def get_response_image(image):
    pil_img = image # reads the PIL image
    byte_arr = io.BytesIO()
    pil_img.save(byte_arr, format='PNG') # convert the PIL image to byte array
    encoded_img = encodebytes(byte_arr.getvalue()).decode('ascii') # encode as base64
    return encoded_img

@app.get("/plot-picture")
def plot_picture(description: str):
    model_id = "stabilityai/stable-diffusion-2"
    scheduler = EulerDiscreteScheduler.from_pretrained(model_id, subfolder="scheduler")
    pipe = StableDiffusionPipeline.from_pretrained(model_id, scheduler=scheduler, revision="fp16", torch_dtype=torch.float16)
    pipe = pipe.to("cuda")
    prompt = description
    images = pipe(prompt, height=512, width=512).images[0]
    encoded_img = get_response_image(images)
    response = { 'Status' : 'Success', 'ImageBytes': encoded_img }
    return response