Update app.py
Browse files
app.py
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@@ -23,9 +23,9 @@ import uuid
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import time
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from PIL import Image
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import moviepy.editor as mp
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from videoretalking import inference_function
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import base64
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import gfpgan_enhancer
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start_time = time.time()
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@@ -192,55 +192,55 @@ def main(args):
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result, base64_video,temp_file_path,new_audio_path = animate_from_coeff.generate(data, save_dir, pic_path, crop_info, \
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enhancer=args.enhancer, background_enhancer=args.background_enhancer, preprocess=args.preprocess)
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face_path = temp_file_path
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audio_path = new_audio_path
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temp_file = tempfile.NamedTemporaryFile(delete=False, dir=TEMP_DIR.name, suffix='.mp4')
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video_lipsync_file_path = temp_file.name
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output_path = video_lipsync_file_path
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# Call the function
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inference_function.video_lipsync_correctness(
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)
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print('The video with lip sync is generated')
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print("GFPGAN Activated")
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gfpgan_enhancer.process_video_with_gfpgan(output_path, output_path)
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audio_clip = mp.AudioFileClip(new_audio_path)
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video_clip = mp.VideoFileClip(output_path)
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# Combine audio and video
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final_clip = video_clip.set_audio(audio_clip)
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temp_file = tempfile.NamedTemporaryFile(suffix='.mp4', dir=TEMP_DIR.name, delete=False)
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temp_file.close()
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final_video_path = temp_file.name
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final_clip.write_videofile(final_video_path)
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with open(final_video_path, 'rb') as f:
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base64_lipsync_video = base64.b64encode(video_content).decode('utf-8')
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video_clip = mp.VideoFileClip(final_video_path)
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duration = video_clip.duration
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app.config['temp_response'] =
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app.config['final_video_path'] =
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app.config['final_video_duration'] = duration
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return
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# shutil.move(result, save_dir+'.mp4')
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import time
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from PIL import Image
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import moviepy.editor as mp
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# from videoretalking import inference_function
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# import base64
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# import gfpgan_enhancer
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start_time = time.time()
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result, base64_video,temp_file_path,new_audio_path = animate_from_coeff.generate(data, save_dir, pic_path, crop_info, \
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enhancer=args.enhancer, background_enhancer=args.background_enhancer, preprocess=args.preprocess)
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# face_path = temp_file_path
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# audio_path = new_audio_path
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# temp_file = tempfile.NamedTemporaryFile(delete=False, dir=TEMP_DIR.name, suffix='.mp4')
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# video_lipsync_file_path = temp_file.name
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# output_path = video_lipsync_file_path
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# # Call the function
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# inference_function.video_lipsync_correctness(
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# face=face_path,
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# audio_path=audio_path,
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# face3d_net_path = path_of_net_recon_model,
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# outfile=output_path,
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# tmp_dir="temp",
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# crop=[0, -1, 0, -1],
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# re_preprocess=True, # Set to True if you want to reprocess; False otherwise
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# exp_img="neutral", # Can be 'smile', 'neutral', or path to an expression image
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# one_shot=False,
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# up_face="original", # Options: 'original', 'sad', 'angry', 'surprise'
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# LNet_batch_size=16,
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# without_rl1=False
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# )
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# print('The video with lip sync is generated')
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# print("GFPGAN Activated")
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# gfpgan_enhancer.process_video_with_gfpgan(output_path, output_path)
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# audio_clip = mp.AudioFileClip(new_audio_path)
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# video_clip = mp.VideoFileClip(output_path)
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# # Combine audio and video
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# final_clip = video_clip.set_audio(audio_clip)
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# temp_file = tempfile.NamedTemporaryFile(suffix='.mp4', dir=TEMP_DIR.name, delete=False)
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# temp_file.close()
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# final_video_path = temp_file.name
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# final_clip.write_videofile(final_video_path)
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# with open(final_video_path, 'rb') as f:
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# video_content = f.read()
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# base64_lipsync_video = base64.b64encode(video_content).decode('utf-8')
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# video_clip = mp.VideoFileClip(final_video_path)
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# duration = video_clip.duration
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app.config['temp_response'] = base64_video
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app.config['final_video_path'] = temp_file_path
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app.config['final_video_duration'] = duration
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return base64_video, temp_file_path, duration
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# shutil.move(result, save_dir+'.mp4')
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