Djalim Simaila
03a41b6996
- Introduce `app.py` as the main application file to handle shitpost scanning. - Create `config.py` for configuration settings including scan paths and file types. - Implement database models in `Models.py` for shitposts, songs, speech outputs, and tags. - Add database creation logic in `db.py`. - Develop various scanners (`OcrScanner.py`, `SongScanner.py`, `SpeechScanner.py`, `TagScanner.py`) for extracting information from shitposts. - Implement utility functions in `dateExtractor.py` and `shitpostFactory.py` for handling file metadata and creating shitpost objects. - Include a `pyproject.toml` for project dependencies and configuration.
52 lines
1.9 KiB
Python
52 lines
1.9 KiB
Python
import tempfile
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from time import time
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from config import VIDEO_FILETYPES
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from db.Models import Shitpost, SpeechOutput
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from faster_whisper import WhisperModel
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import threading
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import subprocess
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import json
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def extractSpeech(shitpost: Shitpost,lock:threading.Lock):
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t1 = time()
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print(f"\tstarting to extract speech for {shitpost.hash[:4]} aka {shitpost.path}")
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if shitpost.speech_output is None and shitpost.file_type not in VIDEO_FILETYPES:
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#whisper(shitpost)
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fastWhisper(shitpost, lock)
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print(f"\tspeech extracted for {shitpost.hash[:4]} in :{time()-t1} ")
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def whisper(shitpost: Shitpost):
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filename = shitpost.path.split("/")[-1]
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filename = filename.split(".")[0]
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with tempfile.TemporaryDirectory() as tmpdir:
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cmd = f"whisper --verbose False -f json -o {tmpdir} \"{shitpost.path}\""
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subprocess.run(cmd, shell=True)
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with open(f"{tmpdir}/{filename}.json", "r") as file:
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data = json.load(file)
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print("extracted speech :", data["text"] )
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shitpost.speech_output = SpeechOutput(
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text=json.dumps(data),
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)
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def fastWhisper(shitpost: Shitpost,lock:threading.Lock):
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dico = {}
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filename = shitpost.path.split("/")[-1]
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filename = filename.split(".")[0]
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with tempfile.TemporaryDirectory() as tmpdir:
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model = WhisperModel("turbo", device="cpu", compute_type="int8")
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segments, info = model.transcribe(shitpost.path,beam_size=5,language_detection_segments=2)
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#print("Detected language '%s' with probability %f" % (info.language, info.language_probability))
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for segment in segments:
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#print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
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dico[round(segment.start,2)] = segment.text
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with lock:
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shitpost.speech_output = SpeechOutput(
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text=json.dumps(dico),
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)
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