| import numpy as np | |
| def sample_points_from_masks(masks, num_points): | |
| """ | |
| sample points from masks and return its absolute coordinates | |
| Args: | |
| masks: np.array with shape (n, h, w) | |
| num_points: int | |
| Returns: | |
| points: np.array with shape (n, points, 2) | |
| """ | |
| n, h, w = masks.shape | |
| points = [] | |
| for i in range(n): | |
| # find the valid mask points | |
| indices = np.argwhere(masks[i] == 1) | |
| # the output format of np.argwhere is (y, x) and the shape is (num_points, 2) | |
| # we should convert it to (x, y) | |
| indices = indices[:, ::-1] # (num_points, [y x]) to (num_points, [x y]) | |
| # import pdb; pdb.set_trace() | |
| if len(indices) == 0: | |
| # if there are no valid points, append an empty array | |
| points.append(np.array([])) | |
| continue | |
| # resampling if there's not enough points | |
| if len(indices) < num_points: | |
| sampled_indices = np.random.choice(len(indices), num_points, replace=True) | |
| else: | |
| sampled_indices = np.random.choice(len(indices), num_points, replace=False) | |
| sampled_points = indices[sampled_indices] | |
| points.append(sampled_points) | |
| # convert to np.array | |
| points = np.array(points, dtype=np.float32) | |
| return points | |