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""" |
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import gradio as gr |
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from PIL import Image |
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import requests |
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from io import BytesIO |
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import os |
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# Функция для взаимодействия с моделью на Hugging Face |
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def process_image(image, prompt): |
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# Преобразование объекта Image в байты |
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buffered = BytesIO() |
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image.save(buffered, format="JPEG") |
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image_data = buffered.getvalue() |
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# Отправка запроса на API Hugging Face |
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headers = { |
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"Authorization": f"Bearer {os.getenv('HF_TOKEN')}" |
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} |
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files = { |
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"file": ("image.jpg", image_data, "image/jpeg"), |
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"data": (None, '{"inputs": {"prompt": ' + f'"{prompt}"' + '}}', "application/json"), |
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} |
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response = requests.post("https://api-inference.huggingface.co/models/CrucibleAI/ControlNetMediaPipeFace", headers=headers, files=files) |
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# Обработка ответа |
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if response.status_code == 200: |
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# Преобразование ответа в изображение |
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image = Image.open(BytesIO(response.content)) |
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return image |
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else: |
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# В случае ошибки возвращаем информацию об ошибке |
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return f"Error: {response.text}" |
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# Создание Gradio Blocks интерфейса |
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with gr.Blocks() as demo: |
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with gr.Row(): |
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with gr.Column(): |
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image_input = gr.Image(type="pil", label="Upload Image") |
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prompt_input = gr.Textbox(label="Enter Prompt") |
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with gr.Column(): |
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output_image = gr.Image(type="pil", label="Output Image") |
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submit_button = gr.Button("Submit") |
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submit_button.click(fn=process_image, inputs=[image_input, prompt_input], outputs=output_image) |
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# Запуск интерфейса |
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demo.launch() |
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""" |
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import gradio as gr |
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from transformers import StableDiffusionPipeline |
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from PIL import Image |
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import torch |
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pipe = StableDiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0") |
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pipe = pipe.to("cuda") |
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def image_to_image(image, prompt): |
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image = Image.fromarray(image.astype('uint8'), 'RGB') |
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with torch.autocast("cuda"): |
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image = pipe(prompt=prompt, init_image=image, strength=0.8)["sample"][0] |
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return image |
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with gr.Blocks() as demo: |
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with gr.Row(): |
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with gr.Column(): |
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image_input = gr.Image(type="pil") |
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prompt_input = gr.Textbox(placeholder="Enter prompt here...") |
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with gr.Column(): |
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output_image = gr.Image(type="pil") |
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with gr.Row(): |
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submit_button = gr.Button("Generate") |
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submit_button.click( |
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fn=image_to_image, |
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inputs=[image_input, prompt_input], |
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outputs=output_image |
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) |
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demo.launch() |
