Spaces:
Runtime error
Runtime error
File size: 4,403 Bytes
2786a41 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 |
import numpy as np
import gradio as gr
import requests
import time
import json
import base64
import os
from PIL import Image
from io import BytesIO
class Prodia:
def __init__(self, api_key, base=None):
self.base = base or "https://api.prodia.com/v1"
self.headers = {
"X-Prodia-Key": api_key
}
def generate(self, params):
response = self._post(f"{self.base}/sdxl/generate", params)
return response.json()
def get_job(self, job_id):
response = self._get(f"{self.base}/job/{job_id}")
return response.json()
def wait(self, job):
job_result = job
while job_result['status'] not in ['succeeded', 'failed']:
time.sleep(0.25)
job_result = self.get_job(job['job'])
return job_result
def list_models(self):
response = self._get(f"{self.base}/sdxl/models")
return response.json()
def list_samplers(self):
response = self._get(f"{self.base}/sdxl/samplers")
return response.json()
def _post(self, url, params):
headers = {
**self.headers,
"Content-Type": "application/json"
}
response = requests.post(url, headers=headers, data=json.dumps(params))
if response.status_code != 200:
raise Exception(f"Bad Prodia Response: {response.status_code}")
return response
def _get(self, url):
response = requests.get(url, headers=self.headers)
if response.status_code != 200:
raise Exception(f"Bad Prodia Response: {response.status_code}")
return response
def image_to_base64(image_path):
# Open the image with PIL
with Image.open(image_path) as image:
# Convert the image to bytes
buffered = BytesIO()
image.save(buffered, format="PNG") # You can change format to PNG if needed
# Encode the bytes to base64
img_str = base64.b64encode(buffered.getvalue())
return img_str.decode('utf-8') # Convert bytes to string
prodia_client = Prodia(api_key=os.getenv("PRODIA_API_KEY"))
def flip_text(prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed):
result = prodia_client.generate({
"prompt": prompt,
"negative_prompt": negative_prompt,
"model": model,
"steps": steps,
"sampler": sampler,
"cfg_scale": cfg_scale,
"width": width,
"height": height,
"seed": seed
})
job = prodia_client.wait(result)
return job["imageUrl"]
css = """
#generate {
height: 100%;
}
"""
with gr.Blocks(css=css, model="sd_xl_base_1.0.safetensors [be9edd61]", sampler="DPM++ 2M Karras", batch_size=1, batch_count=1) as demo:
with gr.Row():
with gr.Column(scale=1):
gr.HTML(value=""""<h1><center>Fast SDXL on <a href="https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0" target="_blank">stabilityai/stable-diffusion-xl-base-1.0</a>""")
with gr.Column(scale=6, min_width=600):
prompt = gr.Textbox(label="Prompt", placeholder="a cute cat, 8k", show_label=true, lines=1)
text_button = gr.Button("Generate", variant='primary', elem_id="generate")
with gr.Row():
with gr.Accordion("Additionals inputs"):
with gr.Column(scale=1):
negative_prompt = gr.Textbox(label="Negative Prompt", value="text, blurry", placeholder="What you don't want to see in the image", show_label=True, lines=1)
with gr.Column(scale=1):
steps = gr.Slider(label="Sampling Steps", minimum=1, maximum=30, value=25, step=1)
cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, value=7, step=1)
seed = gr.Number(label="Seed", value=-1)
with gr.Column(scale=1):
width = gr.Slider(label="↔️ Width", minimum=1024, maximum=1024, value=1024, step=8)
height = gr.Slider(label="↕️ Height", minimum=1024, maximum=1024, value=1024, step=8)
with gr.Column(scale=1):
image_output = gr.Image()
text_button.click(flip_text, inputs=[prompt, negative_prompt, steps, cfg_scale, width, height, seed], outputs=image_output)
demo.queue(concurrency_count=16, max_size=20, api_open=False).launch(max_threads=64)
|