def createScene(self, stepNum): bundleFile = os.path.abspath(self.config.NVMFileName) imgDir = os.path.abspath(self.config.SRCImageDirName) outDir = os.path.abspath(self.config.NVMOutputDirName) if False == os.path.isfile(bundleFile): log("Step %d - SceneCreation cannot begin because the NVM file %s is missing." % (stepNum, bundleFile)) log("Processing will not proceed.") return -stepNum if False == os.path.isdir(imgDir): log("Step %d - SceneCreation cannot beging because the image directory %s cannot be found." % (stepNum, imgDir)) log("Processing will not proceed.") return -stepNum log("Creating scene with bundleFile %s." % (bundleFile)) log("Output will be written to %s." % (outDir)) boxm2_batch.not_verbose() boxm2_batch.register_processes() boxm2_batch.register_datatypes() # class used for python/c++ pointers in database class dbvalue: def __init__(self, index, type): self.id = index # unsigned integer self.type = type # string # run process boxm2_batch.init_process("boxm2BundleToSceneProcess") boxm2_batch.set_input_string(0, bundleFile) boxm2_batch.set_input_string(1, imgDir) boxm2_batch.set_input_string(2, self.config.NVMAppModel) boxm2_batch.set_input_string(3, self.config.NVMNobsModel) boxm2_batch.set_input_int(4, 8) boxm2_batch.set_input_string(5, outDir) boxm2_batch.run_process() (scene_id, scene_type) = boxm2_batch.commit_output(0) uscene = dbvalue(scene_id, scene_type) (scene_id, scene_type) = boxm2_batch.commit_output(1) rscene = dbvalue(scene_id, scene_type) return 0
# Recovering the correct offsets for rpc cameras # # s3_copy_files_from_local.py <local_folder> <name_ending> <hdfs_folder> # # all the files in <local_folder> as: # <local_folder>/*<name_ending> will be copied over to <hdfs_working_dir>/<hdfs_folder> on hdfs # e.g. python s3_copy_files_from_local.py ./crops _normalized.png world_dir # <hdfs_working_dir> will be retrieved from <hdfs> manager # import boxm2_batch boxm2_batch.register_processes() boxm2_batch.register_datatypes() import glob import random import math import os import shutil import time import sys class dbvalue: def __init__(self, index, type): self.id = index # unsigned integer self.type = type # string print "create FS" boxm2_batch.init_process("bhdfsCreateFSManagerProcess") boxm2_batch.set_input_string(0, "default") boxm2_batch.set_input_int(1, 0)
# Recovering the correct offsets for rpc cameras # # s4_prepare_stdin_txt.py <local_folder1> <name_ending1> <local folder2> <name_ending2> <hdfs file name> <hdfs_output_folder> # # prepare a file list with all the files in <local_folder1> as: # <local_folder1>/*<name_ending1> # a list such as # <hdfs_working_dir>/<hdfs_output_folder>/<file name1> <hdfs_working_dir>/<hdfs_output_folder>/<file name2> # and copy the file to <hdfs_working_dir>/<hdfs file name> ; <hdfs_working_dir> will be retrieved from <hdfs> manager # e.g. python ./crops _normalized.png ./crops ./crops/exp_imgs _exp.png some_hdfs_folder/input_stdin.txt hadoop_output_folder # # # import boxm2_batch boxm2_batch.register_processes() boxm2_batch.register_datatypes() import glob import random import math import os import shutil import time import sys class dbvalue: def __init__(self, index, type): self.id = index # unsigned integer self.type = type # string
def writeSceneFromBox(data_path, resolution, min_pt, max_pt, ntrees_x=64,ntrees_y=64,ntrees_z=64, max_num_lvls=4, appearance_model1 = "boxm2_mog3_grey", appearance_model2 = "boxm2_num_obs", appearance_model3 = "boxm2_sum_log_msg_pos", p_init=0.001,max_data_size=1500.0): """A function that takes