[DOC] Improved readability of the warnings

doc/tutorial/detection_dnn/tutorial-detection-dnn.dox

@@ -474,10 +474,9 @@ If you want to train your own YoloV7 model, please refer to the [official docume
 If your dataset is rather small (only hundreds of pictures), you may want to consider to base your training on
 `yolov7-tiny` network, as it tends to get better results.
 
-**Important note**: if you train your own model, be sure to use the same image size in the `python train.py`,
-`python export.py` and `./tutorial-dnn-object-detection-live` commands. Otherwise, it can lead to :
-- an error thrown by OpenCV
-- the absence of detection by the ONNX model while the Pytorch model works perfectly using the `python detect.py` command.
+\warning If you train your own model, be sure to use the same image size in the `python train.py`,
+`python export.py` and `./tutorial-dnn-object-detection-live` commands. Otherwise, it can lead to either an error thrown
+by OpenCV or the absence of detection by the ONNX model while the Pytorch model works perfectly using the `python detect.py` command.
 
 \subsubsection dnn_supported_yolov8 Yolo v8
 

doc/tutorial/misc/tutorial-synthetic-blenderproc.dox

@@ -715,16 +715,9 @@ We also download the pretrained yolo model, that we will finetune on our own dat
 (yolov7) ~/yolov7 $ wget https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7-tiny.pt
 ```
 
-**Important note**: while creating the yolov7 virtual environment, you may face the following error:
-```
-requirements to build wheel did not run successfully
-```
-It can be solved by fixing the version of the Python of the virtual environment:
-```
-~/yolov7 $ conda create --name yolov7 pip python=3.10
-~/yolov7 $ conda activate yolov7
-(yolov7) ~/yolov7 $ pip install -r requirements.txt
-```
+\warning While creating the yolov7 virtual environment, you may face the following error:
+"requirements to build wheel did not run successfully". It can be solved by fixing the version of the Python of
+the virtual environment: `conda create --name yolov7 pip python=3.10`
 
 To fine-tune a YoloV7, we should create two new files: the network configuration and the hyperparameters.
 We will reuse the ones provided for the tiny model.