def write_six_img_grid_w_embedded_names(
rgb_img: np.ndarray,
pred: np.ndarray,
label_img: np.ndarray,
id_to_class_name_map: Mapping[int,str],
save_fpath: str
) -> None:
"""
Create a 6-image tile grid with the following structure:
------------------------------------------------------------
RGB Image | Blended RGB+GT Label Map | GT Label Map
------------------------------------------------------------
RGB Image | Blended RGB+Pred Label Map | Predicted Label Map
------------------------------------------------------------
We embed classnames directly into the predicted and ground
truth label maps, instead of using a colorbar.
Args:
rgb_img:
pred: predicted label map
label_img
id_to_class_name_map
save_fpath
"""
assert label_img.ndim == 2
assert pred.ndim == 2
assert rgb_img.ndim == 3
label_hgrid = form_mask_triple_embedded_classnames(
rgb_img,
label_img,
id_to_class_name_map,
save_fpath='dummy.jpg',
save_to_disk=False
)
pred_hgrid = form_mask_triple_embedded_classnames(
rgb_img,
pred,
id_to_class_name_map,
save_fpath='dummy.jpg',
save_to_disk=False
)
vstack_img = form_vstacked_imgs(
img_list=[label_hgrid,pred_hgrid],
vstack_save_fpath=save_fpath,
save_to_disk=True
)
def form_mask_triple_vertical(rgb_img: np.ndarray,
label_img: np.ndarray,
save_fpath: str,
save_to_disk: bool = False) -> np.ndarray:
"""
Args:
- rgb_img:
- label_img:
- save_fpath
- save_to_disk
Returns:
- Array, representing 3 horizontally concatenated images: from left-to-right, they are
RGB, RGB+Semantic Masks, Semantic Masks
"""
rgb_with_mask = convert_instance_img_to_mask_img(label_img, rgb_img.copy())
mask_img = convert_instance_img_to_mask_img(label_img, img_rgb=None)
return form_vstacked_imgs([rgb_img, rgb_with_mask, mask_img], save_fpath,
save_to_disk)
def test_form_vstacked_imgs_two(): """ Vertically stack two 2x2 RGB images into a single 2x4 RGB image. """ vstack_save_fpath = 'vtmp.png' img1 = np.zeros((2,2,3), dtype=np.uint8) img1[0,0,:] = [255,0,1] img2 = np.zeros((2,2,3), dtype=np.uint8) img2[1,1,:] = [5,10,15] img_list = [img1, img2] vstack_img = form_vstacked_imgs(img_list, vstack_save_fpath, save_to_disk=False) gt_vstack_img = np.zeros((4,2,3), dtype=np.uint8) gt_vstack_img[0,0,:] = [255,0,1] gt_vstack_img[3,1,:] = [5,10,15] assert np.allclose(vstack_img, gt_vstack_img)