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| import gradio as gr | |
| import moviepy.video.io.ImageSequenceClip | |
| from PIL import Image | |
| from pydub import AudioSegment | |
| # Import everything needed to edit video clips | |
| from moviepy.editor import * | |
| import numpy as np | |
| import mutagen | |
| from mutagen.mp3 import MP3 | |
| import cv2 | |
| def resize(img_list): | |
| print("** inside resize **") | |
| print(img_list) | |
| resize_img_list = [] | |
| for item in img_list: | |
| im = Image.open(item) | |
| imResize = im.resize((256,256), Image.ANTIALIAS) | |
| resize_img_list.append(np.array(imResize)) | |
| print(type(resize_img_list[0])) | |
| return resize_img_list | |
| def merge_audio_video(entities_num, resize_img_list, text_input): | |
| print("** inside merge aud vid **") | |
| print(type(resize_img_list)) | |
| print(type(resize_img_list[0])) | |
| #Convert text to speech using facebook's latest model from HF hub | |
| speech = text2speech(text_input) | |
| print('type of speech : ',type(speech)) | |
| print(speech) | |
| wav_audio = AudioSegment.from_file(speech, "flac") #("/content/gdrive/My Drive/AI/audio1.flac", "flac") | |
| #convert flac to mp3 audio format | |
| print('flac audio read', type(wav_audio)) | |
| wav_audio.export("audio.mp3", format="mp3") #("/content/gdrive/My Drive/AI/audio1.mp3", format="mp3") | |
| print('flac audio converted to mp3 audio' ) | |
| print('now getting duration of this mp3 audio' ) | |
| #getting audio clip's duration | |
| audio_length = int(MP3("audio.mp3").info.length) | |
| #Calculate the desired frame per second based on given audio length and entities identified | |
| fps= entities_num / audio_length #length of audio file | |
| fps = float(format(fps, '.5f')) | |
| print('fps is: ',fps) | |
| #String a list of images into a video and write to memory | |
| clip = moviepy.video.io.ImageSequenceClip.ImageSequenceClip(resize_img_list, fps=fps) | |
| clip.write_videofile('my_vid_tmp.mp4') | |
| print('video clip created from images') | |
| # loading video file | |
| print('Starting video and audio merge') | |
| videoclip = VideoFileClip('my_vid_tmp.mp4') #("/content/gdrive/My Drive/AI/my_video1.mp4") | |
| print('loading video-clip audio') | |
| # loading audio file | |
| audioclip = AudioFileClip('audio.mp3') #.subclip(0, 15) | |
| print('loading mp3-format audio') | |
| # adding audio to the video clip | |
| mergedclip = videoclip.set_audio(audioclip) | |
| print('video and audio merged') | |
| #Getting size and frame count of merged video file | |
| print('Getting size and frame count of merged video file') | |
| duration = mergedclip.duration | |
| frame_count = mergedclip.fps | |
| print('duration is:',duration) | |
| print('frame count :', frame_count) | |
| return mergedclip | |
| fastspeech = gr.Interface.load("huggingface/facebook/fastspeech2-en-ljspeech") | |
| def text2speech(text): | |
| print('inside testtospeech') | |
| print(type(fastspeech)) | |
| print(fastspeech) | |
| speech = fastspeech(text) | |
| print(type(speech)) | |
| print(speech) | |
| return speech | |
| def engine(text_input): | |
| print(" ** Inside Enngine **") | |
| #Extract entities from text | |
| ner = gr.Interface.load("huggingface/flair/ner-english-ontonotes-large") | |
| entities = ner(text_input) | |
| entities = [tupl for tupl in entities if None not in tupl] | |
| entities_num = len(entities) | |
| #Generate images using multimodelart's space for each entity identified above | |
| img_list = [] | |
| for ent in entities: | |
| img = gr.Interface.load("spaces/multimodalart/latentdiffusion")(ent[0],'50','256','256','1',10)[0] | |
| img_list.append(img) | |
| print('img_list size:',len(img_list)) | |
| #Resizing all images produced to same size | |
| resize_img_list = resize(img_list) | |
| print('back from resize') | |
| #Merge video and audio created above | |
| mergedclip = merge_audio_video(entities_num, resize_img_list, text_input) | |
| print('Back in engine') | |
| print(' merged clip type :',type(mergedclip)) | |
| print('Writing the merged video clip to a file') | |
| mergedclip.to_videofile('mergedvideo.mp4') | |
| print('mergedvideo.mp4 created') | |
| return 'mergedvideo.mp4' | |
| app = gr.Interface(engine, | |
| gr.inputs.Textbox(lines=5, label="Input Text"), | |
| gr.outputs.Video(type=None, label='Final Merged video'), | |
| description="<div>Firstly, the Demo generates speech from input-text using facebook's fastspeech2-en-ljspeech from <a href='https://huggingface.co/facebook/fastspeech2-en-ljspeech' target='_blank'>HF hub</a>.<br>Then, takes the input-text and extracts the entities in it using Flair NER model from <a href='https://huggingface.co/flair/ner-english-ontonotes-large' target='_blank'>HF Hub</a>. <br>Then, generate images using <a href='https://huggingface.co/spaces/multimodalart/latentdiffusion' target='_blank'>Multimodalart Space</a> for every entity separately.<br>Creates a video by stringing all the entity-images together. <br>Lastly, Fuses the AI enerated audio and video together to create a coherent movie for you to watch. <br><br>A fun little app that lets you turn your text to video (well, in some ways atleast :) ). More the entities in your text, More time to build the output (expect 10-20 seconds per entity), More fun to watch.</div>" , | |
| examples=["On April 17th Sunday George celebrated Easter. He is staying at Empire State building with his parents. He is a citizen of Canada and speaks English and French fluently. His role model is former president Obama. He got 1000 dollar from his mother to visit Disney World and to buy new iPhone mobile. George likes watching Game of Thrones.", "April is the month of Easter weekend. Visit places like Statue of Liberty with friends. Take at least 200 dollars in cash with you. Use Android phone to find places in Newyork City."], | |
| title="Generate Video from Text", | |
| article="<br><div>For best results, make sure to enter a text that has entities listed on model card for <a href='https://huggingface.co/flair/ner-english-ontonotes-large' target='_blank'>flair/ner-english-ontonotes-large</a>. Some examples of type of entities that will be helpful are - Date values, event names, building names, languages, locations, money value, organization names, famous people names, products and so on.</div><br><h4 style='font-size: 110%;margin-top:1em'>Who owns the videos produced by this demo?</h4><div><i>(Borrowing this from multimodalart spaces)</i> Definetly not me! Probably you do. I say probably because the Copyright discussion about AI generated art is ongoing. So <a href='https://www.theverge.com/2022/2/21/22944335/us-copyright-office-reject-ai-generated-art-recent-entrance-to-paradise' target='_blank'>it may be the case that everything produced here falls automatically into the public domain</a>. But in any case it is either yours or is in the public domain.</div>" | |
| ).launch(enable_queue=True, debug=True) | |