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import os |
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import glob |
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from natsort import natsorted |
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import gradio as gr |
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from inference_util import init_model, infenrece |
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from attributtes_utils import input_pose, input_emotion, input_blink |
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model = init_model() |
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def process(input_vid, audio_path, pose_select, emotion_select, blink_select): |
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pose = input_pose(pose_select) |
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emotion = input_emotion(emotion_select) |
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blink = input_blink(blink_select) |
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print("input_vid: ", input_vid) |
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result = infenrece(model, os.path.join("./assets/videos/", input_vid), os.path.join("./assets/audios/", audio_path), pose, emotion, blink) |
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print("result: ", result) |
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print("finished !") |
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return result |
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available_videos = natsorted(glob.glob("./assets/videos/*.mp4")) |
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available_videos = [os.path.basename(x) for x in available_videos] |
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for video in available_videos: |
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audio = video.replace(".mp4", ".wav") |
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if not os.path.exists(os.path.join("./assets/audios/", audio)): |
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os.system(f"ffmpeg -y -loglevel error -i ./assets/videos/{video} -vn -acodec pcm_s16le -ar 16000 -ac 1 ./assets/audios/{audio}") |
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available_audios = natsorted(glob.glob("./assets/audios/*.wav")) |
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available_audios = [os.path.basename(x) for x in available_audios] |
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with gr.Blocks() as demo: |
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gr.HTML( |
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""" |
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<h1 style="text-align: center; font-size: 40px; font-family: 'Times New Roman', Times, serif;"> |
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Free-View Expressive Talking Head Video Editing |
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</h1> |
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<p style="text-align: center; font-size: 20px; font-family: 'Times New Roman', Times, serif;"> |
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<a style="text-align: center; display:inline-block" |
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href="https://sky24h.github.io/websites/icassp2023_free-view_video-editing"> |
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<img src="https://huggingface.co/datasets/huggingface/badges/raw/main/paper-page-sm.svg#center" |
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alt="Project Page"> |
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</a> |
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<a style="text-align: center; display:inline-block" href="https://huggingface.co/spaces/sky24h/Free-View_Expressive_Talking_Head_Video_Editing?duplicate=true"> |
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<img src="https://huggingface.co/datasets/huggingface/badges/raw/main/duplicate-this-space-sm.svg#center" alt="Duplicate Space"> |
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</a> |
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</p> |
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""" |
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) |
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with gr.Column(elem_id="col-container"): |
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with gr.Row(): |
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with gr.Column(): |
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video_preview = gr.Video(label="Video Preview", elem_id="video-preview", height=360, value="./assets/videos/sample1.mp4") |
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video_input = gr.Dropdown(available_videos, label="Input Video", value="sample1.mp4") |
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audio_preview = gr.Audio(label="Audio Preview", elem_id="audio-preview", height=360, value="./assets/audios/sample2.wav") |
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audio_input = gr.Dropdown(available_audios, label="Input Audio", value="sample2.wav") |
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pose_select = gr.Radio(["front", "left_right_shaking"], label="Pose", value="front") |
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emotion_select = gr.Radio(["neutral", "happy", "angry", "surprised"], label="Emotion", value="neutral") |
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blink_select = gr.Radio(["yes", "no"], label="Blink", value="yes") |
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with gr.Column(): |
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video_out = gr.Video(label="Video Output", elem_id="video-output", height=360) |
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submit_btn = gr.Button("Generate video") |
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inputs = [video_input, audio_input, pose_select, emotion_select, blink_select] |
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outputs = [video_out] |
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video_preview_output = [video_preview] |
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audio_preview_output = [audio_preview] |
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video_input.select(lambda x: "./assets/videos/" + x, video_input, video_preview_output) |
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audio_input.select(lambda x: "./assets/audios/" + x, audio_input, audio_preview_output) |
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submit_btn.click(process, inputs, outputs) |
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demo.queue(max_size=10).launch() |
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