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import gradio as gr |
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import boto3 |
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import banana_dev as client |
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import os |
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from typing import Iterable |
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import gradio as gr |
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from gradio.themes.base import Base |
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from gradio.themes.utils import colors, fonts, sizes |
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from PIL import Image |
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import io |
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import base64 |
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from io import BytesIO |
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import traceback |
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import uuid |
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from dotenv import load_dotenv |
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import gzip |
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load_dotenv() |
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BANANA_API_KEY = os.getenv("BANANA_API_KEY") |
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BANANA_MODEL_KEY = os.getenv("BANANA_MODEL_KEY") |
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BANANA_URL = os.getenv("BANANA_URL") |
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def predict(image, prompt,qr_code, negative_prompt, seed): |
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try: |
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my_model = client.Client( |
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api_key=BANANA_API_KEY, |
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model_key=BANANA_MODEL_KEY, |
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url=BANANA_URL, |
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) |
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with open(image.name, "rb") as f: |
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image_bytes = f.read() |
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image_encoded = base64.b64encode(image_bytes) |
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image = image_encoded.decode("utf-8") |
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print(image) |
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print(negative_prompt) |
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print(seed) |
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print(qr_code) |
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print(prompt) |
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inputs = { |
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"prompt" : prompt, |
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"qr_code_content" : qr_code, |
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"negative_prompt": negative_prompt, |
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"image": image, |
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"seed": seed |
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} |
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result, meta = my_model.call("/", inputs) |
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output_bytes = result["outputs"] |
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image_encoded = output_bytes.encode('utf-8') |
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image_data = base64.b64decode(image_encoded) |
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image_data = gzip.decompress(image_data) |
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image_io = BytesIO(image_data) |
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output_image = Image.open(image_io) |
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return output_image, None |
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except Exception as e: |
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tb_str = traceback.format_exception(type(e), e, e.__traceback__) |
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tb_str = "".join(tb_str) |
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return None, tb_str |
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with gr.Blocks() as demo: |
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title_with_logo = gr.Markdown("# Powered by Banana <img src='https://files.umso.co/lib_udQIfMXlGlflDxFd/rnqmq7j8oqug1kae.png' align='left' width='50' height='50'>") |
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with gr.Column(): |
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image = gr.File(label="Image", file_count="single", scale=1) |
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prompt=gr.Textbox(label="Prompt") |
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qr_code=gr.Textbox(label="QR code link") |
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negative_prompt= gr.Textbox(label="Negative Prompt") |
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seed= gr.Textbox(label="Seed") |
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btn = gr.Button("Run illusion-diffusion-hq") |
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output_image = gr.Image(label="Output Image") |
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output_error = gr.Textbox(label="Error Message") |
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btn.click(predict, [image, prompt,qr_code, negative_prompt, seed], [output_image, output_error]) |
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demo.launch() |
