def draw_object(backg):
obj = sample_object()
mask = calculate_mask(obj)
obj = photometric_seq(image=obj)
det_aug = geometric_seq.to_deterministic()
obj = det_aug(image=obj)
mask = det_aug(image=mask)
bin_mask = (mask > 0.1) * 1.0
row_mask = bin_mask.any(axis=1)
col_mask = bin_mask.any(axis=0)
Xs, = np.where(col_mask > 0.1)
Ys, = np.where(row_mask > 0.1)
try:
x1, y1 = Xs.min(), Ys.min()
x2, y2 = Xs.max(), Ys.max()
except:
x1, y1, x2, y2 = 0, 0, backg.shape[1], backg.shape[0]
x1 *= backg.shape[1] / obj.shape[1]
x2 *= backg.shape[1] / obj.shape[1]
y1 *= backg.shape[0] / obj.shape[0]
y2 *= backg.shape[0] / obj.shape[0]
obj = cv2.resize(obj, (backg.shape[1], backg.shape[0]))
mask = cv2.resize(mask, (backg.shape[1], backg.shape[0]))
if mask.ndim < 3:
mask = np.expand_dims(mask, -1)
return (backg * (1 - mask) + obj * mask).astype('uint8'), x1, y1, x2, y2
def draw_object(backg):
obj = sample_object()
obj = photometric_seq(image=obj)
det_aug = geometric_seq.to_deterministic()
obj = det_aug(image=obj)
x1, y1, x2, y2 = 0, 0, obj.shape[1], obj.shape[0]
x1 *= backg.shape[1] / obj.shape[1]
x2 *= backg.shape[1] / obj.shape[1]
y1 *= backg.shape[0] / obj.shape[0]
y2 *= backg.shape[0] / obj.shape[0]
obj = cv2.resize(obj, (backg.shape[1], backg.shape[0]))
return obj.astype('uint8'), x1, y1, x2, y2