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| import base64 | |
| import os | |
| from os import path as osp | |
| from PIL import Image | |
| from io import BytesIO | |
| from io import StringIO, BytesIO | |
| import textwrap | |
| from typing import Iterator, TextIO, List, Dict, Any, Optional, Sequence, Union | |
| import urllib.parse # Add this if missing | |
| import yt_dlp # Add this - it's missing! | |
| import glob | |
| from tqdm import tqdm | |
| from pytubefix import YouTube, Stream | |
| from youtube_transcript_api import YouTubeTranscriptApi | |
| from youtube_transcript_api.formatters import WebVTTFormatter | |
| from transformers import BridgeTowerProcessor, BridgeTowerForContrastiveLearning | |
| import torch | |
| import cv2 | |
| # encoding image at given path or PIL Image using base64 | |
| def encode_image(image_path_or_PIL_img): | |
| if isinstance(image_path_or_PIL_img, Image.Image): | |
| # this is a PIL image | |
| buffered = BytesIO() | |
| image_path_or_PIL_img.save(buffered, format="JPEG") | |
| return base64.b64encode(buffered.getvalue()).decode('utf-8') | |
| else: | |
| # this is a image_path | |
| with open(image_path_or_PIL_img, "rb") as image_file: | |
| return base64.b64encode(image_file.read()).decode('utf-8') | |
| # checking whether the given string is base64 or not | |
| def isBase64(sb): | |
| try: | |
| if isinstance(sb, str): | |
| # If there's any unicode here, an exception will be thrown and the function will return false | |
| sb_bytes = bytes(sb, 'ascii') | |
| elif isinstance(sb, bytes): | |
| sb_bytes = sb | |
| else: | |
| raise ValueError("Argument must be string or bytes") | |
| return base64.b64encode(base64.b64decode(sb_bytes)) == sb_bytes | |
| except Exception: | |
| return False | |
| def create_dummy_image(size=(224, 224)): | |
| """Creates a blank white image to be used as a dummy input when no real image is provided.""" | |
| return Image.new("RGB", size, (255, 255, 255)) | |
| def bt_embeddings(prompt, base64_image=None): | |
| # Load the processor and model | |
| processor = BridgeTowerProcessor.from_pretrained("BridgeTower/bridgetower-large-itm-mlm-itc") | |
| model = BridgeTowerForContrastiveLearning.from_pretrained("BridgeTower/bridgetower-large-itm-mlm-itc") | |
| if base64_image: | |
| if not isBase64(base64_image): | |
| raise TypeError("Image input must be in base64 encoding!") | |
| try: | |
| image_data = base64.b64decode(base64_image) | |
| image = Image.open(BytesIO(image_data)).convert("RGB") | |
| except Exception as e: | |
| raise ValueError("Invalid image data!") from e | |
| else: | |
| image = create_dummy_image() # Use a dummy white image for text-only input | |
| texts = [prompt] | |
| images = [image] | |
| inputs = processor(images=images, text=texts, padding=True, return_tensors="pt") | |
| with torch.no_grad(): | |
| outputs = model(**inputs) | |
| if base64_image: | |
| embeddings = outputs.cross_embeds # Use cross-modal embeddings when an image is provided | |
| else: | |
| embeddings = outputs.text_embeds # Extract unimodal text embeddings | |
| return embeddings.squeeze().tolist() | |
| # Resizes a image and maintains aspect ratio | |
| def maintain_aspect_ratio_resize(image, width=None, height=None, inter=cv2.INTER_AREA): | |
| # Grab the image size and initialize dimensions | |
| dim = None | |
| (h, w) = image.shape[:2] | |
| # Return original image if no need to resize | |
| if width is None and height is None: | |
| return image | |
| # We are resizing height if width is none | |
| if width is None: | |
| # Calculate the ratio of the height and construct the dimensions | |
| r = height / float(h) | |
| dim = (int(w * r), height) | |
| # We are resizing width if height is none | |
| else: | |
| # Calculate the ratio of the width and construct the dimensions | |
| r = width / float(w) | |
| dim = (width, int(h * r)) | |
| # Return the resized image | |
| return cv2.resize(image, dim, interpolation=inter) | |
| # a help function that helps to convert a specific time written as a string in format `webvtt` into a time in miliseconds | |
