boxm_batch.init_process("vilImageSizeProcess") boxm_batch.set_input_from_db(0, image) boxm_batch.run_process() (ni_id, type) = boxm_batch.commit_output(0) (nj_id, type) = boxm_batch.commit_output(1) ni = boxm_batch.get_input_unsigned(ni_id) nj = boxm_batch.get_input_unsigned(nj_id) if ni > nj: sizes.append(ni) else: sizes.append(nj) # set up the connectivity table to be used for computing tracks from the # matches boxm_batch.init_process("baplCreateConnTableProcess") boxm_batch.set_input_int(0, img_cnt) boxm_batch.run_process() (id, type) = boxm_batch.commit_output(0) conn_table = dbvalue(id, type) key_sets = [] for i in range(0, img_cnt, 1): if keys_available: # warning: remove this option boxm_batch.init_process("baplLoadKeypointsProcess") boxm_batch.set_input_string(0, output_path + out_key_name % i) boxm_batch.run_process() (id, type) = boxm_batch.commit_output(0) out_set = dbvalue(id, type) key_sets.append(out_set)
model_dir ="/Users/isa/Experiments/CapitolBOXM_6_4_4"; output_path = "/Users/isa/Experiments/tests/ocl_scene"; if not os.path.isdir( output_path + "/"): os.mkdir( output_path + "/"); max_mb = -1; print("Creating a Scene"); boxm_batch.init_process("boxmCreateSceneProcess"); boxm_batch.set_input_string(0, model_dir + "/capitol_scene.xml"); boxm_batch.run_process(); (scene_id, scene_type) = boxm_batch.commit_output(0); scene = dbvalue(scene_id, scene_type); print("Convert Scene"); boxm_batch.init_process("boxmOclConvertBoxmToOclProcess"); boxm_batch.set_input_from_db(0, scene); boxm_batch.set_input_string(1, output_path); boxm_batch.set_input_int(2, -1); boxm_batch.set_input_bool(3, 0); boxm_batch.run_process(); # print("Refine Scene"); # boxm_batch.init_process("boxmOclRefineProcess"); # boxm_batch.set_input_string(0, "F:/APl/try4ocl/scene.xml"); # boxm_batch.set_input_float(1, prob_thresh); # boxm_batch.run_process();
boxm_batch.set_input_from_db(0, image); boxm_batch.run_process(); (ni_id, type) = boxm_batch.commit_output(0); (nj_id, type) = boxm_batch.commit_output(1); ni=boxm_batch.get_input_unsigned(ni_id); nj=boxm_batch.get_input_unsigned(nj_id); if ni > nj: sizes.append(ni); else: sizes.append(nj); boxm_batch.remove_data(image.id); # set up the connectivity table to be used for computing tracks from the matches boxm_batch.init_process("baplCreateConnTableProcess"); boxm_batch.set_input_int(0, img_cnt); boxm_batch.run_process(); (id,type) = boxm_batch.commit_output(0); conn_table = dbvalue(id,type); for i in range(0,img_cnt,1): print("Loading Image"); boxm_batch.init_process("vilLoadImageViewProcess"); boxm_batch.set_input_string(0,img_path + img_name % (i*every_nth+1)); boxm_batch.run_process(); (id,type) = boxm_batch.commit_output(0); image = dbvalue(id,type); if keypoints_available: boxm_batch.init_process("baplLoadKeypointsProcess"); boxm_batch.set_input_string(0,output_path + out_key_name % (i*every_nth+1));