def crop_image_using_3d_box(img_res, camera, lower_left_lon, lower_left_lat, lower_left_elev, upper_right_lon, upper_right_lat, upper_right_elev, uncertainty):
boxm2_batch.init_process("vpglCropImgUsing3DboxProcess");
boxm2_batch.set_input_from_db(0, img_res);
boxm2_batch.set_input_from_db(1, camera);
boxm2_batch.set_input_double(2, lower_left_lon);
boxm2_batch.set_input_double(3, lower_left_lat);
boxm2_batch.set_input_double(4, lower_left_elev);
boxm2_batch.set_input_double(5, upper_right_lon);
boxm2_batch.set_input_double(6, upper_right_lat);
boxm2_batch.set_input_double(7, upper_right_elev);
boxm2_batch.set_input_double(8, uncertainty);
status = boxm2_batch.run_process();
if status:
(id, type) = boxm2_batch.commit_output(0);
local_cam = dbvalue(id, type);
(id, type) = boxm2_batch.commit_output(1);
i0 = boxm2_batch.get_output_unsigned(id)
(id, type) = boxm2_batch.commit_output(2);
j0 = boxm2_batch.get_output_unsigned(id)
(id, type) = boxm2_batch.commit_output(3);
ni = boxm2_batch.get_output_unsigned(id)
(id, type) = boxm2_batch.commit_output(4);
nj = boxm2_batch.get_output_unsigned(id)
return status, local_cam, i0, j0, ni, nj;
else:
return status, dbvalue(0, ""), 0, 0, 0, 0;
def offset_cam_using_3d_box(camera, lower_left_lon, lower_left_lat, lower_left_elev, upper_right_lon, upper_right_lat, upper_right_elev, uncertainty, lvcs=None):
boxm2_batch.init_process("vpglOffsetCamUsing3DboxProcess");
boxm2_batch.set_input_from_db(0, camera);
boxm2_batch.set_input_double(1, lower_left_lon);
boxm2_batch.set_input_double(2, lower_left_lat);
boxm2_batch.set_input_double(3, lower_left_elev);
boxm2_batch.set_input_double(4, upper_right_lon);
boxm2_batch.set_input_double(5, upper_right_lat);
boxm2_batch.set_input_double(6, upper_right_elev);
boxm2_batch.set_input_double(7, uncertainty);
if lvcs:
boxm2_batch.set_input_from_db(8, lvcs);
status = boxm2_batch.run_process();
if status:
(id, type) = boxm2_batch.commit_output(0);
local_cam = dbvalue(id, type);
(id, type) = boxm2_batch.commit_output(1);
i0 = boxm2_batch.get_output_unsigned(id)
boxm2_batch.remove_data(id);
(id, type) = boxm2_batch.commit_output(2);
j0 = boxm2_batch.get_output_unsigned(id)
boxm2_batch.remove_data(id);
(id, type) = boxm2_batch.commit_output(3);
ni = boxm2_batch.get_output_unsigned(id)
boxm2_batch.remove_data(id);
(id, type) = boxm2_batch.commit_output(4);
nj = boxm2_batch.get_output_unsigned(id)
boxm2_batch.remove_data(id);
return status, local_cam, i0, j0, ni, nj;
else:
return status, dbvalue(0, ""), 0, 0, 0, 0;
def test_classifier_clouds(tclsf, dictionary_name, image_resource, i, j, width, height, block_size, percent_cat_name, category_id_file=""):
boxm2_batch.init_process("sdetTextureClassifySatelliteCloudsProcess");
boxm2_batch.set_input_from_db(0, tclsf);
boxm2_batch.set_input_string(1, dictionary_name);
boxm2_batch.set_input_from_db(2, image_resource);
boxm2_batch.set_input_unsigned(3, i);
boxm2_batch.set_input_unsigned(4, j);
boxm2_batch.set_input_unsigned(5, width);
boxm2_batch.set_input_unsigned(6, height);
boxm2_batch.set_input_unsigned(7, block_size);
boxm2_batch.set_input_string(8, category_id_file);
boxm2_batch.set_input_string(9, percent_cat_name);
status = boxm2_batch.run_process();
if status:
(out_id, out_type)=boxm2_batch.commit_output(0);
out_crop = dbvalue(out_id, out_type);
(out_id, out_type)=boxm2_batch.commit_output(1);
out_id_map = dbvalue(out_id, out_type);
(out_id, out_type)=boxm2_batch.commit_output(2);
out_rgb_map = dbvalue(out_id, out_type);
(percent_id, percent_type) = boxm2_batch.commit_output(3);
percent = boxm2_batch.get_output_float(percent_id);
boxm2_batch.remove_data(percent_id)
return out_crop, out_id_map, out_rgb_map, percent
else:
out_crop = 0;
out_id_map = 0;
out_rgb_map = 0;
percent = 100;
return out_crop, out_id_map, out_rgb_map, percent
def crop_image_using_3d_box(img_res, camera, lower_left_lon, lower_left_lat, lower_left_elev, upper_right_lon, upper_right_lat, upper_right_elev, uncertainty, lvcs=0):
boxm2_batch.init_process("vpglCropImgUsing3DboxProcess")
boxm2_batch.set_input_from_db(0, img_res)
boxm2_batch.set_input_from_db(1, camera)
boxm2_batch.set_input_double(2, lower_left_lon)
boxm2_batch.set_input_double(3, lower_left_lat)
boxm2_batch.set_input_double(4, lower_left_elev)
boxm2_batch.set_input_double(5, upper_right_lon)
boxm2_batch.set_input_double(6, upper_right_lat)
boxm2_batch.set_input_double(7, upper_right_elev)
boxm2_batch.set_input_double(8, uncertainty)
if lvcs:
boxm2_batch.set_input_from_db(9, lvcs)
status = boxm2_batch.run_process()
if status:
(id, type) = boxm2_batch.commit_output(0)
local_cam = dbvalue(id, type)
(id, type) = boxm2_batch.commit_output(1)
i0 = boxm2_batch.get_output_unsigned(id)
boxm2_batch.remove_data(id)
(id, type) = boxm2_batch.commit_output(2)
j0 = boxm2_batch.get_output_unsigned(id)
boxm2_batch.remove_data(id)
(id, type) = boxm2_batch.commit_output(3)
ni = boxm2_batch.get_output_unsigned(id)
boxm2_batch.remove_data(id)
(id, type) = boxm2_batch.commit_output(4)
nj = boxm2_batch.get_output_unsigned(id)
boxm2_batch.remove_data(id)
return status, local_cam, i0, j0, ni, nj
else:
return status, dbvalue(0, ""), 0, 0, 0, 0
def blobwise_kl_div(p_img, q_img, blob_img, thresh=.1) :
boxm2_batch.init_process("bripBlobwiseKLDivProcess")
boxm2_batch.set_input_from_db(0, p_img);
boxm2_batch.set_input_from_db(1, q_img);
boxm2_batch.set_input_from_db(2, blob_img);
boxm2_batch.set_input_float(3, thresh);
boxm2_batch.run_process();
(id,type) = boxm2_batch.commit_output(0);
kl_img = dbvalue(id,type);
(id,type) = boxm2_batch.commit_output(1);
thresh_img = dbvalue(id,type);
return kl_img, thresh_img;
def test_classifier(tclsf, block_size, category_id_file=""):
boxm2_batch.init_process("sdetTextureClassifierProcess2");
boxm2_batch.set_input_from_db(0, tclsf);
boxm2_batch.set_input_unsigned(1, block_size);
boxm2_batch.set_input_string(2, category_id_file);
boxm2_batch.run_process();
(out_id, out_type)=boxm2_batch.commit_output(0);
out = dbvalue(out_id, out_type);
(out_id, out_type)=boxm2_batch.commit_output(1);
out_color = dbvalue(out_id, out_type);
(out_id, out_type)=boxm2_batch.commit_output(2);
out_id = dbvalue(out_id, out_type);
return out, out_color, out_id
def detect_shadow_ridge(region_img, blob_size_t, sun_angle):
boxm2_batch.init_process("vilShadowRidgeDetectionProcess")
boxm2_batch.set_input_from_db(0, region_img)
boxm2_batch.set_input_int(1, blob_size_t)
boxm2_batch.set_input_float(2, sun_angle)
boxm2_batch.run_process()
