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demon071/autotranslate_hardsubs.py

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Created March 13, 2024 13:40
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Revisions

  1. @kumorikuma kumorikuma revised this gist Jan 31, 2023. 1 changed file with 110 additions and 93 deletions.
    203 changes: 110 additions & 93 deletions autotranslate_hardsubs.py
    View file
    Original file line number Diff line number Diff line change
    @@ -24,15 +24,27 @@ def gcloud_API_translate_text(textList, project_id, target_language_code):
    client = translate.TranslationServiceClient()
    location = "global"
    parent = f"projects/{project_id}/locations/{location}"
    response = client.translate_text(
    request={
    "parent": parent,
    "contents": textList,
    "mime_type": "text/plain",
    "target_language_code": target_language_code,
    }
    )
    return response.translations

    MAX_STRINGS = 1024 # GCloud API has hard limit of 1024 lines per request
    numStringsToTranslate = len(textList)
    numStringsTranslated = 0
    translations = []
    while numStringsTranslated < numStringsToTranslate:
    endIndex = numStringsTranslated + MAX_STRINGS
    if endIndex > numStringsToTranslate:
    endIndex = numStringsToTranslate
    contents = textList[numStringsTranslated:endIndex]
    response = client.translate_text(
    request={
    "parent": parent,
    "contents": contents,
    "mime_type": "text/plain",
    "target_language_code": target_language_code,
    }
    )
    numStringsTranslated += len(response.translations)
    translations.extend(response.translations)
    return translations

    os.system("") # enables ansi escape characters in terminal
    LINE_CLEAR = '\x1b[2K' # <-- ANSI sequence
    @@ -46,6 +58,7 @@ def gcloud_API_translate_text(textList, project_id, target_language_code):
    parser.add_argument('-l', '--language', help='Language to translate to', default='en-US', choices=['en-US', 'zh-CN', 'zh-TW', 'ja', 'ko'])
    parser.add_argument('--test_run', action='store_true', help='Runs a few times and displays debug info')
    parser.add_argument('--skip_cleanup', action='store_true', help='Does not delete temporary files')
    parser.add_argument('--skip_extract', action='store_true', help='Skips extracting subtitle images step (uses cached temporary files)')

    args = parser.parse_args()
    video_path = args.video_path
    @@ -57,59 +70,61 @@ def gcloud_API_translate_text(textList, project_id, target_language_code):
    project_id = args.project_id
    test_run = args.test_run
    skip_cleanup = args.skip_cleanup or test_run
    skip_extract = args.skip_extract

    # Generate raw images of the subtitles
    print("Extracting subtitle images with VideoSubFinder (takes quite a long time) ...")
    startTime = time.time()
    subprocess.run([
    "VideoSubFinderWXW.exe",
    "--clear_dirs",
    "--run_search",
    "--create_cleared_text_images",
    "--input_video", video_path,
    "--output_dir", tmp_dir,
    "--num_threads", str(4),
    "--num_ocr_threads", str(4),
    "--top_video_image_percent_end", str(0.25),
    "--bottom_video_image_percent_end", str(0.0)
    ], capture_output=True)
    endTime = time.time()
    print("Completed! Took "+str(endTime - startTime)+"s")
    if not skip_extract:
    print("Extracting subtitle images with VideoSubFinder (takes quite a long time) ...")
    startTime = time.time()
    subprocess.run([
    "VideoSubFinderWXW.exe",
    "--clear_dirs",
    "--run_search",
    "--create_cleared_text_images",
    "--input_video", video_path,
    "--output_dir", tmp_dir,
    "--num_threads", str(4),
    "--num_ocr_threads", str(4),
    "--top_video_image_percent_end", str(0.25),
    "--bottom_video_image_percent_end", str(0.0)
    ], capture_output=True)
    endTime = time.time()
    print("Completed! Took "+str(endTime - startTime)+"s")

