import gradio 
import cv2

#def inference(img, in_bright):
#    new_img = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
#    in_bright=1
#    return new_img

#iface = gradio.Interface(
#  fn=inference,
#  inputs=['image',gradio.Slider(0,100)],
#  outputs='image',
#  title='Change Image', 
#  description='Interface!',
#  examples=["llama.jpg"])  

#iface.launch()

import gradio as gr

def greet(image, name, is_morning, temperature):
    salutation = "Good morning" if is_morning else "Good evening"
    greeting = f"{salutation} {name}. It is {temperature} degrees today"
    celsius = (temperature - 32) * 5 / 9

    # contrast [1.0-3.0]
    # brightness [0-100]
    # https://docs.opencv.org/4.x/d3/dc1/tutorial_basic_linear_transform.html
    in_contrast = 1.0
    in_brightness = 50

    for y in range(image.shape[0]):
        for x in range(image.shape[1]):
            for c in range(image.shape[2]):
                new_image[y,x,c] = np.clip(in_contrast*image[y,x,c] + in_brightness, 0, 255)
    
    return new_image, greeting, round(celsius, 2)
    

demo = gr.Interface(
    fn=greet,
    inputs=['image',"text", "checkbox", gr.Slider(0, 100)],
    outputs=['image',"text", "number"],
)
demo.launch()