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#!pip install -q transformers | |
#!pip install -q youtube_transcript_api | |
import gradio as gr | |
from transformers import pipeline | |
from youtube_transcript_api import YouTubeTranscriptApi | |
def TextScript_demo(input_text): | |
#youtube_video = "https://www.youtube.com/watch?v=7gTpHugdUWc" | |
youtube_video=input_text | |
video_id = youtube_video.split("=")[1] | |
YouTubeTranscriptApi.get_transcript(video_id) | |
transcript = YouTubeTranscriptApi.get_transcript(video_id) | |
result = "" | |
for i in transcript: | |
result += ' ' + i['text'] | |
#print(result) | |
# print(len(result)) | |
summarizer = pipeline('summarization') | |
num_iters = int(len(result)/1000) | |
summarized_text = [] | |
for i in range(0, num_iters + 1): | |
start = 0 | |
start = i * 1000 | |
end = (i + 1) * 1000 | |
#print("input text \n" + result[start:end]) | |
out = summarizer(result[start:end]) | |
#out = out[0] | |
#out = out['summary_text'] | |
#print("Summarized text\n"+out) | |
#summarized_text.append(out) | |
return out | |
title ='Text Script Generation from YouTube Link' | |
description = "Extract Script" | |
textScript_demo= gr.Interface(fn=TextScript_demo, inputs = 'text', outputs='text', title = title, description = description) | |