    # Enumerate all the images
    imagePaths = []
    if os.path.isdir(txt_images_folder):
    filetypes = ('*.jpg', '*.jpeg', '*.png')
    for filetype in filetypes:
    globPath = os.path.join(txt_images_folder, filetype);
    imagePaths.extend(glob.glob(globPath));
    filetypes = ('*.jpg', '*.jpeg', '*.png')
    for filetype in filetypes:
    globPath = os.path.join(txt_images_folder, filetype);
    imagePaths.extend(glob.glob(globPath));
    else:
    print("ERROR: Invalid paths provided!\n")
    parser.print_help()
    sys.exit(2)
    print("ERROR: Invalid paths provided!\n")
    parser.print_help()
    sys.exit(2)
    numImages = len(imagePaths)

    # Reduce image size OCR has a max image size
    i = 0
    totalTimeElapsedS = 0
    estimateText = "Estimated time remaining: Unknown"
    for imagePath in imagePaths:
    if test_run and i > 10:
    break
    progressText = "Preprocessing image "+str(i+1)+"/"+str(numImages)+". "+estimateText+". Filename: " + os.path.basename(imagePath)
    print(end=LINE_CLEAR)
    print(progressText, end='\r')
    startTime = time.time()
    # Leaving some padding and not doing "-trim" seems to be important
    subprocess.run(["magick", "convert", imagePath, "-resize", "x200>", imagePath], capture_output=True)
    endTime = time.time()
    i += 1
    # Some logic to provide an estimated time
    timeElapsed = endTime - startTime
    totalTimeElapsedS += timeElapsed
    averageTime = totalTimeElapsedS / float(i)
    numImagesRemaining = numImages - i
    estimateText = "Estimated time remaining: "+str(averageTime * numImagesRemaining)+"s"
    if test_run and i > 10:
    break
    progressText = "Preprocessing image "+str(i+1)+"/"+str(numImages)+". "+estimateText+". Filename: " + os.path.basename(imagePath)
    print(end=LINE_CLEAR)
    print(progressText, end='\r')
    startTime = time.time()
    # Leaving some padding and not doing "-trim" seems to be important
    subprocess.run(["magick", "convert", imagePath, "-resize", "x200>", imagePath], capture_output=True)
    endTime = time.time()
    i += 1
    # Some logic to provide an estimated time
    timeElapsed = endTime - startTime
    totalTimeElapsedS += timeElapsed
    averageTime = totalTimeElapsedS / float(i)
    numImagesRemaining = numImages - i
    estimateText = "Estimated time remaining: "+str(averageTime * numImagesRemaining)+"s"

    # Run Windows OCR on the images and save to text file
    i = 0
    @@ -119,68 +134,70 @@ def gcloud_API_translate_text(textList, project_id, target_language_code):
    baseNameList = []
    textList = []
    for imagePath in imagePaths:
    if test_run and i > 10:
    break
    progressText = "Running OCR on image "+str(i+1)+"/"+str(numImages)+". "+estimateText+". Filename: " + os.path.basename(imagePath)
    print(end=LINE_CLEAR)
    print(progressText, end='\r')
    startTime = time.time()
    result = subprocess.run(["Windows.Media.Ocr.Cli.exe", imagePath], capture_output=True)
    ocrText = result.stdout.decode("utf-8")
    # Replace carriage returns with spaces.
    # This leads to more naturally flowing translations most of the time.
    ocrText = " ".join(ocrText.splitlines()).strip()
    filename, ext = os.path.splitext(imagePath)
    basename = os.path.basename(filename)
    # GCloud API throws error if we give it blanks
    if len(ocrText) > 0:
    baseNameList.append(basename)
    textList.append(ocrText)
    totalCharacterCount += len(ocrText)
    endTime = time.time()
    i += 1
    # Some logic to provide an estimated time
    timeElapsed = endTime - startTime
    totalTimeElapsedS += timeElapsed
    averageTime = totalTimeElapsedS / float(i)
    numImagesRemaining = numImages - i
    estimateText = "Estimated time remaining: "+str(averageTime * numImagesRemaining)+"s"
    if test_run and i > 10:
    break
    progressText = "Running OCR on image "+str(i+1)+"/"+str(numImages)+". "+estimateText+". Filename: " + os.path.basename(imagePath)
    print(end=LINE_CLEAR)
    print(progressText, end='\r')
    startTime = time.time()
    result = subprocess.run(["Windows.Media.Ocr.Cli.exe", imagePath], capture_output=True)
    ocrText = result.stdout.decode("utf-8")
    # Replace carriage returns with spaces.
    # This leads to more naturally flowing translations most of the time.
    ocrText = " ".join(ocrText.splitlines()).strip()
    filename, ext = os.path.splitext(imagePath)
    basename = os.path.basename(filename)
    # GCloud API throws error if we give it blanks
    if len(ocrText) > 0:
    baseNameList.append(basename)
    textList.append(ocrText)
    totalCharacterCount += len(ocrText)
    endTime = time.time()
    i += 1
    # Some logic to provide an estimated time
    timeElapsed = endTime - startTime
    totalTimeElapsedS += timeElapsed
    averageTime = totalTimeElapsedS / float(i)
    numImagesRemaining = numImages - i
    estimateText = "Estimated time remaining: "+str(averageTime * numImagesRemaining)+"s"
    # Additionally writeout to file for easier debugging
    original_text_file = os.path.join(tmp_dir, "original_text.txt")
    with open(original_text_file, 'w', encoding="utf-8") as f:
    for i in range(len(textList)):
    f.write(str(i)+": "+textList[i]+"\n")

