128 lines
No EOL
5.9 KiB
Python
128 lines
No EOL
5.9 KiB
Python
import tkinter as tk
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from tkinter import ttk
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import threading
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import whisper
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import torch
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import gc
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from .keywords_page import KeywordsPage
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class TranscriptionPage(tk.Frame):
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def __init__(self, parent, app_data):
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super().__init__(parent)
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self.app = parent
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self.app_data = app_data
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self.grid_columnconfigure(0, weight=1)
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self.grid_rowconfigure(7, weight=1)
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self.transcription_description = """Wait until your audio input gets processed.
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> You can pass citations to your notes by highlighting piece of text with **text to cite**
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> Press <Control-f> when focused in text-area, to find the next match from the current cursor position
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> Pressing "Extract Keywords" will save the modified transcription"""
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tk.Label(self, text="Transcription", font=self.app_data.heading_font).grid(row=0, column=0, columnspan=2, pady=5, padx=5)
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self.audio_filename_label = tk.Label(self, text="No file", font=self.app_data.mono_font)
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self.audio_filename_label.grid(row=1, column=0, pady=4)
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tk.Label(self, text=self.transcription_description, font=self.app_data.paragraph_font, justify="left").grid(row=3, column=0, columnspan=2, padx=20)
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self.transcription_textarea = tk.Text(self, wrap="word", font=self.app_data.paragraph_font)
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self.transcription_textarea.grid(row=6, column=0, sticky="nsew", pady=6, padx=6)
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# Search box (initially not displayed)
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self.search_box = tk.Entry(self)
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self.search_tooltip = tk.Label(self, text="enter a string and press enter", font=("DejaVu Sans", 10), justify="left")
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self.search_box.bind("<Return>", self.search_text)
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self.transcription_textarea.bind('<Control-a>', select_all)
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self.transcription_textarea.bind('<Control-A>', select_all)
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# Bind Ctrl+F to display the search box
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self.transcription_textarea.bind('<Control-f>', self.display_search_box)
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self.transcription_textarea.bind('<Control-F>', self.display_search_box)
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transcription_scrollbar = tk.Scrollbar(self, command=self.transcription_textarea.yview)
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transcription_scrollbar.grid(row=6, column=1, sticky="ns")
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self.transcription_textarea.config(yscrollcommand=transcription_scrollbar.set)
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tk.Button(self, text="Extract Keywords", command=self.forward_to_keywords_page).grid(row=7, column=0, columnspan=2, pady=5)
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def display_search_box(self, event):
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# Display the search box above the text area
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self.search_box.grid(row=4, column=0, pady=(0, 6), padx=6, sticky="ew")
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self.search_box.focus_set()
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self.search_tooltip.grid(row=5, column=0, sticky="ew")
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def search_text(self, event):
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# Get the search query from the Entry widget
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query = self.search_box.get()
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if not query:
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return
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# Starting position for the search (insert cursor position)
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start_pos = self.transcription_textarea.index(tk.INSERT)
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# Search for the query in the text area
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pos = self.transcription_textarea.search(query, start_pos, tk.END)
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if pos:
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# If found, move cursor to the start of the found text and select the text
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end_pos = f"{pos}+{len(query)}c" # Calculate end position of the selection
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self.transcription_textarea.tag_remove(tk.SEL, "1.0", tk.END)
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self.transcription_textarea.tag_add(tk.SEL, pos, end_pos)
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self.transcription_textarea.mark_set(tk.INSERT, pos)
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self.transcription_textarea.see(pos)
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# Hide the search box after search
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self.search_box.grid_remove()
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self.search_tooltip.grid_remove()
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def insert_into_textarea(self, transcription):
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"""Insert transcription text into the Text widget."""
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def update_text():
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self.transcription_textarea.delete('1.0', tk.END)
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self.transcription_textarea.insert(tk.END, transcription)
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self.transcription_textarea.after(0, update_text)
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def start_transcription_process(self, audio_filepath):
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"""Start transcription threading process."""
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self.audio_filename_label.config(text=f"Filename: {audio_filepath}")
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# Check if the lecture_filename was skipped
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if audio_filepath == "skipped":
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self.insert_into_textarea("")
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return
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else:
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self.insert_into_textarea("Transcribing, please wait...")
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threading.Thread(target=self.create_transcription, args=(audio_filepath,), daemon=True).start()
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gc.collect() # Collect garbage to free up memory (doesn't seem to work)
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return
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def create_transcription(self, audio_filepath):
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"""Transcribe with Whisper."""
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try:
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hw_device = "cuda" if torch.cuda.is_available() else "cpu"
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whisper_model = whisper.load_model("small", device=hw_device)
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device_label = tk.Label(self, text="Loaded Whisper on: " + hw_device, font=self.app_data.mono_font)
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device_label.grid(row=2, column=0, pady=4)
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transcription_text = whisper_model.transcribe(audio_filepath)
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self.insert_into_textarea(transcription_text['text'])
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# Collect garbage to free up memory (doesn't seem to work)
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del whisper_model
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if (hw_device=='cuda'):
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torch.cuda.empty_cache()
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gc.collect()
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except Exception as e:
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print(f"Error during transcription: {e}")
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self.insert_into_textarea("Failed to transcribe audio.")
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def forward_to_keywords_page(self):
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transcribed_text = self.transcription_textarea.get("1.0", tk.END)
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self.app.show_frame(KeywordsPage)
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self.app.frames[KeywordsPage].start_kw_extraction_process(transcribed_text)
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def select_all(event):
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text_widget = event.widget
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text_widget.tag_add(tk.SEL, "1.0", tk.END)
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text_widget.mark_set(tk.INSERT, "1.0")
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text_widget.see(tk.INSERT)
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return 'break' |