import numpy as np

import gradio as gr

title = "SavtaDepth WebApp"
description = "<center>Monocular Depth Estimation - Turn 2d photos into 3d photos</center>"
article = "<p style='text-align: center'><a href='https://dagshub.com/OperationSavta/SavtaDepth' target='_blank'>SavtaDepth Project from OperationSavta</a></p><p style='text-align: center'><a href='https://colab.research.google.com/drive/1XU4DgQ217_hUMU1dllppeQNw3pTRlHy1?usp=sharing' target='_blank'>Google Colab Demo</a></p></center></p>"

examples = [
    ["examples/00008.jpg"],
    ["examples/00045.jpg"],
]


def sepia(input_img):
    sepia_filter = np.array(
        [[0.393, 0.769, 0.189], [0.349, 0.686, 0.168], [0.272, 0.534, 0.131]]
    )
    sepia_img = input_img.dot(sepia_filter.T)
    sepia_img /= sepia_img.max()
    return sepia_img


iface = gr.Interface(sepia, gr.inputs.Image(shape=(200, 200)), "image", title = title, description = description, article = article, examples = examples)

iface.launch(enable_queue=True) # auth=("admin", "pass1234")