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import json
import requests
import gradio as gr
def generate_image(prompt, negative_prompt, width, height, samples, num_inference_steps, safety_checker, enhance_prompt, seed, guidance_scale, multi_lingual, panorama, self_attention, upscale, embeddings, lora, webhook, track_id):
url = "https://modelslab.com/api/v6/images/text2img"
payload = json.dumps({
"key": "sHj15HTjxiCkFtV3PHmSeehjaVGdpNotsb1iMbIpniNzfTsjgbN7Z9RFB8Wu",
"model_id": "juggernaut-xl-v8",
"prompt": prompt,
"negative_prompt": negative_prompt,
"width": width,
"height": height,
"samples": samples,
"num_inference_steps": num_inference_steps,
"safety_checker": safety_checker,
"enhance_prompt": enhance_prompt,
"seed": seed,
"guidance_scale": guidance_scale,
"multi_lingual": multi_lingual,
"panorama": panorama,
"self_attention": self_attention,
"upscale": upscale,
"embeddings": embeddings,
"lora": lora,
"webhook": webhook,
"track_id": track_id
})
headers = {
'Content-Type': 'application/json'
}
response = requests.request("POST", url, headers=headers, data=payload)
return response.text
# Interface
iface = gr.Interface(fn=generate_image,
inputs=["text", "text", "text", "text", "text", "text", "text", "text", "text", "number", "text", "text", "text", "text", "text", "text", "text", "text", "text"],
outputs="text",
title="Text to Image Generation",
description="Generate an image based on text prompts.",
article="Enter your prompts and settings and click 'Generate Image'.")
iface.launch()
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