def save_img_results_test(imgs_tcpu, real_box, boxes_pred, count, test_dir):
num = cfg.TRAIN.VIS_COUNT
# The range of real_img (i.e., self.imgs_tcpu[i][0:num])
# is changed to [0, 1] by function vutils.save_image
real_img = imgs_tcpu[-1][0:num]
vutils.save_image(
real_img, '%s/count_%09d_real_samples.png' % (test_dir, count),
normalize=True)
# save bounding box images
vutils.save_bbox(
real_img, real_box, '%s/count_%09d_real_bbox.png' % (test_dir, count),
normalize=True)
vutils.save_bbox(
real_img, boxes_pred, '%s/count_%09d_fake_bbox.png' % (test_dir, count),
normalize=True)
# save floor plan images
vutils.save_floor_plan(
real_img, real_box, '%s/count_%09d_real_floor_plan.png' % (test_dir, count),
normalize=True)
vutils.save_floor_plan(
real_img, boxes_pred, '%s/count_%09d_fake_floor_plan.png' % (test_dir, count),
normalize=True)
def visualize(boxes_coords, boxes_types, save_pic_path):
"""
function: visualize the coord to check as follow
box_collection: [(tensor([[boxes_coord],[boxes_coord],..]), [tensor,tensor,...])]
example:[(tensor([[0.6235, 0.3686, 0.3373, 0.3686],
[0.3373, 0.3686, 0.3373, 0.6941],
[0.3373, 0.6941, 0.6235, 0.6941],
[0.6235, 0.6941, 0.6235, 0.3686],
[0.6235, 0.3686, 0.6235, 0.3686]]),
[tensor(0.), tensor(0.), tensor(0.), tensor(0.), tensor(0.)])]
"""
import vutils
boxes_types_tensor = [torch.tensor(boxes_types[t]) for t in range(len(boxes_types))]
boxes_coords = torch.tensor(boxes_coords)
boxes_collection = [(boxes_coords, boxes_types_tensor)]
background = np.zeros((256, 256))
vutils.save_bbox(background, boxes_collection, save_pic_path, normalize=True, draw_line=True)
def visualize(boxes_coord, boxes_type, save_pic_path):
"""
boxes_coord:[[],[],..] boxes_type:[]
box_collection: [(tensor([[boxes_coord],[boxes_coord],..]), [tensor,tensor,...])]
example:[(tensor([[0.6235, 0.3686, 0.3373, 0.3686],
[0.3373, 0.3686, 0.3373, 0.6941],
[0.3373, 0.6941, 0.6235, 0.6941],
[0.6235, 0.6941, 0.6235, 0.3686],
[0.6235, 0.3686, 0.6235, 0.3686]]),
[tensor(0.), tensor(0.), tensor(0.), tensor(0.), tensor(0.)])]
"""
# visualize the coord to check as follow
import vutils
boxes_type = [torch.tensor(boxes_type[i]) for i in range(len(boxes_type))]
boxes_coord = torch.tensor(boxes_coord)
boxes_collection = [(boxes_coord, boxes_type)]
background = np.zeros((256, 256))
vutils.save_bbox(background, boxes_collection, save_pic_path, normalize=True, draw_line=True)