import os
import gradio as gr


read_key = os.getenv('HUGGINGFACE_TOKEN')
client = Client("Albert-NHWang/Depth-Anywhere", hf_token=read_key)


def get_example():
    case = [
        [
            'examples/small_nthu_assembly.jpg'
        ],
        [
            'examples/small_Luca_Biada_flickr_2.jpg'
        ],
        [
            'examples/small_Dominic_Alves_flickr_panohead_test.jpg'
        ],
        [
            'examples/small_Luca_Biada_flickr.jpg'
        ],
    ]
    return case

def depth(path):
    depth_path = client.predict(handle_file(path), api_name='/process_image')
    return depth_path

intro = """
<div style="text-align:center">
<h1 style="font-weight: 1400; text-align: center; margin-bottom: 7px;">
   Depth Anywhere: Enhancing 360 Monocular Depth Estimation via Perspective Distillation and Unlabeled Data Augmentation
</h1>
<span>[<a target="_blank" href="https://albert100121.github.io/Depth-Anywhere/">Project page</a>], [<a target="_blank" href="http://arxiv.org/abs/2406.12849">Paper</a>], [<a target="_blank" href="https://huggingface.co/papers/2406.12849">Hugging Face Daily Paper</a>]</span>
<div style="display:flex; justify-content: center;margin-top: 0.5em">Please test with browsers other then Safari, and avoid using incognito window due to unsolved gradio bug!</div>
</div>
"""
footnote = """
<div style="display:flex; justify-content: left;margin-top: 0.5em">
Dominic Alves, https://www.flickr.com/photos/dominicspics/28296671029/, CC BY 2.0 DEED <br>
Luca Biada, https://www.flickr.com/photos/pedroscreamerovsky/6873256488/, CC BY 2.0 DEED <br>
Luca Biada, https://www.flickr.com/photos/pedroscreamerovsky/6798474782/, CC BY 2.0 DEED</div>
"""


with gr.Blocks(css="style.css") as demo:
    gr.HTML(intro)
    with gr.Row():
        input_image = gr.File(type="filepath")
        output_rgb = gr.Image(label="Loaded Image", type="filepath")
    with gr.Row():
        load_button = gr.Button("Load RGB!", visible=True)

    load_button.click(fn = lambda x: x,
        inputs = [input_image],
        outputs = [output_rgb]
        )
    
    with gr.Row():
        output_image = gr.Image(label="Output Depth", type="filepath")

    with gr.Row():
        run_button = gr.Button("Estimate Depth!", visible=True)

    run_button.click(fn = depth,
        inputs = [input_image],
        outputs = [output_image]
        )

    gr.Examples(
        fn=lambda x:x,
        inputs=[input_image], 
        outputs=[output_rgb], 
        examples=get_example(),
        run_on_click=True,
        cache_examples=False)
    
    gr.HTML(footnote)
demo.queue()
demo.launch()