(o_id, o_type) = boxm2_batch.commit_output(0)
region_img = dbvalue(o_id, o_type)
(o_id, o_type) = boxm2_batch.commit_output(1)
out_img = dbvalue(o_id, o_type)
(o_id, o_type) = boxm2_batch.commit_output(2)
dist_img = dbvalue(o_id, o_type)
return region_img, out_img, dist_img
def get_xyz_from_depth_image(cam,depth_img):
boxm2_batch.init_process("vpglGenerateXYZFromDepthImageProcess");
boxm2_batch.set_input_from_db(0,cam); # perspective or generic camera
boxm2_batch.set_input_from_db(1,depth_img);
boxm2_batch.run_process();
(id,type) = boxm2_batch.commit_output(0);
x_img = dbvalue(id,type);
(id,type) = boxm2_batch.commit_output(1);
y_img = dbvalue(id,type);
(id,type) = boxm2_batch.commit_output(2);
z_img = dbvalue(id,type);
return x_img,y_img,z_img;
def classify_image(eig, h_no, h_atmos, input_image_filename, tile_ni, tile_nj):
boxm2_batch.init_process("bradClassifyImageProcess");
boxm2_batch.set_input_from_db(0, eig);
boxm2_batch.set_input_from_db(1, h_no);
boxm2_batch.set_input_from_db(2, h_atmos);
boxm2_batch.set_input_string(3, input_image_filename);
boxm2_batch.set_input_unsigned(4, tile_ni);
boxm2_batch.set_input_unsigned(5, tile_nj);
boxm2_batch.run_process();
(vid, vtype) = boxm2_batch.commit_output(0);
q_img = dbvalue(vid, vtype);
(vid, vtype) = boxm2_batch.commit_output(1);
q_img_orig_size = dbvalue(vid, vtype);
return q_img, q_img_orig_size
def gradient(img):
boxm2_batch.init_process('vilGradientProcess')
boxm2_batch.set_input_from_db(0, img)
boxm2_batch.run_process()
# x image
(id, type) = boxm2_batch.commit_output(0)
dIdx = dbvalue(id, type)
# y image
(id, type) = boxm2_batch.commit_output(1)
dIdy = dbvalue(id, type)
# mag image
(id, type) = boxm2_batch.commit_output(2)
magImg = dbvalue(id, type)
return dIdx, dIdy, magImg
def correct_cam_rotation(img, pcam, exp_img, cone_half_angle, n_steps, refine=True):
boxm2_batch.init_process('icamCorrectCamRotationProcess')
boxm2_batch.set_input_from_db(0,img)
boxm2_batch.set_input_from_db(1,pcam)
boxm2_batch.set_input_from_db(2,exp_img)
boxm2_batch.set_input_float(3,cone_half_angle)
boxm2_batch.set_input_unsigned(4,n_steps)
boxm2_batch.set_input_bool(5,refine)
boxm2_batch.run_process()
(m_id,m_type) = boxm2_batch.commit_output(0)
mapped_img = dbvalue(m_id,m_type);
(c_id,c_type) = boxm2_batch.commit_output(1)
corr_cam = dbvalue(c_id,c_type);
return mapped_img, corr_cam
def generate_roc(tclsf, class_out_prob_img, class_out_color_img, orig_img, prefix_for_bin_files, positive_category_name,category_id_file):
boxm2_batch.init_process("sdetTextureClassifierROCProcess");
boxm2_batch.set_input_from_db(0, tclsf);
boxm2_batch.set_input_from_db(1, class_out_prob_img);
boxm2_batch.set_input_from_db(2, class_out_color_img);
boxm2_batch.set_input_from_db(3, orig_img);
boxm2_batch.set_input_string(4, prefix_for_bin_files);
boxm2_batch.set_input_string(5, positive_category_name);
boxm2_batch.set_input_string(6, category_id_file);
boxm2_batch.run_process();
(id,type) = boxm2_batch.commit_output(0);
tp = boxm2_batch.get_bbas_1d_array_float(id);
boxm2_batch.remove_data(id);
(id,type) = boxm2_batch.commit_output(1);
tn = boxm2_batch.get_bbas_1d_array_float(id);
boxm2_batch.remove_data(id);
(id,type) = boxm2_batch.commit_output(2);
fp = boxm2_batch.get_bbas_1d_array_float(id);
