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()