how to visualize Superpoint+FLANN Matches?
lisaring opened this issue · comments
how to get this visualization in the code? Thank you.
check this function:
Lines 38 to 91 in c03e88f
| def plot_matches(image0, image1, kpts0, kpts1, scores=None, layout="lr"): | |
| """ | |
| plot matches between two images. If score is nor None, then red: bad match, green: good match | |
| :param image0: reference image | |
| :param image1: current image | |
| :param kpts0: keypoints in reference image | |
| :param kpts1: keypoints in current image | |
| :param scores: matching score for each keypoint pair, range [0~1], 0: worst match, 1: best match | |
| :param layout: 'lr': left right; 'ud': up down | |
| :return: | |
| """ | |
| H0, W0 = image0.shape[0], image0.shape[1] | |
| H1, W1 = image1.shape[0], image1.shape[1] | |
| if layout == "lr": | |
| H, W = max(H0, H1), W0 + W1 | |
| out = 255 * np.ones((H, W, 3), np.uint8) | |
| out[:H0, :W0, :] = image0 | |
| out[:H1, W0:, :] = image1 | |
| elif layout == "ud": | |
| H, W = H0 + H1, max(W0, W1) | |
| out = 255 * np.ones((H, W, 3), np.uint8) | |
| out[:H0, :W0, :] = image0 | |
| out[H0:, :W1, :] = image1 | |
| else: | |
| raise ValueError("The layout must be 'lr' or 'ud'!") | |
| kpts0, kpts1 = np.round(kpts0).astype(int), np.round(kpts1).astype(int) | |
| # get color | |
| if scores is not None: | |
| smin, smax = scores.min(), scores.max() | |
| assert (0 <= smin <= 1 and 0 <= smax <= 1) | |
| color = cm.gist_rainbow(scores * 0.4) | |
| color = (np.array(color[:, :3]) * 255).astype(int)[:, ::-1] | |
| else: | |
| color = np.zeros((kpts0.shape[0], 3), dtype=int) | |
| color[:, 1] = 255 | |
| for (x0, y0), (x1, y1), c in zip(kpts0, kpts1, color): | |
| c = c.tolist() | |
| if layout == "lr": | |
| cv2.line(out, (x0, y0), (x1 + W0, y1), color=c, thickness=1, lineType=cv2.LINE_AA) | |
| # display line end-points as circles | |
| cv2.circle(out, (x0, y0), 2, c, -1, lineType=cv2.LINE_AA) | |
| cv2.circle(out, (x1 + W0, y1), 2, c, -1, lineType=cv2.LINE_AA) | |
| elif layout == "ud": | |
| cv2.line(out, (x0, y0), (x1, y1 + H0), color=c, thickness=1, lineType=cv2.LINE_AA) | |
| # display line end-points as circles | |
| cv2.circle(out, (x0, y0), 2, c, -1, lineType=cv2.LINE_AA) | |
| cv2.circle(out, (x1, y1 + H0), 2, c, -1, lineType=cv2.LINE_AA) | |
| return out |
check this function:
Lines 38 to 91 in c03e88f
def plot_matches(image0, image1, kpts0, kpts1, scores=None, layout="lr"): """ plot matches between two images. If score is nor None, then red: bad match, green: good match :param image0: reference image :param image1: current image :param kpts0: keypoints in reference image :param kpts1: keypoints in current image :param scores: matching score for each keypoint pair, range [0~1], 0: worst match, 1: best match :param layout: 'lr': left right; 'ud': up down :return: """ H0, W0 = image0.shape[0], image0.shape[1] H1, W1 = image1.shape[0], image1.shape[1] if layout == "lr": H, W = max(H0, H1), W0 + W1 out = 255 * np.ones((H, W, 3), np.uint8) out[:H0, :W0, :] = image0 out[:H1, W0:, :] = image1 elif