Check-out: checkout 2023-10-09

README.md

@@ -22,7 +22,7 @@ sudo apt install ffmpeg
 
 To generate transcripts create a new job with your specifications (see jobs section below).
 <br/>
-If you need to download the transcriber model set your huggingface token:
+If you need to download the transcriber model set your huggingface token (initially running or using new language):
 
 On Linux/Mac:
 
@@ -36,6 +36,8 @@ On Windows (Command prompt):
 set HF_TOKEN="your-token-here"
 ```
 
+If the token is not set you will be asked for it when running the software
+
 Then run the following command to generate your transcript:
 
 ```bash
@@ -50,17 +52,14 @@ Jobs specify tasks for transcript creation. A job contains the following informa
 
 - `name`: string: The name of the job
 - `source`: List[string]: The sources of the videos (paths, YouTube links, TibAV links)
-- `modelpath`: Optional[string]: The path to the model if already saved locally (will be downloaded temporarily if not)
+- `modelpath`: Optional[string]: The path to the model if a specific model should be used.
 - `language`: Optional[string]: The language of the video (If not specified employs auto-detection)
 
 ## to-do
 
 - seperate data production form code
-- remember to accept the conditions on diarization if you use huggingface
+- remember to accept the conditions on models if you use huggingface
 - do a config json
-- do option to have models already stored and point to them (is this necessary? > if you do not want to interact with
-  huggingface yes)
-    - also for single language models
 - check warnings
 - downloader for tib-av
 - more optional setting
@@ -71,19 +70,20 @@ Jobs specify tasks for transcript creation. A job contains the following informa
 ```
 project_root/
 ├── src/
+│   ├── init.py # init so the main can load all necessary classes
 │   ├── file_manager.py   # Contains FileManager class
 │   ├── transcriber.py    # Contains Transcriber class
 │   ├── transcript_generator.py    # Contains TranscriptGenerator class
 │   ├── data_handling.py  # Contains download_audio and convert_to_wav methods
-│   └── main.py    # Main script that runs the process
 ├── tests/    
 │   ├── test_file_manager.py
 │   ├── test_transcriber.py
 │   └── test_transcript_generator.py
 ├── data/
-│   ├── audio/   # downloaded mp4 and output wav files
-│   ├── models/   # models used for transcripts (are ignored by git and not necessarily)
-│   └── transcripts/  # JSON and text transcript files
+│   ├── results/   # results of the transcripts (downloaded video files, audio, JSON and text transcript files)
+│   ├── jobs/   # place to store jobs to run
+│   └── logs/  # logs of previous jobs
+├── main.py # Initial entry point for the project
 └── README.md
 ```
 
@@ -96,5 +96,4 @@ project_root/
 
 - **tests/**: This directory contains all your test scripts corresponding to your source files.
 
-- **data/**: This directory contains all the data needed for your code. For simplicity, I categorize the files into
-  separate directories for audio, model and transcript files.
+- **data/**: This directory contains all the data needed for your code as well as the results.