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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() |