layout == "ud": H, W = H0 + H1, max(W0, W1) out = 255 * np.ones((H, W, 3), np.uint8) out[:H0, :W0, :] = image0 out[H0:, :W1, :] = image1 else: raise ValueError("The layout must be 'lr' or 'ud'!") kpts0, kpts1 = np.round(kpts0).astype(int), np.round(kpts1).astype(int) # get color if scores is not None: smin, smax = scores.min(), scores.max() assert (0 <= smin <= 1 and 0 <= smax <= 1) color = cm.gist_rainbow(scores * 0.4) color = (np.array(color[:, :3]) * 255).astype(int)[:, ::-1] else: color = np.zeros((kpts0.shape[0], 3), dtype=int) color[:, 1] = 255 for (x0, y0), (x1, y1), c in zip(kpts0, kpts1, color): c = c.tolist() if layout == "lr": cv2.line(out, (x0, y0), (x1 + W0, y1), color=c, thickness=1, lineType=cv2.LINE_AA) # display line end-points as circles cv2.circle(out, (x0, y0), 2, c, -1, lineType=cv2.LINE_AA) cv2.circle(out, (x1 + W0, y1), 2, c, -1, lineType=cv2.LINE_AA) elif layout == "ud": cv2.line(out, (x0, y0), (x1, y1 + H0), color=c, thickness=1, lineType=cv2.LINE_AA) # display line end-points as circles cv2.circle(out, (x0, y0), 2, c, -1, lineType=cv2.LINE_AA) cv2.circle(out, (x1, y1 + H0), 2, c, -1, lineType=cv2.LINE_AA) return out
check this function:
Lines 38 to 91 in c03e88f
def plot_matches(image0, image1, kpts0, kpts1, scores=None, layout="lr"): """ plot matches between two images. If score is nor None, then red: bad match, green: good match :param image0: reference image :param image1: current image :param kpts0: keypoints in reference image :param kpts1: keypoints in current image :param scores: matching score for each keypoint pair, range [0~1], 0: worst match, 1: best match :param layout: 'lr': left right; 'ud': up down :return: """ H0, W0 = image0.shape[0], image0.shape[1] H1, W1 = image1.shape[0], image1.shape[1] if layout == "lr": H, W = max(H0, H1), W0 + W1 out = 255 * np.ones((H, W, 3), np.uint8) out[:H0, :W0, :] = image0 out[:H1, W0:, :] = image1 elif layout == "ud": H, W = H0 + H1, max(W0, W1) out = 255 * np.ones((H, W, 3), np.uint8) out[:H0, :W0, :] = image0 out[H0:, :W1, :] = image1 else: raise ValueError("The layout must be 'lr' or 'ud'!") kpts0, kpts1 = np.round(kpts0).astype(int), np.round(kpts1).astype(int) # get color if scores is not None: smin, smax = scores.min(), scores.max() assert (0 <= smin <= 1 and 0 <= smax <= 1) color = cm.gist_rainbow(scores * 0.4) color = (np.array(color[:, :3]) * 255).astype(int)[:, ::-1] else: color = np.zeros((kpts0.shape[0], 3), dtype=int) color[:, 1] = 255 for (x0, y0), (x1, y1), c in zip(kpts0, kpts1, color): c = c.tolist() if layout == "lr": cv2.line(out, (x0, y0), (x1 + W0, y1), color=c, thickness=1, lineType=cv2.LINE_AA) # display line end-points as circles cv2.circle(out, (x0, y0), 2, c, -1, lineType=cv2.LINE_AA) cv2.circle(out, (x1 + W0, y1), 2, c, -1, lineType=cv2.LINE_AA) elif layout == "ud": cv2.line(out, (x0, y0), (x1, y1 + H0), color=c, thickness=1, lineType=cv2.LINE_AA) # display line end-points as circles cv2.circle(out, (x0, y0), 2, c, -1, lineType=cv2.LINE_AA) cv2.circle(out, (x1, y1 + H0), 2, c, -1, lineType=cv2.LINE_AA) return out
Thank you.