diff --git a/.github/workflows/ci-cd.yaml b/.github/workflows/ci-cd.yaml new file mode 100644 index 0000000..591ea9d --- /dev/null +++ b/.github/workflows/ci-cd.yaml @@ -0,0 +1,33 @@ +# Copyright Jiaqi Liu +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +--- +name: CI/CD + +on: + pull_request: + push: + branches: [master] + +jobs: + sync-to-huggingface-space: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v3 + with: + fetch-depth: 0 + lfs: true + - name: Push to hub + run: git push https://QubitPi:$HF_TOKEN@huggingface.co/spaces/QubitPi/tiger master:main -f + env: + HF_TOKEN: ${{ secrets.HF_TOKEN }} diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..d868f45 --- /dev/null +++ b/.gitignore @@ -0,0 +1,4 @@ +.venv +.idea/ +.DS_Store +__pycache__ diff --git a/.streamlit/config.toml b/.streamlit/config.toml new file mode 100644 index 0000000..e7a38ea --- /dev/null +++ b/.streamlit/config.toml @@ -0,0 +1,8 @@ +[theme] +primaryColor="#F63366" +backgroundColor="#FFFFFF" +secondaryBackgroundColor="#F0F2F6" +textColor="#262730" +font="sans serif" +[server] +maxUploadSize=1028 diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..7d7429c --- /dev/null +++ b/LICENSE @@ -0,0 +1,201 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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Tiger generates transcriptions using the +[OpenAI Whisper](https://openai.com/blog/whisper) model. + +The app is available on [Hugging Face space][Project Tiger on Hugging Face]. Please have a try. + +How Project Tiger Started +------------------------- + +I don't believe NLP is inherently AI. [Project Tiger](), however, enlightened me on what way should AI makes NLP more +powerful for people. + +Paraphrasing movie lines has been my favorite approach to learn a foreign language. This was why I was able to speak +close-native English in early days. I used this same tactic for German today as well. + +One morning I was studying German with the famous German WW2 movie +[_Generation War_](https://youtu.be/TmyGPX23px4?si=wk3V62vLUe9zFzfo). Managing to find its subtitles[^1][^2][^3] were +easy for me. A problem, however, soon arose as I proceeded with them: _the subtitles had errors - missing couple of +phrases every few other lines_. This was a big NO for language learners like me. In old days 10 years ago, I would've +reached a dead end... + +[^1]: https://www.opensubtitles.org/en/subtitles/6243166/generation-war-eine-andere-zeit-de +[^2]: https://www.opensubtitles.org/en/subtitles/6243167/generation-war-ein-anderer-krieg-de +[^3]: https://www.opensubtitles.org/en/subtitles/6243168/generation-war-ein-anderes-land-de + +Almost immediately, however, I had this idea of having AI figure out those missing words for me; so tried +[OpenAI's Whisper](https://huggingface.co/spaces/openai/whisper) which, quite surprisingly, yield 100% accurate results. +That was the first occasion where AI produced significant solid values for me as a language learner. + +Feeling so excited, I decided to industrialize this process and hereby present it as +[Project Tiger on Hugging Face], an __AI movie transcription service that targets specifically for language learners__ + +> [!NOTE] +> +> On name "__Tiger__" +> +> The project name _tiger_ was taken from the _German heavy tank of World War II - +> [Tiger I](https://en.wikipedia.org/wiki/Tiger_I)_. +> +> I chose this name because the project idea was spawned from the study of German language. More importantly, _Tiger I_ +> has been widely recognized as a revolutionary tank being a crown jewels in the history of warfare technology: +> +> > _"It is tempting to view the appearance of the Tiger