import gradio as gr import time from moviepy.editor import * from share_btn import community_icon_html, loading_icon_html, share_js caption = gr.Blocks.load(name="spaces/SRDdev/Image-Caption") audio_gen = gr.Blocks.load(name="spaces/haoheliu/audioldm-text-to-audio-generation") def infer(image_input): cap = caption(image_input, fn_index=0) sound = audio_gen(cap, 10, 2.5, 45, 3, fn_index=0) time.sleep(2) FILETOCONVERT = AudioFileClip(sound) FILETOCONVERT.write_audiofile("audio.wav") FILETOCONVERT.close() return gr.Textbox.update(value=cap, visible=True), "audio.wav", gr.Group.update(visible=True) title = """

Image to Sound Effect

Convert an image to a corresponding sound effect generated through GPT2 Image Captioning & AudioLDM

""" article = """

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""" with gr.Blocks(css="style.css") as demo: with gr.Column(elem_id="col-container"): gr.HTML(title) input_img = gr.Image(type="filepath", elem_id="input-img") caption_output = gr.Textbox(label="Caption", lines=1, visible=False, elem_id="text-caption") sound_output = gr.Audio(label="Result", elem_id="sound-output") generate = gr.Button("Generate SFX from Image") with gr.Group(elem_id="share-btn-container", visible=False) as share_group: community_icon = gr.HTML(community_icon_html) loading_icon = gr.HTML(loading_icon_html) share_button = gr.Button("Share to community", elem_id="share-btn") gr.HTML(article) generate.click(infer, inputs=[input_img], outputs=[caption_output, sound_output, share_group], api_name="i2fx") share_button.click(None, [], [], _js=share_js) demo.queue(max_size=32).launch(debug=True)