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import os
from io import StringIO, BytesIO
from typing import Iterator, TextIO, List, Dict, Any, Optional, Sequence, Union
import base64
import glob
from tqdm import tqdm
from pytubefix import YouTube, Stream
import cv2
import json
import textwrap
# 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,
)
# Taken from the course: https://www.deeplearning.ai/short-courses/multimodal-rag-chat-with-videos/
def getSubs(segments: Iterator[dict], format: str, maxLineWidth: int=-1) -> str:
segmentStream = StringIO()
if format == 'vtt':
write_vtt(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
# 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
# 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)
def load_json_file(file_path):
# Open the JSON file in read mode
with open(file_path, 'r') as file:
data = json.load(file)
return data |