import gradio as gr
import inference_flask as util
import cv2
from PIL import Image

model, transform, device = util.load_model()

def inference_img(input_img):
    global model, transform, device
    input_img = Image.fromarray(input_img)
    output = util.image_inference(model, transform, device, input_img, raw_img_input=True, return_img=True)
    output = cv2.putText(output[0],str(output[1]), (0,70), cv2.FONT_HERSHEY_SIMPLEX, 
                   1, (255, 0, 0), 2, cv2.LINE_AA)
    return output


with open('style.css', 'r') as f:
    css = f.read()

with gr.Blocks(css=css) as demo:
    gr.HTML('<a href="https://www.binoocle.com/"><img src="https://www.binoocle.com/wp-content/uploads/2019/10/Risorsa-1@2x-1.png" class="logo"></a>')

    # Load descriptions
    gr.HTML("<h1 class='title'>Crowdy spaces Model</h1>"
            "<br>"
            "<p> prova prova</p>")
    
    gr.Interface(inference_img, gr.Image(), "image")

    
demo.launch()