    print('')

    # Translate via Google Cloud Translation API and output to disk
    print("Translating text...")
    translations = gcloud_API_translate_text(textList, project_id, target_language_code)
    print("# of characters translated: " + str(totalCharacterCount))
    print("# of lines translated: " + str(len(translations)))
    for i in range(len(translations)):
    out_filepath = os.path.join(txt_results_folder, baseNameList[i]) + '.txt'
    translated_text = translations[i].translated_text
    if test_run:
    print("Orignal text: " + repr(textList[i]))
    print("Translated text: " + repr(translated_text))
    with open(out_filepath, 'w', encoding="utf-8") as f:
    f.write(translated_text)
    # Additional writeout all text to files for easier debugging
    if skip_cleanup:
    with open(os.path.join(tmp_dir, "original_text.txt"), 'w', encoding="utf-8") as f:
    for i in range(len(textList)):
    f.write(str(i)+": "+textList[i]+"\n")
    with open(os.path.join(tmp_dir, "translated_text.txt"), 'w', encoding="utf-8") as f:
    for i in range(len(translations)):
    f.write(str(i)+": "+translations[i].translated_text+"\n")
    out_filepath = os.path.join(txt_results_folder, baseNameList[i]) + '.txt'
    translated_text = translations[i].translated_text
    if test_run:
    print("Orignal text: " + repr(textList[i]))
    print("Translated text: " + repr(translated_text))
    with open(out_filepath, 'w', encoding="utf-8") as f:
    f.write(translated_text)
    # Additionally writeout to file for easier debugging
    with open(os.path.join(tmp_dir, "translated_text.txt"), 'w', encoding="utf-8") as f:
    for i in range(len(translations)):
    f.write(str(i)+": "+translations[i].translated_text+"\n")

    # Generate subtitle file
    srt_path = video_filename+".srt"
    print("Generating softsubs with VideoSubFinder... Output file: "+srt_path)
    startTime = time.time()
    subprocess.run([
    "VideoSubFinderWXW.exe",
    "--create_sub_from_txt_results", srt_path,
    "--output_dir", tmp_dir
    "VideoSubFinderWXW.exe",
    "--create_sub_from_txt_results", srt_path,
    "--output_dir", tmp_dir
    ], capture_output=True)
    endTime = time.time()
    print("Completed! Took "+str(endTime - startTime)+"s")

