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fix 4.x links

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This commit is contained in:
Alexander Alekhin
2021-12-22 13:01:26 +00:00
parent be110d0464
commit c78a8dfd2d
134 changed files with 334 additions and 332 deletions
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doc/tutorials/dnn/dnn_pytorch_tf_segmentation/pytorch_sem_segm_model_conversion_tutorial.md
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@@ -258,7 +258,7 @@ python -m dnn_model_runner.dnn_conversion.pytorch.segmentation.py_to_py_segm --m
Chosen from the list segmentation model will be read into OpenCV ``cv.dnn_Net`` object. Evaluation results of PyTorch and OpenCV models (pixel accuracy, mean IoU, inference time) will be written into the log file. Inference time values will be also depicted in a chart to generalize the obtained model information.
Necessary evaluation configurations are defined in the [``test_config.py``](https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py):
Necessary evaluation configurations are defined in the [``test_config.py``](https://github.com/opencv/opencv/tree/4.x/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py):
```python
@dataclass
@@ -290,7 +290,7 @@ python -m dnn_model_runner.dnn_conversion.pytorch.segmentation.py_to_py_segm --m
Here ``default_img_preprocess`` key defines whether you'd like to parametrize the model test process with some particular values or use the default values, for example, ``scale``, ``mean`` or ``std``.
Test configuration is represented in [``test_config.py``](https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py) ``TestSegmModuleConfig`` class:
Test configuration is represented in [``test_config.py``](https://github.com/opencv/opencv/tree/4.x/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py) ``TestSegmModuleConfig`` class:
```python
@dataclass
doc/tutorials/dnn/dnn_pytorch_tf_segmentation/tf_sem_segm_model_conversion_tutorial.md
+2 -2
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@@ -338,7 +338,7 @@ python -m dnn_model_runner.dnn_conversion.tf.segmentation.py_to_py_segm
The model will be read into OpenCV ``cv.dnn_Net`` object. Evaluation results of TF and OpenCV models (pixel accuracy, mean IoU, inference time) will be written into the log file. Inference time values will be also depicted in a chart to generalize the obtained model information.
Necessary evaluation configurations are defined in the [``test_config.py``](https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py):
Necessary evaluation configurations are defined in the [``test_config.py``](https://github.com/opencv/opencv/tree/4.x/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py):
```python
@dataclass
@@ -364,7 +364,7 @@ python -m dnn_model_runner.dnn_conversion.tf.segmentation.py_to_py_segm --test T
Here ``default_img_preprocess`` key defines whether you'd like to parametrize the model test process with some particular values or use the default values, for example, ``scale``, ``mean`` or ``std``.
Test configuration is represented in [``test_config.py``](https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py) ``TestSegmModuleConfig`` class:
Test configuration is represented in [``test_config.py``](https://github.com/opencv/opencv/tree/4.x/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py) ``TestSegmModuleConfig`` class:
```python
@dataclass