir_img):
boxm2_batch.init_process("vilEOIRCombineProcess")
boxm2_batch.set_input_from_db(0, eo_img)
boxm2_batch.set_input_from_db(1, ir_img)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
img_out = dbvalue(id, type)
return img_out
def get_plane(img, plane_id):
boxm2_batch.init_process("vilGetPlaneProcess")
boxm2_batch.set_input_from_db(0, img)
boxm2_batch.set_input_unsigned(1, plane_id)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
img_plane = dbvalue(id, type)
return img_plane
def fuse_based_visibility(device, sceneA, sceneB, opencl_cache):
print("Updating Max Vis")
batch.init_process("boxm2OclFuseBasedVisibilityProcess")
batch.set_input_from_db(0, device)
batch.set_input_from_db(1, sceneA)
batch.set_input_from_db(2, sceneB)
batch.set_input_from_db(3, opencl_cache)
return batch.run_process()
def median_filter_image(img, neighborhood_radius):
boxm2_batch.init_process("vilMedianFilterProcess")
boxm2_batch.set_input_from_db(0,img)
boxm2_batch.set_input_int(1,neighborhood_radius)
boxm2_batch.run_process()
(id,type) = boxm2_batch.commit_output(0)
filt_img = dbvalue(id,type)
return filt_img
def img_sum(img, plane_index=0):
boxm2_batch.init_process("vilImageSumProcess")
boxm2_batch.set_input_from_db(0,img)
boxm2_batch.set_input_unsigned(1,plane_index)
boxm2_batch.run_process()
(id,type) = boxm2_batch.commit_output(0)
value = boxm2_batch.get_output_double(id)
return value
def get_plane(img, plane_id):
boxm2_batch.init_process("vilGetPlaneProcess");
boxm2_batch.set_input_from_db(0, img);
boxm2_batch.set_input_unsigned(1, plane_id);
boxm2_batch.run_process();
(id, type) = boxm2_batch.commit_output(0);
img_plane = dbvalue(id, type);
return img_plane;
def convert_image(img, type="byte") :
boxm2_batch.init_process("vilConvertPixelTypeProcess");
boxm2_batch.set_input_from_db(0, img);
boxm2_batch.set_input_string(1, type);
boxm2_batch.run_process();
(id,type) = boxm2_batch.commit_output(0);
cimg = dbvalue(id,type);
return cimg;
def detect_shadow_rgb(img,threshold) :
boxm2_batch.init_process("vilShadowDetectionProcess");
boxm2_batch.set_input_from_db(0,img)
boxm2_batch.set_input_float(1, threshold);
boxm2_batch.run_process();
(o_id,o_type) = boxm2_batch.commit_output(0);
region_img = dbvalue(o_id,o_type);
return region_img;
def combine_eo_ir(eo_img,ir_img):
boxm2_batch.init_process("vilEOIRCombineProcess")
boxm2_batch.set_input_from_db(0,eo_img)
boxm2_batch.set_input_from_db(1,ir_img)
boxm2_batch.run_process()
(id,type) = boxm2_batch.commit_output(0)
img_out = dbvalue(id,type)
return img_out
def arf_next_frame(rawStream) :
boxm2_batch.init_process("bilArfReadFrameProcess")
boxm2_batch.set_input_from_db(0,rawStream);
boxm2_batch.run_process();
(id, type) = boxm2_batch.commit_output(0);
img = dbvalue(id,type);
(id, type) = boxm2_batch.commit_output(1);
time = boxm2_batch.get_output_unsigned(id);
return img, time
def arf_next_frame(rawStream):
boxm2_batch.init_process("bilArfReadFrameProcess")
boxm2_batch.set_input_from_db(0, rawStream)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
img = dbvalue(id, type)
(id, type) = boxm2_batch.commit_output(1)
time = boxm2_batch.get_output_unsigned(id)
return img, time
def query_cell_brdf(scene, cache, point, model_type):
batch.init_process("boxm2CppQueryCellBrdfProcess")
batch.set_input_from_db(0, scene)
batch.set_input_from_db(1, cache)
batch.set_input_float(2, point[0])
batch.set_input_float(3, point[1])
batch.set_input_float(4, point[2])
batch.set_input_string(5, model_type)
batch.run_process()
