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import io
from PIL import Image
from IPython.display import Image as IPImage
import requests
import json
import gradio as gr
model_id_list = ['stablediffusionapi/dreamshaper-v7', 'runwayml/stable-diffusion-v1-5', 'stabilityai/stable-diffusion-2-1', 'digiplay/DreamShaper_7', 'hakurei/waifu-diffusion']
#Text-to-image endpoint
def get_completion(inputs, model_id, hf_api_key, parameters=None):
ENDPOINT_URL='https://api-inference.huggingface.co/models/{}'.format(model_id)
headers = {
"Authorization": f"Bearer {hf_api_key}",
"Content-Type": "application/json"
}
data = { "inputs": inputs }
if parameters is not None:
data.update({"parameters": parameters})
response = requests.request("POST",
ENDPOINT_URL,
headers=headers,
data=json.dumps(data))
if 'error' in str(response.content):
return None
else:
return IPImage(response.content)
# A helper function to convert the bytes string into PIL image to send to API
def bytes_to_pil_image(img_bytes):
byte_stream = io.BytesIO(img_bytes)
pil_image = Image.open(byte_stream)
return pil_image
def generate(hf_api_key, prompt):
outputs = []
for model_id in model_id_list:
output = get_completion(prompt, model_id, hf_api_key)
if output == None:
outputs.append(output)
else:
pil_image = bytes_to_pil_image(output.data) # Use the corrected function here
outputs.append(pil_image)
return outputs
with gr.Blocks() as demo:
gr.Markdown("# AI Image Comparator")
with gr.Row():
hf_api_key = gr.Textbox(label="Hugging Face API Key")
with gr.Row():
with gr.Column(scale=4):
prompt = gr.Textbox(label="Your prompt to generate image") #Give prompt some real estate
with gr.Column(scale=1, min_width=50):
btn = gr.Button("Submit") #Submit button side by side!
with gr.Row():
with gr.Column():
output1 = gr.Image(label= model_id_list[0])
with gr.Column():
output2 = gr.Image(label= model_id_list[1])
with gr.Row():
with gr.Column():
output3 = gr.Image(label= model_id_list[2])
with gr.Column():
output4 = gr.Image(label= model_id_list[3])
with gr.Column():
output5 = gr.Image(label= model_id_list[4])
btn.click(fn=generate, inputs=[hf_api_key, prompt], outputs=[output1,output2,output3,output4,output5])
gr.close_all()
demo.launch() |