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);
