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@@ -5,5 +5,5 @@ Unfortunately, I have not found a permament solution for this, not being a Mac u
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1. You can also right-click (or equivalent) on the root folder to open a Terminal within the folder.
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2. Run the following command:
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```
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python main.py
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```
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python app.py
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```
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@@ -8,7 +8,6 @@ Local Transcribe with Whisper is a user-friendly desktop application that allows
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3. Model selection: Now a dropdown option that includes most models for typical use.
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2. New and improved GUI.
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3. Executable: On Windows and don't want to install python? Try the Exe file! See below for instructions (Experimental)
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## Features
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* Select the folder containing the audio or video files you want to transcribe. Tested with m4a video.
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@@ -27,11 +26,6 @@ Or by cloning the repository with:
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```
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git clone https://github.com/soderstromkr/transcribe.git
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```
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### Executable Version **(Experimental. Windows only)**
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The executable version of Local Transcribe with Whisper is a standalone program and should work out of the box. This experimental version is available if you have Windows, and do not have (or don't want to install) python and additional dependencies. However, it requires more disk space (around 1Gb), has no GPU acceleration and has only been lightly tested for bugs, etc. Let me know if you run into any issues!
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1. Download the project folder. As the image above shows.
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2. Find and unzip build.zip (get a coffee or a tea, this might take a while depending on your computer)
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3. Run the executable (app.exe) file.
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### Python Version **(any platform including Mac users)**
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This is recommended if you don't have Windows. Have Windows and use python, or want to use GPU acceleration (Pytorch and Cuda) for faster transcriptions. I would generally recommend this method anyway, but I can understand not everyone wants to go through the installation process for Python, Anaconda and the other required packages.
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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.
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@@ -45,9 +39,9 @@ conda install -c conda-forge ffmpeg-python
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```
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pip install -U openai-whisper
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```
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4. To run the app built on TKinter and TTKthemes. If using these options, make sure they are installed in your Python build. You can install them via pip.
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4. To run the app built on TKinter and TTKthemes. If using these options, make sure they are installed in your Python build. You can install them and colorama via pip.
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```
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pip install tkinter
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pip install colorama
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```
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and
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```
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@@ -55,7 +49,7 @@ pip install customtkinter
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```
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5. Run the app:
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1. For **Windows**: In the same folder as the *app.py* file, run the app from terminal by running ```python app.py``` or with the batch file called run_Windows.bat (for Windows users), which assumes you have conda installed and in the base environment (This is for simplicity, but users are usually adviced to create an environment, see [here](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#creating-an-environment-with-commands) for more info) just make sure you have the correct environment (right click on the file and press edit to make any changes). 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.
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2. For **Mac**: Haven't figured out a better way to do this, see [the instructions here](Mac_instructions.txt)
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2. For **Mac**: Haven't figured out a better way to do this, see [the instructions here](Mac_instructions.md)
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## Usage
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1. When launched, the app will also open a terminal that shows some additional information.
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2. Select the folder containing the audio or video files you want to transcribe by clicking the "Browse" button next to the "Folder" label. This will open a file dialog where you can navigate to the desired folder. Remember, you won't be choosing individual files but whole folders!
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@@ -5,9 +5,10 @@ from tkinter import messagebox
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from src._LocalTranscribe import transcribe, get_path
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import customtkinter
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import threading
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from colorama import Back, Fore
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from colorama import Back
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import colorama
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colorama.init(autoreset=True)
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import os
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@@ -72,7 +73,8 @@ class App:
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# Helper functions
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# Browsing
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def browse(self):
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folder_path = filedialog.askdirectory()
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initial_dir = os.getcwd()
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folder_path = filedialog.askdirectory(initialdir=initial_dir)
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self.path_entry.delete(0, tk.END)
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self.path_entry.insert(0, folder_path)
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# Start transcription
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@@ -92,22 +94,15 @@ class App:
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self.progress_bar.start()
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# Setting path and files
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glob_file = get_path(path)
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info_path = 'I will transcribe all eligible audio/video files in the path: {}\n\nContinue?'.format(path)
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answer = messagebox.askyesno("Confirmation", info_path)
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if not answer:
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self.progress_bar.stop()
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self.progress_bar.pack_forget()
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self.transcribe_button.configure(state=tk.NORMAL)
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return
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messagebox.showinfo("Message", "Starting transcription!")
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# Start transcription
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error_language = 'https://github.com/openai/whisper#available-models-and-languages'
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try:
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output_text = transcribe(path, glob_file, model, language, verbose)
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except UnboundLocalError:
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messagebox.showinfo("Files not found error!", 'Nothing found, choose another folder.')
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pass
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except ValueError:
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messagebox.showinfo("Language error!", 'See {} for supported languages'.format(error_language))
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messagebox.showinfo("Invalid language name, you might have to clear the default text to continue!")
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# Hide progress bar
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self.progress_bar.stop()
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self.progress_bar.pack_forget()
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@@ -1,3 +0,0 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:b361c4993eceb2006f225ffdd2f7b63265586e3dded351972dfcd5e5d75559c7
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size 249467977
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