boxm2_batch.remove_data(id);
(id,type) = boxm2_batch.commit_output(3);
fn = boxm2_batch.get_bbas_1d_array_float(id);
boxm2_batch.remove_data(id);
(id,type) = boxm2_batch.commit_output(4);
tpr = boxm2_batch.get_bbas_1d_array_float(id);
boxm2_batch.remove_data(id);
(id,type) = boxm2_batch.commit_output(5);
fpr = boxm2_batch.get_bbas_1d_array_float(id);
boxm2_batch.remove_data(id);
(id,type) = boxm2_batch.commit_output(6);
outimg = dbvalue(id,type);
return tp, tn, fp, fn, tpr, fpr, outimg;
def load_classifier(classifier_name):
boxm2_batch.init_process("sdetLoadTextureClassifierProcess");
boxm2_batch.set_input_string(0,classifier_name);
boxm2_batch.run_process();
(tclsf_id, tclsf_type)=boxm2_batch.commit_output(0);
tclsf = dbvalue(tclsf_id, tclsf_type);
return tclsf
def load_dictionary(dictionary_name):
boxm2_batch.init_process("sdetLoadTextureDictionaryProcess");
boxm2_batch.set_input_string(0,dictionary_name);
boxm2_batch.run_process();
(tclsf_id, tclsf_type)=boxm2_batch.commit_output(0);
tclsf = dbvalue(tclsf_id, tclsf_type);
return tclsf
def load_mesh(filename):
boxm2_batch.init_process("boxm2LoadMeshProcess");
boxm2_batch.set_input_string(0,filename);
boxm2_batch.run_process();
(id, type) = boxm2_batch.commit_output(0);
mesh = dbvalue(id, type);
return mesh;
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 initialize_rng(seed=0):
boxm2_batch.init_process("bstaInitializeRandomSeedProcess");
boxm2_batch.set_input_unsigned(0,seed);
boxm2_batch.run_process();
(id,type) = boxm2_batch.commit_output(0)
rng = dbvalue(id,type)
return rng
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 load_projective_camera(file_path):
boxm2_batch.init_process("vpglLoadProjCameraProcess")
boxm2_batch.set_input_string(0, file_path)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
cam = dbvalue(id, type)
return cam
def load_local_rational_camera(file_path) :
boxm2_batch.init_process("vpglLoadLocalRationalCameraProcess");
boxm2_batch.set_input_string(0, file_path);
boxm2_batch.run_process();
(id,type) = boxm2_batch.commit_output(0);
cam = dbvalue(id,type);
return cam;
def load_perspective_camera(file_path) :
boxm2_batch.init_process("vpglLoadPerspectiveCameraProcess");
boxm2_batch.set_input_string(0, file_path);
boxm2_batch.run_process();
(id,type) = boxm2_batch.commit_output(0);
cam = dbvalue(id,type);
return cam;
def convert_local_rational_perspective_camera(local_cam) :
boxm2_batch.init_process("vpglConvertLocalRationalToPerspectiveProcess");
boxm2_batch.set_input_from_db(0, local_cam);
boxm2_batch.run_process();
(id,type) = boxm2_batch.commit_output(0);
cam = dbvalue(id,type);
return cam;
def load_atmospheric_parameters(filename):
boxm2_batch.init_process("bradLoadAtmosphericParametersProcess")
boxm2_batch.set_input_string(0,filename)
boxm2_batch.run_process()
(id,type) = boxm2_batch.commit_output(0)
atm_params = dbvalue(id,type)
return atm_params
def load_rational_camera_nitf(file_path):
boxm2_batch.init_process("vpglLoadRationalCameraNITFProcess")
boxm2_batch.set_input_string(0, file_path)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
cam = dbvalue(id, type)
return cam
def invert_float_image(img):
boxm2_batch.init_process("vilInvertFloatImageProcess")