the minimum and maximum points of a bounding box for the scene in real world coordinates and partitions the space into the appropriate number of boxes given a user specified number of trees. min_pt : A python list specifying the 3d position of the minimum corner of the box. This is interpreted by boxm2 as the 3d origin of the scene. max-pt : A python list specifying the 3d position of the maximum corner of the box. ntrees : Number of trees in all dimensions (the python interface only supports symmetric trees thus far) max_num_lvls : Maximum number of levels in the trees (a tree will have pow(2,max_num_lvls-1) possible cells) appearance_model : A string indicating desired appearance model occupancy_model : A string indicating desired occupancy model max_data_size : Maximum Sizer of a block in megabytes. Determined by GPU memory. Recomment 650MB for 1GB card and 1.1GB for 1.5GM card maximum_data_size : Maximum memory allowable for a superblock. The max_data_size is determined by GPU memory size. For a 1 GB card, a maximum data size of 650MB is recommended. For a 1.5GB card, a 1.1G maximum data size of 1.1GB is recommended. p_init : Initial occupancy probability.""" boxm2_batch.register_processes(); boxm2_batch.register_datatypes(); tree_size=resolution*pow(2,max_num_lvls-1); block_size_x=ntrees_x*tree_size; block_size_y=ntrees_y*tree_size; block_size_z=ntrees_z*tree_size; xsize=max_pt[0]-min_pt[0]; ysize=max_pt[1]-min_pt[1]; zsize=max_pt[2]-min_pt[2]; print "zsize: %f" % zsize print "block size: %f" % block_size_z nblocks_x=int(round(xsize/block_size_x)); nblocks_y=int(round(ysize/block_size_y)); nblocks_z=int(round(zsize/block_size_z)); print "nblocks_z : %f" % nblocks_z if(nblocks_x<=0):nblocks_x=1; if(nblocks_y<=0):nblocks_y=1; if(nblocks_z<=0):nblocks_z=1; print '\t Number of blocks in the x dimension: %d' % nblocks_x print '\t Number of blocks in the y dimension: %d' % nblocks_y print '\t Number of blocks in the z dimension: %d' % nblocks_z print("\t CREATING THE BOXM2_SCENE_SPTR") boxm2_batch.init_process("boxm2CreateSceneProcess"); boxm2_batch.set_input_string(0,data_path); boxm2_batch.set_input_string(1,appearance_model1); boxm2_batch.set_input_string(2,appearance_model2); boxm2_batch.set_input_string(3,appearance_model3); boxm2_batch.set_input_float(4,min_pt[0]); boxm2_batch.set_input_float(5,min_pt[1]); boxm2_batch.set_input_float(6,min_pt[2]); boxm2_batch.run_process(); (id,type)=boxm2_batch.commit_output(0); scene=dbvalue(id,type); for k in range(nblocks_z): for j in range(nblocks_y): for i in range(nblocks_x): block_origin_x=min_pt[0]+i*block_size_x; block_origin_y=min_pt[1]+j*block_size_y; block_origin_z=min_pt[2]+k*block_size_z; print '\t \t Creating block with id (%d,%d,%d) at origin (%s,%s,%s)' % (i,j,k,block_origin_x, block_origin_y, block_origin_z) boxm2_batch.init_process("boxm2AddBlockProcess"); boxm2_batch.set_input_from_db(0,scene); boxm2_batch.set_input_int(1,i); boxm2_batch.set_input_int(2,j); boxm2_batch.set_input_int(3,k); boxm2_batch.set_input_unsigned(4,ntrees_x); boxm2_batch.set_input_unsigned(5,ntrees_y); boxm2_batch.set_input_unsigned(6,ntrees_z); boxm2_batch.set_input_unsigned(7,max_num_lvls); boxm2_batch.set_input_float(8,block_origin_x); boxm2_batch.set_input_float(9,block_origin_y); boxm2_batch.set_input_float(10,block_origin_z); boxm2_batch.set_input_float(11,tree_size); boxm2_batch.set_input_float(12,max_data_size); boxm2_batch.set_input_float(13,p_init); boxm2_batch.set_input_unsigned(14,1); boxm2_batch.run_process(); boxm2_batch.init_process("boxm2WriteSceneXMLProcess") boxm2_batch.set_input_from_db(0,scene); boxm2_batch.set_input_string(1,"scene"); boxm2_batch.run_process();
