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import httpcore |
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setattr(httpcore, 'SyncHTTPTransport', 'AsyncHTTPProxy') |
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import gradio as gr |
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from googletrans import Translator |
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from huggingface_hub import InferenceClient |
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from PIL import Image |
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import time |
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models =[ |
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"Yntec/NostalgicLife", |
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"Yntec/Genuine", |
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"Yntec/Abased", |
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"Yntec/CuteFurry", |
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"Yntec/incha_re_zoro", |
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"Yntec/InsaneM3U", |
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"digiplay/2K-VAE", |
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"digiplay/ya3_VAE", |
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"digiplay/ya3p_VAE", |
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"digiplay/pan04", |
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"digiplay/AM-mix1", |
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"digiplay/MRMD_0505", |
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] |
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translator = Translator() |
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def translate_to_english(prompt): |
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try: |
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translated_prompt = translator.translate(prompt, src='auto', dest='en').text |
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return translated_prompt |
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except Exception as e: |
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return str(e) |
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def respond_with_timestamp(prompt, model_name): |
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client = InferenceClient(model=model_name) |
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translated_prompt = translate_to_english(prompt) |
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prompt_with_timestamps = [f"{translated_prompt} {time.time() + i}" for i in range(3)] |
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images = [client.text_to_image(text) for text in prompt_with_timestamps] |
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return images |
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demo = gr.Interface( |
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fn=respond_with_timestamp, |
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inputs=[ |
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gr.Textbox(label="請輸入提示語 Please input a prompt"), |
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gr.Dropdown(label="選擇模型 Choose a model", choices=models) |
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], |
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outputs=[gr.Image(type="pil", label=f"img-{i+1}", show_share_button = False) for i in range(3)], |
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title="Text-to-Image with Google Translation", |
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description="Supports any languages, as long as Google supports them 😄<br>" |
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"Special Thanks : Yntec 🤗 and Every cool developers and artists and you on Huggingface." |
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) |
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if __name__ == "__main__": |
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demo.launch() |
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