intiial commit

.gitignore

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+/*.mp4
+/*.srt
+/*.zip
+.idea

app.py

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+import gradio as gr
+import pathlib
+import subprocess
+import math
+from pydub import AudioSegment
+import openai
+import re
+import MeCab
+import deepl
+import os
+import zipfile
+
+def split_japanese_line(line, max_length):
+    """Split a Japanese line into multiple lines using MeCab for morphological analysis."""
+    if len(line) < max_length:
+        return line
+
+    max_line = 2
+    line = re.sub(r'[、。]', '', line)
+
+    m = MeCab.Tagger()
+    nodes = m.parse(line).split("\n")
+
+    words = [node.split("\t")[0] for node in nodes if node and not node.startswith("EOS")]
+    word_features = [re.split('[\t,]', node)[4] if len(re.split('[\t,]', node)) > 3 else None for node in nodes if
+                     node and not node.startswith("EOS")]
+
+    lines = []
+    current_line = ""
+
+    idx = 0
+    allowed_features = ["助詞-格助詞", "助詞-副助詞", "助詞-終助詞", "助詞-係助詞", "補助記号-句点"]
+    whitelisted_words = ["という", "っていう", "になって", "みたいな", "として", "に対して", "とする", "というか", "ていう", "になって", "について", "にかけて", "とか", "とかで", "にも", "には", "について",
+               "がある", "があって", "でも", "では", "のような", "のように", "のいる", "のある", "がします", "がする"]
+
+    while idx < len(words):
+        word = words[idx]
+        # If adding the next word exceeds the max_length or if the word is a particle, break the line
+        if idx + 1 < len(words) and any(
+                whitelisted_word == word + words[idx + 1] for whitelisted_word in whitelisted_words):
+            current_line += word + words[idx + 1]
+            idx += 2  # Increment to skip next word
+            if len(word_features) > idx:
+                if word_features[idx] not in allowed_features:
+                    lines.append(current_line)
+                    current_line = ""
+        elif len(word_features) > idx:
+            if word_features[idx - 1] in allowed_features and word_features[idx] not in allowed_features:
+                lines.append(current_line)
+                current_line = ""
+            current_line += word
+            idx += 1
+        else:
+            current_line += word
+            idx += 1
+
+
+    # Append the last line if it exists
+    if current_line:
+        lines.append(current_line)
+
+    # Merge lines to ensure each line is less than or equal to max_length
+    merged_lines = []
+    temp_line = ''
+    for line in lines:
+        if len(temp_line) <= max_length / 2:
+            temp_line += line
+        elif len(temp_line + line) <= max_length:
+            temp_line += line
+        elif len(merged_lines) >= max_line - 1:
+            temp_line += line
+        else:
+            if temp_line == '':
+                merged_lines.append(line)
+            else:
+                merged_lines.append(temp_line)
+                temp_line = line
+    if temp_line:
+        merged_lines.append(temp_line)
+
+    return "\n".join(merged_lines)
+
+
+def split_japanese_srt_text(srt_content, max_length):
+    """Split the lines of the srt content for Japanese text."""
+    srt_lines = srt_content.split("\n")
+    modified_lines = []
+
+    for line in srt_lines:
+        # Check if the line looks like a subtitle text (not an index or a timestamp)
+        if re.match(r"^[0-9]{1,2}:[0-9]{2}:[0-9]{2},[0-9]{3} --> [0-9]{1,2}:[0-9]{2}:[0-9]{2},[0-9]{3}$", line):
+            modified_lines.append(line)
+        elif line.isdigit():
+            modified_lines.append(line)
+        elif line == "":
+            modified_lines.append(line)
+        else:
+            # Split the Japanese subtitle text line
+            modified_lines.extend(split_japanese_line(line, max_length).split("\n"))
+
+    return "\n".join(modified_lines)
+
+def format_transcription_for_japanese(file_path, max_length):
+    with open(file_path, "r", encoding="utf-8") as file:
+        srt_content = file.read()
+    modified_japanese_srt_content = split_japanese_srt_text(srt_content, max_length)
+    with open("formatted_transcription.srt", "w", encoding="utf-8") as file:
+        file.write(modified_japanese_srt_content)
+
+def mp4ToSrt(api_key, sampletext_path):
+    openai.api_key = api_key  # Set the API key
+
+    # Read the provided text file and replace actual newline characters with "\n" string
+    with open(sampletext_path, "r", encoding="utf-8") as file:
+        content = file.read()
+
+    # Replace newline characters with "\n" string
+    modified_content = content.replace('\n', '\\n')
+
+    with open(str('converted.mp4'), "rb") as f:
+        response = openai.Audio.transcribe(
+            "whisper-1",
+            f,
+            temperature=0,
+            language="ja",
+            prompt=modified_content,
+            response_format="srt")
+    transcription = response
+
+    with open("transcription.srt", "wt", encoding="utf-8") as f:
+        f.writelines([transcription])
+
+def compress_mp4(path):
+    original_file = pathlib.Path(path)
+    audio_file = pathlib.Path("./audio").with_suffix(original_file.suffix)
+
+    # If the audio file already exists, delete it
+    if audio_file.exists():
+        audio_file.unlink()
+
+    subprocess.run(["ffmpeg", "-i", str(original_file)
+                       , "-codec:a", "copy", "-vn", str(audio_file)])
+
+    TARGET_FILE_SIZE = 25000000
+
+    print(f"{audio_file.stat().st_size=}")
+
+    if audio_file.stat().st_size > TARGET_FILE_SIZE:
+        print("This file needs to be converted.")
+
+    audio_segment = AudioSegment.from_file(str(audio_file))
+
+    audio_length_sec = len(audio_segment) / 1000
+
+    target_kbps = int(math.floor(TARGET_FILE_SIZE * 8 / audio_length_sec / 1000 * 0.95))
+
+    if target_kbps < 8:
+        assert f"{target_kbps=} is not supported."
+
+    converted_file = pathlib.Path("./converted").with_suffix(".mp4")
+
+    # If the converted file already exists, delete it
+    if converted_file.exists():
+        converted_file.unlink()
+
+    subprocess.run(["ffmpeg", "-i", str(audio_file)
+                       , "-codec:a", "aac", "-ar", "16000", "-ac", "1", "-b:a", f"{target_kbps}k"
+                       , str(converted_file)])
+
+    print(f"{converted_file.stat().st_size=}")
+
+def videoToSrt(video_obj, sampletext_obj, max_length, api_key):
+   compress_mp4(video_obj.name)
+   mp4ToSrt(api_key, sampletext_obj.name)
+   format_transcription_for_japanese("transcription.srt", max_length)
+   with open("formatted_transcription.srt", "r", encoding="utf-8") as file:
+       content = file.read()
+       return content
+
+def translateSrt(text, languages, api_key):
+    translator = deepl.Translator(api_key)
+
+    # 出力ファイルを保存するための一時ディレクトリを作成
+    if not os.path.exists('translated_srt_files'):
+        os.makedirs('translated_srt_files')
+
+    # 各言語での翻訳をループ処理
+    for lang in languages:
+        result = translator.translate_text(text, target_lang=lang, split_sentences=0).text
+        with open(f'translated_srt_files/{lang}.srt', 'w') as f:
+            f.write(result)
+
+    # srtファイルをまとめたzipを作成
+    zip_filename = "translated_srt_files.zip"
+    with zipfile.ZipFile(zip_filename, 'w') as zipf:
+        for root, _, files in os.walk('translated_srt_files'):
+            for file in files:
+                zipf.write(os.path.join(root, file))
+
+    return zip_filename  # zipファイルのパスを返す
+
+
+with gr.Blocks() as app:
+    with gr.Tab("音声ファイルからsrt生成"):
+        with gr.Row():
+            text_input = [
+                gr.File(file_types=[".mp4"], label="動画ファイル（mp4）"),  # File input for the video
+                gr.File(file_types=[".txt"], label="書き出したい文章の例"),  # File input for the text file
+                gr.Number(20, label="1行あたりの最大文字数"),
+                gr.Textbox(placeholder="openAI API key", type="password", label="openAI API keyを入力してください")
+            ]
+        text_output = gr.Textbox(label="SRTの出力結果", max_lines=30)
+        text_button = gr.Button("SRTに変換")
+    with gr.Tab("srt自動翻訳"):
+        with gr.Row():
+            translate_input = [
+                gr.Textbox(placeholder="srt本文", label="srt本文を貼り付けてください", max_lines=10),
+                gr.Dropdown(["EN-US", "ZH"], multiselect=True, label="翻訳したい言語を選択"),
+                gr.Textbox(placeholder="DeepL API key", type="password", label="DeepL API keyを入力してください")
+            ]
+        translate_output = gr.File(label="翻訳結果")
+        translate_button = gr.Button("SRTを翻訳")
+
+
+    text_button.click(videoToSrt, inputs=text_input, outputs=text_output)
+    translate_button.click(translateSrt, inputs=translate_input, outputs=translate_output)
+
+if __name__ == "__main__":
+    app.launch()

requirements.txt

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+openai~=0.27.2
+deepl~=1.14.0
+pydub~=0.25.1
+mecab-python3==1.0.6
+unidic-lite==1.0.8