tank as revolutionary, ... the end result was a machine that +> > represented a quantum leap forward in tank design and changed everything - forever"_[^4] +> +> As _Tiger_ had steered the direction of next-generation heavy tank, this project has also revolutionized my view +> toward AI subconsciously and serves as an empirical guide on how I should make NLP more powerful for people with AI. + +[^4]: _[Tiger tank : Panzerkampfwagen VI Tiger I Ausf. E (SdKfz 181): owner's workshop manual](https://a.co/d/28OzPsK)_, The Tank Museum, 2011. p.13 + +[Apache License Badge]: https://img.shields.io/badge/Apache%202.0-F25910.svg?style=for-the-badge&logo=Apache&logoColor=white +[Apache License, Version 2.0]: https://www.apache.org/licenses/LICENSE-2.0 + +[Hugging Face space badge]: https://img.shields.io/badge/Hugging%20Face%20Space-tiger-FFD21E?style=for-the-badge&logo=huggingface&logoColor=white +[Hugging Face space URL]: https://huggingface.co/spaces/QubitPi/tiger + +[Hugging Face sync status badge]: https://img.shields.io/github/actions/workflow/status/QubitPi/tiger/ci-cd.yaml?branch=master&style=for-the-badge&logo=github&logoColor=white&label=Hugging%20Face%20Sync%20Up +[Hugging Face sync status URL]: https://github.com/QubitPi/tiger/actions/workflows/ci-cd.yaml + +[Project Tiger on Hugging Face]: https://huggingface.co/spaces/QubitPi/tiger \ No newline at end of file diff --git a/app.py b/app.py new file mode 100644 index 0000000..332aadc --- /dev/null +++ b/app.py @@ -0,0 +1,236 @@ +import whisper +import streamlit as st +from streamlit_lottie import st_lottie +from utils import write_vtt, write_srt +import ffmpeg +import requests +from typing import Iterator +from io import StringIO +import numpy as np +import pathlib +import os + +st.set_page_config(page_title="Auto Subtitled Video Generator", page_icon=":movie_camera:", layout="wide") + + +# Define a function that we can use to load lottie files from a link. +def load_lottieurl(url: str): + r = requests.get(url) + if r.status_code != 200: + return None + return r.json() + + +APP_DIR = pathlib.Path(__file__).parent.absolute() + +LOCAL_DIR = APP_DIR / "local" +LOCAL_DIR.mkdir(exist_ok=True) +save_dir = LOCAL_DIR / "output" +save_dir.mkdir(exist_ok=True) + +loaded_model = whisper.load_model("base") +current_size = "None" + +col1, col2 = st.columns([1, 3]) +with col1: + lottie = load_lottieurl("https://assets1.lottiefiles.com/packages/lf20_HjK9Ol.json") + st_lottie(lottie) + +with col2: + st.write(""" + ## Auto Subtitled Video Generator + ##### Upload a video file and get a video with subtitles. + ###### ➠ If you want to transcribe the video in its original language, select the task as "Transcribe" + ###### ➠ If you want to translate the subtitles to English, select the task as "Translate" + ###### I recommend starting with the base model and then experimenting with the larger models, the small and medium models often work well. """) + + +def change_model(current_size, size): + if current_size != size: + loaded_model = whisper.load_model(size) + return loaded_model + else: + raise Exception("Model size is the same as the current size.") + + +def inferecence(_loaded_model, uploaded_file, task): + with open(f"{save_dir}/input.mp4", "wb") as f: + f.write(uploaded_file.read()) + audio = ffmpeg.input(f"{save_dir}/input.mp4") + audio = ffmpeg.output(audio, f"{save_dir}/output.wav", acodec="pcm_s16le", ac=1, ar="16k") + ffmpeg.run(audio, overwrite_output=True) + if task == "Transcribe": + options = dict(task="transcribe", best_of=5) + results = _loaded_model.transcribe(f"{save_dir}/output.wav", **options) + vtt = getSubs(results["segments"], "vtt", 80) + srt = getSubs(results["segments"], "srt", 80) + lang = results["language"] + return results["text"], vtt, srt, lang + elif task == "Translate": + options = dict(task="translate", best_of=5) + results = _loaded_model.transcribe(f"{save_dir}/output.wav", **options) + vtt = getSubs(results["segments"], "vtt", 80) + srt = getSubs(results["segments"], "srt", 80) + lang = results["language"] + return results["text"], vtt, srt, lang + else: + raise ValueError("Task not supported") + + +def getSubs(segments: Iterator[dict], format: str, maxLineWidth: int) -> str: + segmentStream = StringIO() + + if format == 'vtt': + write_vtt(segments, file=segmentStream, maxLineWidth=maxLineWidth) + elif format == 'srt': + write_srt(segments, file=segmentStream, maxLineWidth=maxLineWidth) + else: + raise Exception("Unknown format " + format) + + segmentStream.seek(0) + return segmentStream.read() + + +def generate_subtitled_video(video, audio, transcript): + video_file = ffmpeg.input(video) + audio_file = ffmpeg.input(audio) + ffmpeg.concat(video_file.filter("subtitles", transcript), audio_file, v=1, a=1).output("final.mp4").run(quiet=True, + overwrite_output=True) + video_with_subs = open("final.mp4", "rb") + return video_with_subs + + +def main(): + size = st.selectbox( + "Select Model Size (The larger the model, the more accurate the transcription will be, but it will take longer)", + ["tiny", "base", "small", "medium", "large"], index=1) + loaded_model = change_model(current_size, size) + st.write(f"Model is {'multilingual' if loaded_model.is_multilingual else 'English-only'} " + f"and has {sum(np.prod(p.shape) for p in loaded_model.parameters()):,} parameters.") + input_file = st.file_uploader("File", type=["mp4", "avi", "mov", "mkv"]) + # get the name of the input_file + if input_file is not None: + filename = input_file.name[:-4] + else: + filename = None + task = st.selectbox("Select Task", ["Transcribe", "Translate"], index=0) + if task == "Transcribe": + if st.button("Transcribe"): + results = inferecence(loaded_model, input_file, task) + col3, col4 = st.columns(2) + col5, col6, col7, col8 = st.columns(4) + col9, col10 = st.columns(2) + with col3: + st.video(input_file) + + with open("transcript.txt", "w+", encoding='utf8') as f: + f.writelines(results[0]) + f.close() + with open(os.path.join(os.getcwd(), "transcript.txt"), "rb") as f: + datatxt = f.read() + + with open("transcript.vtt", "w+", encoding='utf8') as f: + f.writelines(results[1]) + f.close() + with open(os.path.join(os.getcwd(), "transcript.vtt"), "rb") as f: + datavtt = f.read() + + with open("transcript.srt", "w+", encoding='utf8') as f: + f.writelines(results[2]) + f.close() + with open(os.path.join(os.getcwd(), "transcript.srt"), "rb") as f: + datasrt = f.read() + + with col5: + st.download_button(label="Download Transcript (.txt)", + data=datatxt, + file_name="transcript.txt") + with col6: + st.download_button(label="Download Transcript (.vtt)", + data=datavtt, + file_name="transcript.vtt") + with col7: + st.download_button(label="Download Transcript (.srt)", + data=datasrt, + file_name="transcript.srt") + with col9: + st.success( + "You can download the transcript in .srt format, edit it (if you need to) and upload it to YouTube to create subtitles for your video.") + with col10: + st.info( + "Streamlit refreshes after the download button is clicked. The data is cached so you can download the transcript again without having to transcribe the video again.") + + with col4: + with st.spinner("Generating Subtitled Video"): + video_with_subs = generate_subtitled_video(f"{save_dir}/input.mp4", f"{save_dir}/output.wav", + "transcript.srt") + st.video(video_with_subs) + st.snow() + with