| def str2time(strtime): | |
| # strip character " if exists | |
| strtime = strtime.strip('"') | |
| # get hour, minute, second from time string | |
| hrs, mins, seconds = [float(c) for c in strtime.split(':')] | |
| # get the corresponding time as total seconds | |
| total_seconds = hrs * 60**2 + mins * 60 + seconds | |
| total_miliseconds = total_seconds * 1000 | |
| return total_miliseconds | |
| # helper function for convert time in second to time format for .vtt or .srt file | |
| 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 _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) | |
| # helper function to convert transcripts generated by whisper to .vtt file | |
| 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, | |
| ) | |
| # helper function to convert transcripts generated by whisper to .srt file | |
| 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 getSubs(segments: Iterator[dict], format: str, maxLineWidth: int=-1) -> 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 download_video(video_url, path='/tmp/'): | |
| print(f'Getting video information for {video_url}') | |
| if not video_url.startswith('http'): | |
| return os.path.join(path, video_url) | |
| filepath = glob.glob(os.path.join(path, '*.mp4')) | |
| if len(filepath) > 0: | |
| return filepath[0] | |
| def progress_callback(stream: Stream, data_chunk: bytes, bytes_remaining: int) -> None: | |
| pbar.update(len(data_chunk)) | |
| yt = YouTube(video_url, on_progress_callback=progress_callback) | |
| stream = yt.streams.filter(progressive=True, file_extension='mp4', res='720p').desc().first() | |
| if stream is None: | |
| stream = yt.streams.filter(progressive=True, file_extension='mp4').order_by('resolution').desc().first() | |
| if not os.path.exists(path): | |
| os.makedirs(path) | |
| filepath = os.path.join(path, stream.default_filename) | |
| if not os.path.exists(filepath): | |
| print('Downloading video from YouTube...') | |
| pbar = tqdm(desc='Downloading video from YouTube', total=stream.filesize, unit="bytes") | |
| stream.download(path) | |
| pbar.close() | |
| return filepath | |
| def get_video_id_from_url(video_url): | |
| """ | |
| Examples: | |
| - http://youtu.be/SA2iWivDJiE | |
| - http://www.youtube.com/watch?v=_oPAwA_Udwc&feature=feedu | |
| - http://www.youtube.com/embed/SA2iWivDJiE | |
| - http://www.youtube.com/v/SA2iWivDJiE?version=3&hl=en_US | |
| """ | |
| import urllib.parse | |
| url = urllib.parse.urlparse(video_url) | |
| if url.hostname == 'youtu.be': | |
| return url.path[1:] | |
| if url.hostname in ('www.youtube.com', 'youtube.com'): | |
| if url.path == '/watch': | |
| p = urllib.parse.parse_qs(url.query) | |
| return p['v'][0] | |
| if url.path[:7] == '/embed/': | |
| return url.path.split('/')[2] | |
| if url.path[:3] == '/v/': | |
| return url.path.split('/')[2] | |
| return video_url | |
| # if this has transcript then download | |
| def get_transcript_vtt(video_url, path='/tmp'): | |
| video_id = get_video_id_from_url(video_url) | |
| filepath = os.path.join(path,'captions.vtt') | |
| if os.path.exists(filepath): | |
| return filepath | |
| transcript = YouTubeTranscriptApi.get_transcript(video_id, languages=['en-GB', 'en']) | |
| formatter = WebVTTFormatter() | |
| webvtt_formatted = formatter.format_transcript(transcript) | |
| with open(filepath, 'w', encoding='utf-8') as webvtt_file: | |
| webvtt_file.write(webvtt_formatted) | |
| webvtt_file.close() | |
| return filepath | |
| # if this has transcript then download | |
| def download_youtube_subtitle(video_url, path='./shared_data/videos/video1'): | |
| video_id = video_url.split('v=')[-1] | |
| output_path = os.path.join(path, f"{video_id}.en.vtt") | |
| if os.path.exists(output_path): | |
| return output_path | |
| os.makedirs(path, exist_ok=True) | |
| ydl_opts = { | |
| 'skip_download': True, | |
| 'writesubtitles': True, | |
| 'subtitleslangs': ['en'], | |
| 'subtitlesformat': 'vtt', | |
| 'outtmpl': os.path.join(path, '%(id)s.%(ext)s'), | |
| } | |
| with yt_dlp.YoutubeDL(ydl_opts) as ydl: | |
| ydl.download([video_url]) | |
| return output_path |