Update README.md

README.md

@@ -3,7 +3,6 @@
 
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@@ -47,7 +46,7 @@ terms of the license, as specified in the document [`LICENSE`](https://github.co
 (included in this package) 
 
 ## Prerequisites
-All the functions and scripts were tested on Windows and Ubuntu O.S., with these constrains:
+All the functions and scripts were tested on Windows and Ubuntu O.S., with these constraints:
 
 - Python 3.9 
 - PyTorch 1.8.1 or 1.10.0
@@ -86,21 +85,21 @@ python main.py -i example/WV3_example.mat -o ./Output_Example -s WV3 -m Z-PNN --
 
 ## Usage
 
-### Before to start
+### Before start
 To test this algorithm it is needed to create a `.mat` file. It must contain:
 - `I_MS_LR`: Original Multi-Spectral Stack in channel-last configuration (Dimensions: H x W x B);
 - `I_PAN`: Original Panchromatic band, without the third dimension (Dimensions: H x W).
 
 It is possible to convert the GeoTIff images into the required format with the scripts provided in [`tiff_mat_conversion.py`](https://github.com/matciotola/Z-PNN/blob/master/tiff_mat_conversion.py): 
 
 ```
-python tiff_mat_conversion.py -m Tiff2Mat -ms /path/to/ms.tif -pan /path/to/ms.tif  -o path/to/file.mat
+python tiff_mat_conversion.py -m Tiff2Mat -ms /path/to/ms.tif -pan /path/to/pan.tif  -o path/to/file.mat
 ```
 
 Please refer to `--help` for more details. 
 
 ### Testing
-The easiest command to use the algorithm on full resolution data:
+The easiest command to use the algorithm on full-resolution data:
 
 ```
 python main.py -i path/to/file.mat -s sensor_name -m method