Write optical flow to file. If the flow is not quantized, it will be saved as a .flo file losslessly, otherwise a jpeg image which is lossy but of much smaller size. (dx and dy will be concatenated horizontally into a single image if quantize is True.) Args: flow (ndarray):
(flow, filename, quantize=False, concat_axis=0, *args, **kwargs)
| 43 | |
| 44 | |
| 45 | def flowwrite(flow, filename, quantize=False, concat_axis=0, *args, **kwargs): |
| 46 | """Write optical flow to file. |
| 47 | |
| 48 | If the flow is not quantized, it will be saved as a .flo file losslessly, |
| 49 | otherwise a jpeg image which is lossy but of much smaller size. (dx and dy |
| 50 | will be concatenated horizontally into a single image if quantize is True.) |
| 51 | |
| 52 | Args: |
| 53 | flow (ndarray): (h, w, 2) array of optical flow. |
| 54 | filename (str): Output filepath. |
| 55 | quantize (bool): Whether to quantize the flow and save it to 2 jpeg |
| 56 | images. If set to True, remaining args will be passed to |
| 57 | :func:`quantize_flow`. |
| 58 | concat_axis (int): The axis that dx and dy are concatenated, |
| 59 | can be either 0 or 1. Ignored if quantize is False. |
| 60 | """ |
| 61 | if not quantize: |
| 62 | with open(filename, 'wb') as f: |
| 63 | f.write('PIEH'.encode('utf-8')) |
| 64 | np.array([flow.shape[1], flow.shape[0]], dtype=np.int32).tofile(f) |
| 65 | flow = flow.astype(np.float32) |
| 66 | flow.tofile(f) |
| 67 | f.flush() |
| 68 | else: |
| 69 | assert concat_axis in [0, 1] |
| 70 | dx, dy = quantize_flow(flow, *args, **kwargs) |
| 71 | dxdy = np.concatenate((dx, dy), axis=concat_axis) |
| 72 | os.makedirs(os.path.dirname(filename), exist_ok=True) |
| 73 | cv2.imwrite(filename, dxdy) |
| 74 | |
| 75 | |
| 76 | def quantize_flow(flow, max_val=0.02, norm=True): |
nothing calls this directly
no test coverage detected