boxm2_batch.set_input_from_db(0, img)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
inverted_img = dbvalue(id, type)
return inverted_img
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 load_joint_hist3d(filename):
boxm2_batch.init_process("bstaLoadJointHist3dProcess");
boxm2_batch.set_input_string(0,filename);
boxm2_batch.run_process();
(h_id,h_type) = boxm2_batch.commit_output(0);
h = dbvalue(h_id, h_type);
return h
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 load_lvcs(lvcs_filename):
boxm2_batch.init_process("vpglLoadLVCSProcess");
boxm2_batch.set_input_string(0, lvcs_filename);
boxm2_batch.run_process();
(lvcs_id, lvcs_type) = boxm2_batch.commit_output(0);
lvcs = dbvalue(lvcs_id, lvcs_type);
return lvcs;
def load_eigenspace(filename):
boxm2_batch.init_process("bradLoadEigenspaceProcess");
boxm2_batch.set_input_string(0, filename);
boxm2_batch.run_process();
(eig_id,eig_type)=boxm2_batch.commit_output(0);
eig = dbvalue(eig_id, eig_type);
return eig;
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 radiometrically_calibrate(cropped_image, meta):
boxm2_batch.init_process("bradNITFAbsRadiometricCalibrationProcess")
boxm2_batch.set_input_from_db(0, cropped_image)
boxm2_batch.set_input_from_db(1, meta)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
cropped_img_cal = dbvalue(id, type)
return cropped_img_cal
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 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 prob_as_expected(image, atomicity):
boxm2_batch.init_process("bslExpectedImageProcess")
boxm2_batch.set_input_from_db(0, image)
boxm2_batch.set_input_float(1, atomicity)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
image_prob = dbvalue(id, type)
return image_prob
def create_taylor_kernel(kernel_path):
print "Creating Taylor Kernel: " + kernel_path
boxm2_batch.init_process("bvplLoadTaylorKernelProcess")
boxm2_batch.set_input_string(0, kernel_path)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
taylor_kernel = dbvalue(id, type)
return taylor_kernel
def scale_scene(scene, scale):
boxm2_batch.init_process("boxm2ScaleSceneProcess")
boxm2_batch.set_input_from_db(0, scene)
boxm2_batch.set_input_float(1, scale)
boxm2_batch.run_process()
(scene_id, scene_type) = boxm2_batch.commit_output(0)
scene = dbvalue(scene_id, scene_type)
return scene
def load_scene(scene_str):
print("Loading a Scene from file: ", scene_str)
boxm2_batch.init_process("boxm2LoadSceneProcess")
boxm2_batch.set_input_string(0, scene_str)
boxm2_batch.run_process()
(scene_id, scene_type) = boxm2_batch.commit_output(0)
scene = dbvalue(scene_id, scene_type)
return scene
def create_local_rational_camera(rational_cam_fname, lvcs_fname):
boxm2_batch.init_process('vpglCreateLocalRationalCameraProcess')
boxm2_batch.set_input_string(0, rational_cam_fname)
boxm2_batch.set_input_string(1, lvcs_fname)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
cam = dbvalue(id, type)
return cam
def load_affine_camera(file_path, viewing_dist=1000):
boxm2_batch.init_process("vpglLoadAffineCameraProcess")
boxm2_batch.set_input_string(0, file_path)
boxm2_batch.set_input_double(1, viewing_dist)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
cam = dbvalue(id, type)
return cam
def persp2genWmargin(pcam, ni, nj, margin, level=0):
