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import gradio as gr
import requests
def generate_image(prompt):
apiUrl = 'https://apiv2.makeai.run/v2/txt2img' # Replace with your API URL
data = {
"mode": "url",
"model": "AOM3A1B_orangemixs.safetensors",
"tiling": false,
"batch_size": 1,
"prompt": prompt,
"negative_prompt": "worst quality, lowres",
"seed": 1234,
"scheduler": "Euler a",
"n_iter": 1,
"steps": 30,
"cfg": 11.0,
"offset_noise": 0.0,
"width": 1024,
"height": 1024,
"clip_skip": 1,
"loras": [
{
"name": "",
"strength": 1.0
}
],
"embeddings": [
{
"name": "",
"strength": 1.0
}
],
"vae": "vae-ft-mse-840000-ema-pruned.ckpt",
"restore_faces": false,
"fr_model": "CodeFormer",
"codeformer_weight": 0.5,
"enable_hr": false,
"denoising_strength": 0.75,
"hr_scale": 2,
"hr_upscale": "None",
"img2img_ref_img_type": "piece",
"img2img_resize_mode": 0,
"img2img_denoising_strength": 0.75,
"controlnet_enabled": false,
"controlnet_ref_img_type": "piece",
"controlnet_guessmode": false,
"controlnet_module": "canny",
"controlnet_model": "control_v11p_sd15_softedge",
"controlnet_weight": 1,
"controlnet_guidance_start": 0,
"controlnet_guidance_end": 1,
"controlnet_ref_img_url": "",
"controlnet_mask": [],
"controlnet_resize_mode": "Scale to Fit (Inner Fit)",
"controlnet_lowvram": false,
"controlnet_processor_res": 512,
"controlnet_threshold_a": 100,
"controlnet_threshold_b": 200
}
headers = {
'Content-Type': 'application/json',
'token': '514f7ecde6a5434dbab5c6579311ad82' # Replace with your API token
}
response = requests.post(apiUrl, json=data, headers=headers)
responseData = response.json()
if responseData and responseData['results'] and responseData['results'][0]:
return responseData['results'][0]
else:
return "No image generated"
# Uncomment the following lines if you want to use the control image component
# def generate_image(prompt, control_image):
# apiUrl = 'https://apiv2.makeai.run/v2/txt2img' # Replace with your API URL
# data = {
# ...
# "controlnet_ref_img_url": control_image,
# ...
# }
# headers = {
# ...
# }
# response = requests.post(apiUrl, json=data, headers=headers)
# responseData = response.json()
# if responseData and responseData['results'] and responseData['results'][0]:
# return responseData['results'][0]
# else:
# return "No image generated"
title = gr.outputs.Textbox(label="Freedom Demonstration")
prompt = gr.inputs.Textbox(lines=2, placeholder="Enter your prompt here", label="Prompt")
image = gr.outputs.Image(label="Generated Image")
# Uncomment the following line if you want to use the control image component
# control_image = gr.inputs.Image(label="Control Image (optional)")
iface = gr.Interface(
fn=generate_image,
inputs=[prompt], # Add control_image to the list if you want to use it
outputs=[title, image],
title="Freedom Demonstration",
description="This is a Gradio app that uses an API to generate images based on text prompts.",
live=False,
layout="vertical"
)
iface.launch() |