    # Cleanup if needed
    if not skip_cleanup:
    shutil.rmtree(tmp_dir, ignore_errors=True)
    shutil.rmtree(tmp_dir, ignore_errors=True)
  2. @kumorikuma kumorikuma created this gist Jan 31, 2023.
    186 changes: 186 additions & 0 deletions autotranslate_hardsubs.py
    View file
    Original file line number Diff line number Diff line change
    @@ -0,0 +1,186 @@
    # Requirements:
    # - ImageMagick binary
    # - Windows.Media.Ocr.Cli binary
    # - VideoSubFinder binary
    #
    # Official GCloud Translate Setup:
    # First 500k characters / mo is free: https://cloud.google.com/translate/pricing
    # Install Python Module: pip install google-cloud-translate
    # Setup Google Cloud account and billing information: https://cloud.google.com/
    # Make a new project and enable "Cloud Translation API": https://console.cloud.google.com/apis/dashboard
    # Install GCloud CLI: https://cloud.google.com/sdk/docs/install
    # Setup authentication: https://cloud.google.com/docs/authentication/provide-credentials-adc#on-prem

    import argparse
    import glob
    import os
    import shutil
    import subprocess
    import sys
    import time

    from google.cloud import translate
    def gcloud_API_translate_text(textList, project_id, target_language_code):
    client = translate.TranslationServiceClient()
    location = "global"
    parent = f"projects/{project_id}/locations/{location}"
    response = client.translate_text(
    request={
    "parent": parent,
    "contents": textList,
    "mime_type": "text/plain",
    "target_language_code": target_language_code,
    }
    )
    return response.translations

    os.system("") # enables ansi escape characters in terminal
    LINE_CLEAR = '\x1b[2K' # <-- ANSI sequence

    parser = argparse.ArgumentParser(description="Takes as input a video with hardsubs, and will generate translated softsubs in the target language.")
    parser.add_argument('video_path', help='Path to input video')
    parser.add_argument('-pid', '--project_id', help='Google Cloud Project ID', required=True)
    parser.add_argument('-t', '--tmp_dir', help='Path to tmp dir', default='tmp')
    parser.add_argument('-te', '--top_edge_offset', help='How much of top of video to ignore', default=0.75)
    parser.add_argument('-be', '--bottom_edge_offset', help='How much of bottom of video to ignore', default=0.0)
    parser.add_argument('-l', '--language', help='Language to translate to', default='en-US', choices=['en-US', 'zh-CN', 'zh-TW', 'ja', 'ko'])
    parser.add_argument('--test_run', action='store_true', help='Runs a few times and displays debug info')
    parser.add_argument('--skip_cleanup', action='store_true', help='Does not delete temporary files')

    args = parser.parse_args()
    video_path = args.video_path
    video_filename, ext = os.path.splitext(video_path)
    tmp_dir = args.tmp_dir
    txt_images_folder = os.path.join(tmp_dir, "TXTImages")
    txt_results_folder = os.path.join(tmp_dir, "TXTResults")
    target_language_code = args.language
    project_id = args.project_id
    test_run = args.test_run
    skip_cleanup = args.skip_cleanup or test_run

    # Generate raw images of the subtitles
    print("Extracting subtitle images with VideoSubFinder (takes quite a long time) ...")
    startTime = time.time()
    subprocess.run([
    "VideoSubFinderWXW.exe",
    "--clear_dirs",
    "--run_search",
    "--create_cleared_text_images",
    "--input_video", video_path,
    "--output_dir", tmp_dir,
    "--num_threads", str(4),
    "--num_ocr_threads", str(4),
    "--top_video_image_percent_end", str(0.25),
    "--bottom_video_image_percent_end", str(0.0)
    ], capture_output=True)
    endTime = time.time()
    print("Completed! Took "+str(endTime - startTime)+"s")

    # Enumerate all the images
    imagePaths = []
    if os.path.isdir(txt_images_folder):
    filetypes = ('*.jpg', '*.jpeg', '*.png')
    for filetype in filetypes:
    globPath = os.path.join(txt_images_folder, filetype);
    imagePaths.extend(glob.glob(globPath));
    else:
    print("ERROR: Invalid paths provided!\n")
    parser.print_help()
    sys.exit(2)
    numImages = len(imagePaths)