col8: + st.download_button(label="Download Video with Subtitles", + data=video_with_subs, + file_name=f"{filename}_with_subs.mp4") + elif task == "Translate": + if st.button("Translate to English"): + results = inferecence(loaded_model, input_file, task) + col3, col4 = st.columns(2) + col5, col6, col7, col8 = st.columns(4) + col9, col10 = st.columns(2) + with col3: + st.video(input_file) + + with open("transcript.txt", "w+", encoding='utf8') as f: + f.writelines(results[0]) + f.close() + with open(os.path.join(os.getcwd(), "transcript.txt"), "rb") as f: + datatxt = f.read() + + with open("transcript.vtt", "w+", encoding='utf8') as f: + f.writelines(results[1]) + f.close() + with open(os.path.join(os.getcwd(), "transcript.vtt"), "rb") as f: + datavtt = f.read() + + with open("transcript.srt", "w+", encoding='utf8') as f: + f.writelines(results[2]) + f.close() + with open(os.path.join(os.getcwd(), "transcript.srt"), "rb") as f: + datasrt = f.read() + + with col5: + st.download_button(label="Download Transcript (.txt)", + data=datatxt, + file_name="transcript.txt") + with col6: + st.download_button(label="Download Transcript (.vtt)", + data=datavtt, + file_name="transcript.vtt") + with col7: + st.download_button(label="Download Transcript (.srt)", + data=datasrt, + file_name="transcript.srt") + with col9: + st.success( + "You can download the transcript in .srt format, edit it (if you need to) and upload it to YouTube to create subtitles for your video.") + with col10: + st.info( + "Streamlit refreshes after the download button is clicked. The data is cached so you can download the transcript again without having to transcribe the video again.") + + with col4: + with st.spinner("Generating Subtitled Video"): + video_with_subs = generate_subtitled_video(f"{save_dir}/input.mp4", f"{save_dir}/output.wav", + "transcript.srt") + st.video(video_with_subs) + st.snow() + with col8: + st.download_button(label="Download Video with Subtitles ", + data=video_with_subs, + file_name=f"{filename}_with_subs.mp4") + else: + st.error("Please select a task.") + + +if __name__ == "__main__": + main() + st.markdown( + "###### Made with :heart: by [@QubitPi](https://github.com/QubitPi) [![this is an image link](https://i.imgur.com/thJhzOO.png)](https://buymeacoffee.com/qubitpi)") diff --git a/languages.py b/languages.py new file mode 100644 index 0000000..0551511 --- /dev/null +++ b/languages.py @@ -0,0 +1,101 @@ +LANGUAGES = { + "en": "eng", + "zh": "zho", + "de": "deu", + "es": "spa", + "ru": "rus", + "ko": "kor", + "fr": "fra", + "ja": "jpn", + "pt": "por", + "tr": "tur", + "pl": "pol", + "ca": "cat", + "nl": "nld", + "ar": "ara", + "sv": "swe", + "it": "ita", + "id": "ind", + "hi": "hin", + "fi": "fin", + "vi": "vie", + "iw": "heb", + "uk": "ukr", + "el": "ell", + "ms": "msa", + "cs": "ces", + "ro": "ron", + "da": "dan", + "hu": "hun", + "ta": "tam", + "no": "nor", + "th": "tha", + "ur": "urd", + "hr": "hrv", + "bg": "bul", + "lt": "lit", + "la": "lat", + "mi": "mri", + "ml": "mal", + "cy": "cym", + "sk": "slk", + "te": "tel", + "fa": "fas", + "lv": "lav", + "bn": "ben", + "sr": "srp", + "az": "aze", + "sl": "slv", + "kn": "kan", + "et": "est", + "mk": "mkd", + "br": "bre", + "eu": "eus", + "is": "isl", + "hy": "hye", + "ne": "nep", + "mn": "mon", + "bs": "bos", + "kk": "kaz", + "sq": "sqi", + "sw": "swa", + "gl": "glg", + "mr": "mar", + "pa": "pan", + "si": "sin", + "km": "khm", + "sn": "sna", + "yo": "yor", + "so": "som", + "af": "afr", + "oc": "oci", + "ka": "kat", + "be": "bel", + "tg": "tgk", + "sd": "snd", + "gu": "guj", + "am": "amh", + "yi": "yid", + "lo": "lao", + "uz": "uzb", + "fo": "fao", + "ht": "hat", + "ps": "pus", + "tk": "tuk", + "nn": "nno", + "mt": "mlt", + "sa": "san", + "lb": "ltz", + "my": "mya", + "bo": "bod", + "tl": "tgl", + "mg": "mlg", + "as": "asm", + "tt": "tat", + "haw": "haw", + "ln": "lin", + "ha": "hau", + "ba": "bak", + "jw": "jav", + "su": "sun", +} \ No newline at end of file diff --git a/packages.txt b/packages.txt new file mode 100644 index 0000000..20645e6 --- /dev/null +++ b/packages.txt @@ -0,0 +1 @@ +ffmpeg diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..9590324 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,10 @@ +ffmpeg +ffmpeg_python +numpy +pytubefix +requests +streamlit +streamlit_lottie +torch +transformers +openai-whisper \ No newline at end of file diff --git a/utils.py b/utils.py new file mode 100644 index 0000000..ae54176 --- /dev/null +++ b/utils.py @@ -0,0 +1,96 @@ +import textwrap +import zlib +from typing import Iterator, TextIO + + +def exact_div(x, y): + assert x % y == 0 + return x // y + + +def str2bool(string): + str2val = {"True": True, "False": False} + if string in str2val: + return str2val[string] + else: + raise ValueError(f"Expected one of {set(str2val.keys())}, got {string}") + + +def optional_int(string): + return None if string == "None" else int(string) + + +def optional_float(string): + return None if string == "None" else float(string) + + +def compression_ratio(text) -> float: + return len(text) / len(zlib.compress(text.encode("utf-8"))) + + +def format_timestamp(seconds: float, always_include_hours: bool = False, fractionalSeperator: str = '.'): + assert seconds >= 0, "non-negative timestamp expected" + milliseconds = round(seconds * 1000.0) + + hours = milliseconds // 3_600_000 + milliseconds -= hours * 3_600_000 + + minutes = milliseconds // 60_000 + milliseconds -= minutes * 60_000 + + seconds = milliseconds // 1_000 + milliseconds -= seconds * 1_000 + + hours_marker = f"{hours:02d}:" if always_include_hours or hours > 0 else "" + return f"{hours_marker}{minutes:02d}:{seconds:02d}{fractionalSeperator}{milliseconds:03d}" + + +def write_txt(transcript: Iterator[dict], file: TextIO): + for segment in transcript: + print(segment['text'].strip(), file=file, flush=True) + + +def write_vtt(transcript: Iterator[dict], file: TextIO, maxLineWidth=None): + print("WEBVTT\n", file=file) + for segment in transcript: + text = processText(segment['text'], maxLineWidth).replace('-->', '->') + + print( + f"{format_timestamp(segment['start'])} --> {format_timestamp(segment['end'])}\n" + f"{text}\n", + file=file, + flush=True, + ) + + +def write_srt(transcript: Iterator[dict], file: TextIO, maxLineWidth=None): + """ + Write a transcript to a file in SRT format. + Example usage: + from pathlib import Path + from whisper.utils import write_srt + result = transcribe(model, audio_path, temperature=temperature, **args) + # save SRT + audio_basename = Path(audio_path).stem + with open(Path(output_dir) / (audio_basename + ".srt"), "w", encoding="utf-8") as srt: + write_srt(result["segments"], file=srt) + """ + for i, segment in enumerate(transcript, start=1): + text = processText(segment['text'].strip(), maxLineWidth).replace('-->', '->') + + # write srt lines + print( + f"{i}\n" + f"{format_timestamp(segment['start'], always_include_hours=True, fractionalSeperator=',')} --> " + f"{format_timestamp(segment['end'], always_include_hours=True, fractionalSeperator=',')}\n" + f"{text}\n", + file=file, + flush=True, + ) + +def processText(text: str, maxLineWidth=None): + if (maxLineWidth is None or maxLineWidth < 0): + return text + + lines = textwrap.wrap(text, width=maxLineWidth, tabsize=4) + return '\n'.join(lines)