DOCS: Fixing formatting in Samples - port to master (#13128)

* DOCS: Fixing formatting in Samples - porting to master

Porting
https://github.com/openvinotoolkit/openvino/pull/13085

Fixing incorrectly numbered lists and indentation of code blocks.

* Update get_started_demos.md

Co-authored-by: Maciej Smyk <maciejx.smyk@intel.com>

samples/python/classification_sample_async/README.md

@@ -69,27 +69,24 @@ To run the sample, you need specify a model and image:
 ### Example
 
 1. Install the `openvino-dev` Python package to use Open Model Zoo Tools:
-
-```
-python -m pip install openvino-dev[caffe,onnx,tensorflow2,pytorch,mxnet]
-```
+   ```
+   python -m pip install openvino-dev[caffe,onnx,tensorflow2,pytorch,mxnet]
+   ```
 
 2. Download a pre-trained model:
-```
-omz_downloader --name alexnet
-```
+   ```
+   omz_downloader --name alexnet
+   ```
 
 3. If a model is not in the IR or ONNX format, it must be converted. You can do this using the model converter:
-
-```
-omz_converter --name alexnet
-```
+   ```
+   omz_converter --name alexnet
+   ```
 
 4. Perform inference of `banana.jpg` and `car.bmp` using the `alexnet` model on a `GPU`, for example:
-
-```
-python classification_sample_async.py -m alexnet.xml -i banana.jpg car.bmp -d GPU
-```
+   ```
+   python classification_sample_async.py -m alexnet.xml -i banana.jpg car.bmp -d GPU
+   ```
 
 ## Sample Output
 

samples/python/hello_classification/README.md

@@ -47,27 +47,24 @@ To run the sample, you need specify a model and image:
 ### Example
 
 1. Install the `openvino-dev` Python package to use Open Model Zoo Tools:
-
-```
-python -m pip install openvino-dev[caffe,onnx,tensorflow2,pytorch,mxnet]
-```
+   ```
+   python -m pip install openvino-dev[caffe,onnx,tensorflow2,pytorch,mxnet]
+   ```
 
 2. Download a pre-trained model:
-```
-omz_downloader --name alexnet
-```
+   ```
+   omz_downloader --name alexnet
+   ```
 
 3. If a model is not in the IR or ONNX format, it must be converted. You can do this using the model converter:
-
-```
-omz_converter --name alexnet
-```
+   ```
+   omz_converter --name alexnet
+   ```
 
 4. Perform inference of `banana.jpg` using the `alexnet` model on a `GPU`, for example:
-
-```
-python hello_classification.py alexnet.xml banana.jpg GPU
-```
+   ```
+   python hello_classification.py alexnet.xml banana.jpg GPU
+   ```
 
 ## Sample Output
 

samples/python/hello_reshape_ssd/README.md

@@ -48,27 +48,24 @@ To run the sample, you need specify a model and image:
 ### Example
 
 1. Install the `openvino-dev` Python package to use Open Model Zoo Tools:
-
-```
-python -m pip install openvino-dev[caffe,onnx,tensorflow2,pytorch,mxnet]
-```
+   ```
+   python -m pip install openvino-dev[caffe,onnx,tensorflow2,pytorch,mxnet]
+   ```
 
 2. Download a pre-trained model:
-```
-omz_downloader --name mobilenet-ssd
-```
+   ```
+   omz_downloader --name mobilenet-ssd
+   ```
 
 3. If a model is not in the IR or ONNX format, it must be converted. You can do this using the model converter:
+   ```
+   omz_converter --name mobilenet-ssd
+   ```
 
-```
-omz_converter --name mobilenet-ssd
-```
-
-4. Perform inference of `banana.jpg` using `mobilenet-ssd` model on a `GPU`, for example:
-
-```
-python hello_reshape_ssd.py mobilenet-ssd.xml banana.jpg GPU
-```
+4. Perform inference of `banana.jpg` using `ssdlite_mobilenet_v2` model on a `GPU`, for example:
+   ```
+   python hello_reshape_ssd.py mobilenet-ssd.xml banana.jpg GPU
+   ```
 
 ## Sample Output