    # Reduce image size OCR has a max image size
    i = 0
    totalTimeElapsedS = 0
    estimateText = "Estimated time remaining: Unknown"
    for imagePath in imagePaths:
    if test_run and i > 10:
    break
    progressText = "Preprocessing image "+str(i+1)+"/"+str(numImages)+". "+estimateText+". Filename: " + os.path.basename(imagePath)
    print(end=LINE_CLEAR)
    print(progressText, end='\r')
    startTime = time.time()
    # Leaving some padding and not doing "-trim" seems to be important
    subprocess.run(["magick", "convert", imagePath, "-resize", "x200>", imagePath], capture_output=True)
    endTime = time.time()
    i += 1
    # Some logic to provide an estimated time
    timeElapsed = endTime - startTime
    totalTimeElapsedS += timeElapsed
    averageTime = totalTimeElapsedS / float(i)
    numImagesRemaining = numImages - i
    estimateText = "Estimated time remaining: "+str(averageTime * numImagesRemaining)+"s"

    # Run Windows OCR on the images and save to text file
    i = 0
    totalTimeElapsedS = 0
    totalCharacterCount = 0
    estimateText = "Estimated time remaining: Unknown"
    baseNameList = []
    textList = []
    for imagePath in imagePaths:
    if test_run and i > 10:
    break
    progressText = "Running OCR on image "+str(i+1)+"/"+str(numImages)+". "+estimateText+". Filename: " + os.path.basename(imagePath)
    print(end=LINE_CLEAR)
    print(progressText, end='\r')
    startTime = time.time()
    result = subprocess.run(["Windows.Media.Ocr.Cli.exe", imagePath], capture_output=True)
    ocrText = result.stdout.decode("utf-8")
    # Replace carriage returns with spaces.
    # This leads to more naturally flowing translations most of the time.
    ocrText = " ".join(ocrText.splitlines()).strip()
    filename, ext = os.path.splitext(imagePath)
    basename = os.path.basename(filename)
    # GCloud API throws error if we give it blanks
    if len(ocrText) > 0:
    baseNameList.append(basename)
    textList.append(ocrText)
    totalCharacterCount += len(ocrText)
    endTime = time.time()
    i += 1
    # Some logic to provide an estimated time
    timeElapsed = endTime - startTime
    totalTimeElapsedS += timeElapsed
    averageTime = totalTimeElapsedS / float(i)
    numImagesRemaining = numImages - i
    estimateText = "Estimated time remaining: "+str(averageTime * numImagesRemaining)+"s"

    print('')

    # Translate via Google Cloud Translation API and output to disk
    print("Translating text...")
    translations = gcloud_API_translate_text(textList, project_id, target_language_code)
    print("# of characters translated: " + str(totalCharacterCount))
    for i in range(len(translations)):
    out_filepath = os.path.join(txt_results_folder, baseNameList[i]) + '.txt'
    translated_text = translations[i].translated_text
    if test_run:
    print("Orignal text: " + repr(textList[i]))
    print("Translated text: " + repr(translated_text))
    with open(out_filepath, 'w', encoding="utf-8") as f:
    f.write(translated_text)
    # Additional writeout all text to files for easier debugging
    if skip_cleanup:
    with open(os.path.join(tmp_dir, "original_text.txt"), 'w', encoding="utf-8") as f:
    for i in range(len(textList)):
    f.write(str(i)+": "+textList[i]+"\n")
    with open(os.path.join(tmp_dir, "translated_text.txt"), 'w', encoding="utf-8") as f:
    for i in range(len(translations)):
    f.write(str(i)+": "+translations[i].translated_text+"\n")

    # Generate subtitle file
    srt_path = video_filename+".srt"
    print("Generating softsubs with VideoSubFinder... Output file: "+srt_path)
    startTime = time.time()
    subprocess.run([
    "VideoSubFinderWXW.exe",
    "--create_sub_from_txt_results", srt_path,
    "--output_dir", tmp_dir
    ], capture_output=True)
    endTime = time.time()
    print("Completed! Took "+str(endTime - startTime)+"s")

    # Cleanup if needed
    if not skip_cleanup:
    shutil.rmtree(tmp_dir, ignore_errors=True)