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import gradio as gr |
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import os |
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import time |
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from moviepy.editor import * |
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from share_btn import community_icon_html, loading_icon_html, share_js |
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token = os.environ.get('HF_TOKEN') |
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caption = gr.Blocks.load(name="spaces/SRDdev/Image-Caption") |
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audio_gen = gr.Blocks.load(name="spaces/fffiloni/audioldm-text-to-audio-generation-clone", api_key=token) |
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ph_message="If you're not happy with sound result, you can manually describe the scene depicted in your image :)" |
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def clean(input_img): |
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if input_img.value == None: |
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return manual_cap.update(value="",placeholder=ph_message), caption_output.update(value=None), sound_output.update(value=None) |
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else: |
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cap = caption(input_img.value, fn_index=0) |
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print("gpt2 caption: '" + cap + "' β’ ") |
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ph_update = "gpt2 caption: '" + cap + "' β’ " |
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return manual_cap.update(value="",placeholder=f"{ph_update}{ph_message}"), caption_output.update(value=cap), sound_output.update(value=None) |
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def infer(image_input, manual_caption, duration_in, seed): |
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print(duration_in) |
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if manual_caption == "": |
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cap = caption(image_input, fn_index=0) |
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print("gpt2 caption: '" + cap + "' β’ ") |
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ph_update = "gpt2 caption: '" + cap + "' β’ " |
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else: |
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cap = manual_caption |
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print("manual caption: " + cap) |
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ph_update="" |
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sound = audio_gen(cap, duration_in, 2.5, seed, 3, fn_index=0) |
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return cap, sound[1], gr.Textbox.update(placeholder=f"{ph_update}{ph_message}"), gr.Group.update(visible=True) |
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title = """ |
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<div style="text-align: center; max-width: 700px; margin: 0 auto;"> |
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<div |
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style=" |
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display: inline-flex; |
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align-items: center; |
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gap: 0.8rem; |
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font-size: 1.75rem; |
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" |
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> |
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<h1 style="font-weight: 900; margin-bottom: 7px; margin-top: 5px;"> |
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Image to Sound Effect |
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</h1> |
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</div> |
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<p style="margin-bottom: 10px; font-size: 94%"> |
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Convert an image to a corresponding sound effect generated through GPT2 Image Captioning & AudioLDM |
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</p> |
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</div> |
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""" |
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article = """ |
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<div class="footer"> |
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<p> |
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Follow <a href="https://twitter.com/fffiloni" target="_blank">Sylvain Filoni</a> for future updates π€ |
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</p> |
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</div> |
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<div id="may-like-container" style="display: flex;justify-content: center;flex-direction: column;align-items: center;margin-bottom: 30px;"> |
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<p>You may also like: </p> |
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<div id="may-like-content" style="display:flex;flex-wrap: wrap;align-items:center;height:20px;"> |
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<svg height="20" width="208" style="margin-left:4px;margin-bottom: 6px;"> |
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<a href="https://huggingface.co/spaces/haoheliu/audioldm-text-to-audio-generation" target="_blank"> |
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<image href="https://img.shields.io/badge/π€ Spaces-AudioLDM_Text_to_Audio-blue" src="https://img.shields.io/badge/π€ Spaces-AudioLDM_Text_to_Audio-blue.png" height="20"/> |
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</a> |
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</svg> |
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<svg height="20" width="122" style="margin-left:4px;margin-bottom: 6px;"> |
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<a href="https://huggingface.co/spaces/fffiloni/spectrogram-to-music" target="_blank"> |
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<image href="https://img.shields.io/badge/π€ Spaces-Riffusion-blue" src="https://img.shields.io/badge/π€ Spaces-Riffusion-blue.png" height="20"/> |
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</a> |
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</svg> |
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</div> |
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</div> |
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""" |
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with gr.Blocks(css="style.css") as demo: |
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with gr.Column(elem_id="col-container"): |
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gr.HTML(title) |
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input_img = gr.Image(type="filepath", elem_id="input-img") |
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with gr.Column(): |
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manual_cap = gr.Textbox(label="Manual Image description (optional)", lines=3, placeholder=ph_message) |
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with gr.Row(): |
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duration_in = gr.Slider(minimum=5, maximum=10, step=5, value=5, label="Duration") |
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seed_in = gr.Slider(label="Seed", value=440, minimum=45, maximum=10000, step=1) |
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caption_output = gr.Textbox(label="Caption", visible=False, elem_id="text-caption") |
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sound_output = gr.Audio(label="Result", elem_id="sound-output") |
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generate = gr.Button("Generate SFX from Image") |
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with gr.Group(elem_id="share-btn-container", visible=False) as share_group: |
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community_icon = gr.HTML(community_icon_html) |
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loading_icon = gr.HTML(loading_icon_html) |
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share_button = gr.Button("Share to community", elem_id="share-btn") |
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gr.HTML(article) |
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clean_out = [manual_cap, caption_output, sound_output] |
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input_img.change(clean, input_img, clean_out) |
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generate.click(infer, inputs=[input_img, manual_cap, duration_in, seed_in], outputs=[caption_output, sound_output, manual_cap, share_group], api_name="i2fx") |
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share_button.click(None, [], [], _js=share_js) |
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demo.queue(max_size=32).launch(debug=True) |
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