Create app.py
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app.py
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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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# Функция для взаимодействия с моделью на Hugging Face
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def process_image(image, prompt):
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# Загрузка изображения
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image_data = image.read()
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# Отправка запроса на API Hugging Face
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headers = {
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"Authorization": f"Bearer YOUR_HUGGINGFACE_TOKEN" # Замените YOUR_HUGGINGFACE_TOKEN на ваш токен
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}
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data = {
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"inputs": {
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"image": image_data,
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"prompt": prompt
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}
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}
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response = requests.post("https://api-inference.huggingface.co/models/CrucibleAI/ControlNetMediaPipeFace", headers=headers, files=data)
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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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