def __init__(self, index, type): self.id = index # unsigned integer self.type = type # string dir = "/Users/isa/Experiments/super3d/scene/expectedImgs_2" test_frames = [8, 112, 96, 208] for frame in test_frames: boxm_batch.init_process("vilLoadImageViewProcess") boxm_batch.set_input_string(0, dir + "/predicted_img_mask_%(#)05d.tiff" % {"#": frame}) boxm_batch.run_process() (id, type) = boxm_batch.commit_output(0) vis_img = dbvalue(id, type) boxm_batch.init_process("vilThresholdImageProcess") boxm_batch.set_input_from_db(0, vis_img) boxm_batch.set_input_float(1, 0.99) boxm_batch.set_input_bool(2, True) boxm_batch.run_process() (id, type) = boxm_batch.commit_output(0) mask_img = dbvalue(id, type) boxm_batch.init_process("vilSaveImageViewProcess") boxm_batch.set_input_from_db(0, mask_img) boxm_batch.set_input_string(1, dir + "/binary_mask_%(#)05d.tiff" % {"#": frame}) boxm_batch.run_process() boxm_batch.remove_data(vis_img.id) boxm_batch.remove_data(mask_img.id)
boxm_batch.run_process(); boxm_batch.init_process("vilLoadImageViewProcess"); boxm_batch.set_input_string(0,original_img_dir + "/frames_%(#)05d.tif"%{"#":frame}); boxm_batch.run_process(); (id,type) = boxm_batch.commit_output(0); true_img = dbvalue(id,type); boxm_batch.init_process("vilImageSSDProcess"); boxm_batch.set_input_from_db(0,pred_img_byte); boxm_batch.set_input_from_db(1,true_img); boxm_batch.run_process(); (id,type) = boxm_batch.commit_output(0); ssd = dbvalue(id,type); ssd_val = boxm_batch.get_output_float(ssd.id); ssd_vals.append(ssd_val); ssd_avg = ssd_avg + ssd_val; boxm_batch.remove_data(pred_img.id) boxm_batch.remove_data(true_img.id) ssd_file = dir + "/ssd.txt" f = open(ssd_file, 'w'); f.write(str(ssd_vals)); f.write("\n"); f.write(str(ssd_avg/(npixels*len(test_frames)))); f.close();
(id, type) = boxm_batch.commit_output(0) image = dbvalue(id, type) 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) 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)
boxm_batch.set_input_unsigned(2,1280); boxm_batch.set_input_unsigned(3,720); boxm_batch.set_input_bool(4,0); boxm_batch.run_process(); (id,type) = boxm_batch.commit_output(0); expected = dbvalue(id,type); (id,type) = boxm_batch.commit_output(1); mask = dbvalue(id,type); print("saving expected image"); boxm_batch.init_process("vilSaveImageViewProcess"); boxm_batch.set_input_from_db(0,expected); boxm_batch.set_input_string(1,expected_fname % it); boxm_batch.run_process(); boxm_batch.remove_data(expected.id); boxm_batch.remove_data(mask.id); if ( (do_refine) & (it+1 < num_its) ): print("Refining Scene"); boxm_batch.init_process("boxmRefineSceneProcess"); boxm_batch.set_input_from_db(0,scene); boxm_batch.set_input_float(1,refine_prob); boxm_batch.set_input_bool(2,False); boxm_batch.run_process(); boxm_batch.remove_data(cam.id); boxm_batch.remove_data(image.id); print("Save Scene"); boxm_batch.init_process("boxmSaveOccupancyRawProcess");
if not os.path.isdir(grey_dir + '/'): os.mkdir(grey_dir + '/'); rgb_imgs = glob.glob1(rgb_dir, '*.png'); for img in rgb_imgs: #tif_img_name = os.path.splitext(img)[0] + '.tif'; boxm_batch.init_process("vilLoadImageViewProcess"); boxm_batch.set_input_string(0,rgb_dir + '/' + img); boxm_batch.run_process(); (id,type) = boxm_batch.commit_output(0); rgb_img = dbvalue(id,type); boxm_batch.init_process("vilRGBToGreyProcess"); boxm_batch.set_input_from_db(0,rgb_img); boxm_batch.run_process(); (id,type) = boxm_batch.commit_output(0); grey_img = dbvalue(id,type); boxm_batch.init_process("vilSaveImageViewProcess"); boxm_batch.set_input_from_db(0,grey_img); boxm_batch.set_input_string(1,grey_dir + '/' + img); boxm_batch.run_process(); boxm_batch.remove_data(rgb_img.id) boxm_batch.remove_data(grey_img.id)
(id,type) = boxm_batch.commit_output(0); image = dbvalue(id,type); 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); 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);