| import gradio as gr | |
| import requests | |
| import base64 | |
| from PIL import Image | |
| from io import BytesIO | |
| def decode_base64_image(image_string): | |
| base64_image = base64.b64decode(image_string) | |
| buffer = BytesIO(base64_image) | |
| return Image.open(buffer) | |
| def inference(prompt, guidance_scale, num_inference_steps): | |
| api_url = 'https://a02q342s5b.execute-api.us-east-2.amazonaws.com/reinvent-demo-inf2-sm-20231114' | |
| prompt_input_one = { | |
| "prompt": prompt, | |
| "parameters": { | |
| "num_inference_steps": num_inference_steps, | |
| "guidance_scale": guidance_scale, | |
| "seed": -1 | |
| }, | |
| "endpoint": "huggingface-pytorch-inference-neuronx-2023-11-14-21-22-10-388" | |
| } | |
| response_one = requests.post(api_url, json=prompt_input_one) | |
| if response_one.status_code == 200: | |
| result_one = response_one.json() | |
| return decode_base64_image(result_one["generated_images"][0]) | |
| else: | |
| return None | |
| def app(): | |
| return gr.Interface(inference, | |
| [gr.Textbox( | |
| label="Prompt", | |
| info="Enter your prompt", | |
| lines=3, | |
| value="Self-portrait oil painting, a beautiful cyborg with golden hair, 8k", | |
| ), | |
| gr.Slider(2, 20, value=15, step=1, label="Guidance Scale"), | |
| gr.Slider(1, 50, value=20, step=1, label="Inference steps") | |
| ], | |
| gr.Image(type="pil", | |
| height=512, | |
| width=512 | |
| ) | |
| , allow_flagging='never', title='Gen Image', | |
| examples=[ | |
| ["A bustling metropolis skyline of towering skyscrapers, illuminated by the neon glow of futuristic advertisements and hover vehicles zipping through the airways, casting dynamic shadows on sleek, reflective surfaces below, 8k", 7, 20], | |
| ["Design an image capturing the essence of 'timeless wonder' in a mystical forest setting.", | |
| 7, 20], | |
| ["Visualize the emotions evoked by the words 'bittersweet symphony' in a unique artwork.", | |
| 15, 20], | |
| ] | |
| ) | |
| if __name__ == "__main__": | |
| app().launch() | |