def boxm2WriteSceneXML(data_path, resolution, origin, nblocks_x, nblocks_y,nblocks_z,ntrees=64,max_num_lvls=4, appearance_model = "boxm2_mog3_grey", occupancy_model = "boxm2_num_obs", max_data_size=650.0,p_init=0.001): """This is boxm2WriteSceneXML.py Function to create a boxm2 scene XML file Author: Brandon Mayer Date: 4/6/2011 data_path : A directory to which the xml file should be saved origin : A python list specifying the 3d origin (x,y,z) nblocks_x : Number of superblocks in the x dimension nblocks_y : Number of superblocks in the y dimension nblocks_z : Number of superblocks in the z dimension ntrees : Number of trees in all dimensions (the python interface only supports symmetric trees thus far) max_num_lvls : Maximum number of levels in the trees (a tree will have pow(2,max_num_lvls-1) possible cells) appearance_model : A string indicating desired appearance model occupancy_model : A string indicating desired occupancy model maximum_data_size : Maximum memory allowable for a superblock. The max_data_size is determined by GPU memory size. For a 1 GB card, a maximum data size of 650MB is recommended. For a 1.5GB card, a 1.1G maximum data size of 1.1GB is recommended. p_init : Initial occupancy probability.""" boxm2_batch.register_processes(); boxm2_batch.register_datatypes(); tree_size=resolution*pow(2,max_num_lvls-1); block_size=ntrees*tree_size; print("\t Creating the boxm2_scene_sptr") boxm2_batch.init_process("boxm2CreateSceneProcess"); boxm2_batch.set_input_string(0,data_path); boxm2_batch.set_input_string(1,appearance_model); boxm2_batch.set_input_string(2,occupancy_model); boxm2_batch.set_input_float(3,origin[0]); boxm2_batch.set_input_float(4,origin[1]); boxm2_batch.set_input_float(5,origin[2]); boxm2_batch.run_process(); (id,type) = boxm2_batch.commit_output(0); scene = dbvalue(id,type); for i in range(nblocks_x): for j in range(nblocks_y): for k in range(nblocks_z): block_origin_x=origin[0]+i*block_size; block_origin_y=origin[1]+j*block_size; block_origin_z=origin[2]+k*block_size; print '\t Creating block with id (%d,%d,%d) at origin (%s,%s,%s)' % (i,j,k,block_origin_x, block_origin_y, block_origin_z) boxm2_batch.init_process("boxm2AddBlockProcess"); boxm2_batch.set_input_from_db(0,scene); boxm2_batch.set_input_unsigned(1,i); boxm2_batch.set_input_unsigned(2,j); boxm2_batch.set_input_unsigned(3,k); boxm2_batch.set_input_unsigned(4,ntrees); boxm2_batch.set_input_unsigned(5,ntrees); boxm2_batch.set_input_unsigned(6,ntrees); boxm2_batch.set_input_unsigned(7,max_num_lvls); boxm2_batch.set_input_float(8,block_origin_x); boxm2_batch.set_input_float(9,block_origin_y); boxm2_batch.set_input_float(10,block_origin_z); boxm2_batch.set_input_float(11,tree_size); boxm2_batch.set_input_float(12,max_data_size); boxm2_batch.set_input_float(13,p_init); boxm2_batch.run_process(); boxm2_batch.init_process("boxm2WriteSceneXMLProcess") boxm2_batch.set_input_from_db(0,scene) boxm2_batch.run_process();
