def draw_instance_contours(img, gti, gtl=None, thickness=2, alpha=1, color=None):
"""
img = util.imread('/home/joncrall/remote/aretha/data/UrbanMapper3D/training/TAM_Tile_003_RGB.tif')
gti = util.imread(ub.truepath('~/remote/aretha/data/UrbanMapper3D/training/TAM_Tile_003_GTI.tif'))
gtl = util.imread('/home/joncrall/remote/aretha/data/UrbanMapper3D/training/TAM_Tile_003_GTL.tif')
thickness = 2
alpha = 1
"""
import cv2
grouped_contours = instance_contours(gti)
if gtl is not None:
unknown_labels = set(np.unique(gti[gtl == 65]))
else:
unknown_labels = set()
known_labels = set(grouped_contours.keys()) - unknown_labels
BGR_GREEN = (0, 255, 0)
BGR_BLUE = (255, 0, 0)
img = util.ensure_float01(img)
base = np.ascontiguousarray((255 * img[:, :, 0:3]).astype(np.uint8))
# Draw an image to overlay first
draw_img = np.zeros(base.shape, dtype=np.uint8)
if color is None:
color = BGR_GREEN
known_contours = np.array(list(ub.flatten(list(ub.take(grouped_contours, known_labels)))))
draw_img = cv2.drawContours(
image=draw_img, contours=known_contours,
contourIdx=-1, color=color, thickness=thickness)
if unknown_labels:
unknown_contours = np.array(list(ub.flatten(ub.take(grouped_contours, unknown_labels))))
draw_img = cv2.drawContours(
image=draw_img, contours=unknown_contours,
contourIdx=-1, color=BGR_BLUE, thickness=thickness)
contour_overlay = util.ensure_alpha_channel(draw_img, alpha=0)
contour_overlay.T[3].T[draw_img.sum(axis=2) > 0] = alpha
# zero out the edges to avoid visualization errors
contour_overlay[0:thickness, :, :] = 0
contour_overlay[-thickness:, :, :] = 0
contour_overlay[:, 0:thickness, :] = 0
contour_overlay[:, -thickness:, :] = 0
# img1 = contour_overlay
# img2 = base
# from clab import profiler
# _ = profiler.profile_onthefly(util.overlay_alpha_images)(contour_overlay, base, keepalpha=False)
draw_img = util.overlay_alpha_images(contour_overlay, base, keepalpha=False)
draw_img = np.ascontiguousarray((255 * draw_img[:, :, 0:3]).astype(np.uint8))
return draw_img
def draw_mask_contours(img, gt, thickness=2, alpha=1):
import cv2
gt = gt.astype(np.uint8)
border = cv2.copyMakeBorder(gt, 1, 1, 1, 1, cv2.BORDER_CONSTANT, value=0 )
_, contours, hierarchy = cv2.findContours(border, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE, offset=(-1, -1))
BGR_GREEN = (0, 255, 0)
img = util.ensure_float01(img)
base = np.ascontiguousarray((255 * img[:, :, 0:3]).astype(np.uint8))
if alpha >= 1:
draw_img = cv2.drawContours(
image=base, contours=contours, contourIdx=-1, color=BGR_GREEN,
thickness=thickness)
else:
# Draw an image to overlay first
draw_img = cv2.drawContours(
image=np.zeros(base.shape, dtype=np.uint8), contours=contours,
contourIdx=-1, color=BGR_GREEN, thickness=thickness)
contour_overlay = util.ensure_alpha_channel(draw_img, alpha=0)
contour_overlay.T[3].T[draw_img.sum(axis=2) > 0] = alpha
# zero out the edges to avoid visualization errors
contour_overlay[0:thickness, :, :] = 0
contour_overlay[-thickness:, :, :] = 0
contour_overlay[:, 0:thickness, :] = 0
contour_overlay[:, -thickness:, :] = 0
draw_img = util.overlay_alpha_images(contour_overlay, base)
draw_img = np.ascontiguousarray((255 * draw_img[:, :, 0:3]).astype(np.uint8))
return draw_img
def draw_contours(bgr, contours, thickness=2, alpha=1, color=None):
# TODO: move to somewhere better
BGR_GREEN = (0, 255, 0)
if color is None:
color = BGR_GREEN
bgr = util.ensure_float01(bgr)
base = np.ascontiguousarray((255 * bgr[:, :, 0:3]).astype(np.uint8))
draw_img = np.zeros_like(base)
draw_img = cv2.drawContours(
image=draw_img, contours=contours,
contourIdx=-1, color=color, thickness=thickness)
contour_overlay = util.ensure_alpha_channel(draw_img, alpha=0)
contour_overlay.T[3].T[draw_img.sum(axis=2) > 0] = alpha
draw_img = util.overlay_alpha_images(contour_overlay, base, keepalpha=False)
draw_img = np.ascontiguousarray((255 * draw_img[:, :, 0:3]).astype(np.uint8))
return draw_img