boxm2_batch.init_process("vpglConvertToGenericCameraWithMarginProcess")
boxm2_batch.set_input_from_db(0, pcam)
boxm2_batch.set_input_unsigned(1, ni)
boxm2_batch.set_input_unsigned(2, nj)
boxm2_batch.set_input_unsigned(3, level)
boxm2_batch.set_input_int(4, margin)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
gcam = dbvalue(id, type)
(id, type) = boxm2_batch.commit_output(1)
ni = boxm2_batch.get_output_unsigned(id)
(id, type) = boxm2_batch.commit_output(2)
nj = boxm2_batch.get_output_unsigned(id)
(id, type) = boxm2_batch.commit_output(3)
new_pers_cam = dbvalue(id, type)
return (gcam, ni, nj, new_pers_cam)
def atmospheric_correct(image, sun_z):
boxm2_batch.init_process('bbasAtmosphericCorrProcess')
boxm2_batch.set_input_from_db(0, image)
boxm2_batch.set_input_float(1, sun_z)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
image_corrected = dbvalue(id, type)
return image_corrected
def trajectory_direct(trajectory, index):
boxm2_batch.init_process("boxm2ViewTrajectoryDirectProcess")
boxm2_batch.set_input_from_db(0, trajectory)
boxm2_batch.set_input_unsigned(1, index)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
cam = dbvalue(id, type)
return cam
def rotate_perspective_camera(cam_in, theta, phi):
boxm2_batch.init_process('vpglRotatePerspCamProcess')
boxm2_batch.set_input_from_db(0, cam_in)
boxm2_batch.set_input_float(1, theta)
boxm2_batch.set_input_float(2, phi)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
rot_cam = dbvalue(id, type)
return rot_cam
def load_geotiff_cam2(filename, ni, nj):
boxm2_batch.init_process("vpglLoadGeoCameraProcess2")
boxm2_batch.set_input_string(0, filename)
boxm2_batch.set_input_unsigned(1, ni)
boxm2_batch.set_input_unsigned(2, nj)
boxm2_batch.run_process()
(c_id, c_type) = boxm2_batch.commit_output(0)
cam = dbvalue(c_id, c_type)
return cam
def next_frame(rawStream):
boxm2_batch.init_process("bilReadFrameProcess")
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
def combine_planes(img_red, img_green, img_blue):
boxm2_batch.init_process("vilCombinePlanesProcess")
boxm2_batch.set_input_from_db(0, img_red)
boxm2_batch.set_input_from_db(1, img_green)
boxm2_batch.set_input_from_db(2, img_blue)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
img_out = dbvalue(id, type)
return img_out
def mask_image_using_id(img, id_img, input_id):
boxm2_batch.init_process("vilMaskImageUsingIDsProcess")
boxm2_batch.set_input_from_db(0, img)
boxm2_batch.set_input_from_db(1, id_img)
boxm2_batch.set_input_unsigned(2, input_id)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
masked_img = dbvalue(id, type)
return masked_img
def fuse_beliefs(image1, image2, atomicity):
boxm2_batch.init_process("bslFusionProcess")
boxm2_batch.set_input_from_db(0, image1)
boxm2_batch.set_input_from_db(1, image2)
boxm2_batch.set_input_float(2, atomicity)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
fused_image = dbvalue(id, type)
return fused_image
def undistort_image(img, param_file, iters):
boxm2_batch.init_process("vilUndistortImageProcess")
boxm2_batch.set_input_from_db(0, img)
boxm2_batch.set_input_string(1, param_file)
boxm2_batch.set_input_int(2, iters)
boxm2_batch.run_process()
(o_id, o_type) = boxm2_batch.commit_output(0)
out_img = dbvalue(o_id, o_type)
