Update README.md

README.md formatting suggestions

README.md

@@ -1,42 +1,71 @@
-## transcribe
-Simple script that uses OpenAI's Whisper to transcribe audio files from your local folders. 
+## Local Transcribe
+
+Local Transcribe uses OpenAI's Whisper to transcribe audio files from your local folders, creating text files on disk. 
+
 ## Note
+
 This implementation and guide is mostly made for researchers not familiar with programming that want a way to transcribe their files locally, without internet connection, usually required within ethical data practices and frameworks. Two examples are shown, a normal workflow with internet connection. And one in which the model is loaded first, via openai-whisper, and then the transcription can be done without being connected to the internet. There is now also a GUI implementation, read below for more information.  
 
-### Instructions 
+### Instructions
+
 #### Requirements
-1. This script was made and tested in an Anaconda environment with python 3.10. I recommend this method if you're not familiar with python.
+
+1. This script was made and tested in an Anaconda environment with Python 3.10. I recommend this method if you're not familiar with Python.
 See [here](https://docs.anaconda.com/anaconda/install/index.html) for instructions. You might need administrator rights. 
+
 2. Whisper requires some additional libraries. The [setup](https://github.com/openai/whisper#setup) page states: "The codebase also depends on a few Python packages, most notably HuggingFace Transformers for their fast tokenizer implementation and ffmpeg-python for reading audio files."
-Users might not need to specifically install Transfomers. However, a conda installation might be needed for ffmepg[^1], which takes care of setting up PATH variables. From the anaconda prompt, type or copy the following:
+Users might not need to specifically install Transfomers. However, a conda installation might be needed for ffmpeg[^1], which takes care of setting up PATH variables. From the anaconda prompt, type or copy the following:
+
 ```
- conda install -c conda-forge ffmpeg-python
- ```
+conda install -c conda-forge ffmpeg-python
+```
+
 3. The main functionality comes from openai-whisper. See their [page](https://github.com/openai/whisper) for details. As of 2023-03-22 you can install via:
+
 ```
 pip install -U openai-whisper
 ```
-4. There is an option to run a batch file, which launches a GUI built on TKinter and TTKthemes. If using these options, make sure they are installed in your python build. You can install them via pip.
+
+4. There is an option to run a batch file, which launches a GUI built on TKinter and TTKthemes. If using these options, make sure they are installed in your Python build. You can install them via pip.
+
 ```
 pip install tk
 ```
+
 and
+
 ```
 pip install ttkthemes 
 ```
+
 #### Using the script
-This is a simple script with no installation. You can either clone the repository with
+
+This is a simple script with no installation. You can download the zip folder and extract it to your preferred working folder.
+
+![](Picture1.png)  
+
+Or by cloning the repository with:
+
 ```
 git clone https://github.com/soderstromkr/transcribe.git
 ```
-and use the example.ipynb template to use the script.
-**OR** download the ```transcribe.py``` file into your work folder. Then you can either import it to another script or notebook for use. I recommend jupyter notebook for new users, see the example below. (Remember to have transcribe.py and example.ipynb in the same working folder). 
-#### Example with jupyter notebook 
-See [example](example.ipynb) for an implementation on jupyter notebook, also added an example for a simple [workaround](example_no_internet.ipynb) to transcribe while offline. 
-#### Using the GUI 
-You can also run the GUI version from your terminal running ```python GUI.py``` or with the batch file called run_Windows.bat (for Windows user, Mac users should read the text file for instructions), just make sure to add your conda path to it. If you want to download a model first, and then go offline for transcription, I recommend running the model with the default sample folder, which will download the model locally. The GUI should look like this:  
+
+
+#### Example with Jupyter Notebook
+
+See [example](example.ipynb) for an implementation on Jupyter Notebook, also added an example for a simple [workaround](example_no_internet.ipynb) to transcribe while offline.
+
+#### Using the GUI
+
+You can also run the GUI version from your terminal running ```python GUI.py``` or with the batch file called run_Windows.bat (for Windows users), just make sure to add your conda path to it. If you want to download a model first, and then go offline for transcription, I recommend running the model with the default sample folder, which will download the model locally. 
+
+The GUI should look like this:
+
 ![python GUI.py](gui_jpeg.jpg?raw=true)
 
+or this, on a Mac, by running `python GUI.py` or `python3 GUI.py`:
+
+![python GUI Mac.py](gui-mac.png)
 
 [^1]: Advanced users can use ```pip install ffmpeg-python``` but be ready to deal with some [PATH issues](https://stackoverflow.com/questions/65836756/python-ffmpeg-wont-accept-path-why), which I encountered in Windows 11.