(img: Union[str, np.ndarray],
result: np.ndarray,
palette: Optional[Iterable] = None,
fig_size: Iterable[int] = (15, 10),
opacity: float = 0.5,
title: str = '',
block: bool = True)
| 74 | |
| 75 | |
| 76 | def show_result_pyplot(img: Union[str, np.ndarray], |
| 77 | result: np.ndarray, |
| 78 | palette: Optional[Iterable] = None, |
| 79 | fig_size: Iterable[int] = (15, 10), |
| 80 | opacity: float = 0.5, |
| 81 | title: str = '', |
| 82 | block: bool = True): |
| 83 | img = mmcv.imread(img) |
| 84 | img = img.copy() |
| 85 | seg = result[0] |
| 86 | seg = mmcv.imresize(seg, img.shape[:2][::-1]) |
| 87 | palette = np.array(palette) |
| 88 | assert palette.shape[1] == 3 |
| 89 | assert len(palette.shape) == 2 |
| 90 | assert 0 < opacity <= 1.0 |
| 91 | color_seg = np.zeros((seg.shape[0], seg.shape[1], 3), dtype=np.uint8) |
| 92 | for label, color in enumerate(palette): |
| 93 | color_seg[seg == label, :] = color |
| 94 | # convert to BGR |
| 95 | color_seg = color_seg[..., ::-1] |
| 96 | |
| 97 | img = img * (1 - opacity) + color_seg * opacity |
| 98 | img = img.astype(np.uint8) |
| 99 | |
| 100 | plt.figure(figsize=fig_size) |
| 101 | plt.imshow(mmcv.bgr2rgb(img)) |
| 102 | plt.title(title) |
| 103 | plt.tight_layout() |
| 104 | plt.show(block=block) |
| 105 | |
| 106 | |
| 107 | def onnx2tensorrt(onnx_file: str, |
no outgoing calls
no test coverage detected