return out_img
def truncate_image(img, min_value, max_value):
boxm2_batch.init_process("vilTruncateImageProcess")
boxm2_batch.set_input_from_db(0, img)
boxm2_batch.set_input_float(1, min_value)
boxm2_batch.set_input_float(2, max_value)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
img_out = dbvalue(id, type)
return img_out
def gradient_angle(Ix, Iy):
boxm2_batch.init_process('vilGradientAngleProcess')
boxm2_batch.set_input_from_db(0, Ix)
boxm2_batch.set_input_from_db(1, Iy)
boxm2_batch.run_process()
# x image
(id, type) = boxm2_batch.commit_output(0)
angleImg = dbvalue(id, type)
return angleImg
def load_geotiff_from_header(filename, lvcs=0):
boxm2_batch.init_process("vpglLoadGeotiffCamFromHeaderProcess")
boxm2_batch.set_input_string(0, filename)
if lvcs != 0:
boxm2_batch.set_input_from_db(1, lvcs)
boxm2_batch.run_process()
(c_id, c_type) = boxm2_batch.commit_output(0)
cam = dbvalue(c_id, c_type)
return cam
def load_image_metadata(filename):
boxm2_batch.init_process("bradLoadImageMetadataProcess")
boxm2_batch.set_input_string(0, filename)
status = boxm2_batch.run_process()
mdata = None
if status:
(id, type) = boxm2_batch.commit_output(0)
mdata = dbvalue(id, type)
return mdata
def translate_geo_camera(geocam, x, y):
boxm2_batch.init_process("vpglTranslateGeoCameraProcess")
boxm2_batch.set_input_from_db(0, geocam)
boxm2_batch.set_input_double(1, x)
boxm2_batch.set_input_double(2, y)
boxm2_batch.run_process()
(c_id, c_type) = boxm2_batch.commit_output(0)
cam = dbvalue(c_id, c_type)
return cam
def correct_rational_camera(cam_in, offset_x, offset_y):
boxm2_batch.init_process('vpglCorrectRationalCameraProcess')
boxm2_batch.set_input_from_db(0, cam_in)
boxm2_batch.set_input_double(1, offset_x)
boxm2_batch.set_input_double(2, offset_y)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
corrected_cam = dbvalue(id, type)
return corrected_cam
def binary_img_op(img1, img2, operation="sum"):
boxm2_batch.init_process("vilBinaryImageOpProcess")
boxm2_batch.set_input_from_db(0, img1)
boxm2_batch.set_input_from_db(1, img2)
boxm2_batch.set_input_string(2, operation)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
out = dbvalue(id, type)
return out
def bae_raw_stream(file_path):
boxm2_batch.init_process("bilCreateRawImageIstreamProcess")
boxm2_batch.set_input_string(0, file_path)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
stream = dbvalue(id, type)
(id, type) = boxm2_batch.commit_output(1)
numImgs = boxm2_batch.get_output_int(id)
return stream, numImgs
def solve_gain_offset(model_image, test_image, test_mask):
boxm2_batch.init_process("bripSolveGainOffsetProcess")
boxm2_batch.set_input_from_db(0, model_image)
boxm2_batch.set_input_from_db(1, test_image)
boxm2_batch.set_input_from_db(3, test_mask)
boxm2_batch.run_process()
(map_image_id, map_image_type) = boxm2_batch.commit_output(0)
map_image = dbvalue(map_image_id, map_image_type)
return map_image
def threshold_image(img, value, threshold_above=True):
boxm2_batch.init_process("vilThresholdImageProcess")
boxm2_batch.set_input_from_db(0, img)
boxm2_batch.set_input_float(1, value)
boxm2_batch.set_input_bool(2, threshold_above)
boxm2_batch.run_process()
(id, type) = boxm2_batch.commit_output(0)
mask = dbvalue(id, type)
return mask