def writeSceneFromBox(data_path, resolution, min_pt, max_pt, ntrees_x=64, ntrees_y=64, ntrees_z=64, max_num_lvls=4, appearance_model1="boxm2_mog3_grey", appearance_model2="boxm2_num_obs", appearance_model3="boxm2_sum_log_msg_pos", p_init=0.001, max_data_size=1500.0): """A function that takes the minimum and maximum points of a bounding box for the scene in real world coordinates and partitions the space into the appropriate number of boxes given a user specified number of trees. min_pt : A python list specifying the 3d position of the minimum corner of the box. This is interpreted by boxm2 as the 3d origin of the scene. max-pt : A python list specifying the 3d position of the maximum corner of the box. ntrees : Number of trees in all dimensions (the python interface only supports symmetric trees thus far) max_num_lvls : Maximum number of levels in the trees (a tree will have pow(2,max_num_lvls-1) possible cells) appearance_model : A string indicating desired appearance model occupancy_model : A string indicating desired occupancy model max_data_size : Maximum Sizer of a block in megabytes. Determined by GPU memory. Recomment 650MB for 1GB card and 1.1GB for 1.5GM card maximum_data_size : Maximum memory allowable for a superblock. The max_data_size is determined by GPU memory size. For a 1 GB card, a maximum data size of 650MB is recommended. For a 1.5GB card, a 1.1G maximum data size of 1.1GB is recommended. p_init : Initial occupancy probability.""" boxm2_batch.register_processes() boxm2_batch.register_datatypes() tree_size = resolution * pow(2, max_num_lvls - 1) block_size_x = ntrees_x * tree_size block_size_y = ntrees_y * tree_size block_size_z = ntrees_z * tree_size xsize = max_pt[0] - min_pt[0] ysize = max_pt[1] - min_pt[1] zsize = max_pt[2] - min_pt[2] print "zsize: %f" % zsize print "block size: %f" % block_size_z nblocks_x = int(round(xsize / block_size_x)) nblocks_y = int(round(ysize / block_size_y)) nblocks_z = int(round(zsize / block_size_z)) print "nblocks_z : %f" % nblocks_z if (nblocks_x <= 0): nblocks_x = 1 if (nblocks_y <= 0): nblocks_y = 1 if (nblocks_z <= 0): nblocks_z = 1 print '\t Number of blocks in the x dimension: %d' % nblocks_x print '\t Number of blocks in the y dimension: %d' % nblocks_y print '\t Number of blocks in the z dimension: %d' % nblocks_z print("\t CREATING THE BOXM2_SCENE_SPTR") boxm2_batch.init_process("boxm2CreateSceneProcess") boxm2_batch.set_input_string(0, data_path) boxm2_batch.set_input_string(1, appearance_model1) boxm2_batch.set_input_string(2, appearance_model2) boxm2_batch.set_input_string(3, appearance_model3) boxm2_batch.set_input_float(4, min_pt[0]) boxm2_batch.set_input_float(5, min_pt[1]) boxm2_batch.set_input_float(6, min_pt[2]) boxm2_batch.run_process() (id, type) = boxm2_batch.commit_output(0) scene = dbvalue(id, type) for k in range(nblocks_z): for j in range(nblocks_y): for i in range(nblocks_x): block_origin_x = min_pt[0] + i * block_size_x block_origin_y = min_pt[1] + j * block_size_y block_origin_z = min_pt[2] + k * block_size_z print '\t \t Creating block with id (%d,%d,%d) at origin (%s,%s,%s)' % ( i, j, k, block_origin_x, block_origin_y, block_origin_z) boxm2_batch.init_process("boxm2AddBlockProcess") boxm2_batch.set_input_from_db(0, scene) boxm2_batch.set_input_int(1, i) boxm2_batch.set_input_int(2, j) boxm2_batch.set_input_int(3, k) boxm2_batch.set_input_unsigned(4, ntrees_x) boxm2_batch.set_input_unsigned(5, ntrees_y) boxm2_batch.set_input_unsigned(6, ntrees_z) boxm2_batch.set_input_unsigned(7, max_num_lvls) boxm2_batch.set_input_float(8, block_origin_x) boxm2_batch.set_input_float(9, block_origin_y) boxm2_batch.set_input_float(10, block_origin_z) boxm2_batch.set_input_float(11, tree_size) boxm2_batch.set_input_float(12, max_data_size) boxm2_batch.set_input_float(13, p_init) boxm2_batch.set_input_unsigned(14, 1) boxm2_batch.run_process() boxm2_batch.init_process("boxm2WriteSceneXMLProcess") boxm2_batch.set_input_from_db(0, scene) boxm2_batch.set_input_string(1, "scene") boxm2_batch.run_process()