templates/final.html

<!doctype html>
<html style="height:100%;">
<head>
    <title>Download Your Annotations</title>
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            <h1 class="text-3xl sm:text-4xl font-bold text-gray-800 leading-tight">
                🇰🇭 For the development of AI 🇰🇭
            </h1>
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    <div class="container" style="margin-top:20px;">
        <center>
        <div class="jumbotron">
            <h2>Download the annotations as jsonl file</h2> 
            <h3>The annotations are in Pascal VOC format</h3> 
            <button id="downloadButton" style="margin-top:10px;" class="btn btn-success">Download</button>
            <div id="messageBox" class="mt-8 p-4 bg-blue-100 border border-blue-400 text-blue-700 rounded-lg hidden" role="alert">
                <p id="messageText" class="font-medium"></p>
            </div>
                    <h5>You can use <code>datasets</code> package of huggingface to load the downloaded dataset. See demo code below.</h5>
            <div class="python-code-block">
                <pre><code class="language-python">
from datasets import load_dataset
your_data = load_dataset('imagefolder', data_dir='annotated_data') # this will use metadata.jsonl in annotated_data to create your_data
print(your_data)
# optional: you can easily plot one instance of your_data in jupyter notebook
import torch
from torchvision.utils import draw_bounding_boxes
from torchvision.transforms.functional import pil_to_tensor, to_pil_image

example = your_data['train'][0]
boxes_xyxy = torch.tensor(example['objects']['bbox'])
labels = [x for x in example['objects']['names']]
to_pil_image(
    draw_bounding_boxes(
        pil_to_tensor(example['image'].convert('RGB')),
        boxes_xyxy,
        colors="red",
        labels=labels,
    )
)
                </code></pre>
            </div>
            <script>
                document.getElementById('downloadButton').addEventListener('click', function() {
                    var messageBox = document.getElementById('messageBox');
                    var messageText = document.getElementById('messageText');
                    messageText.textContent = 'Good luck with your project!';
                    messageBox.classList.remove('hidden', 'bg-red-100', 'border-red-400', 'text-red-700', 'bg-green-100', 'border-green-400', 'text-green-700', 'bg-blue-100', 'border-blue-400', 'text-blue-700');
                    messageBox.classList.add('bg-green-100', 'border-green-400', 'text-green-700');
                    messageBox.classList.remove('hidden');

                    // Trigger the download by creating a temporary link and clicking it
                    var link = document.createElement('a');
                    link.href = "{{ url_for('download', download='annotations_pascal_voc.csv') }}";
                    link.download = 'my_file.txt'; // This is optional but good practice
                    document.body.appendChild(link);
                    link.click();
                    document.body.removeChild(link);

                    // Now, redirect the user after a short delay
                    setTimeout(function() {

                        window.location.href = "{{ url_for('index') }}";
                    }, 3000); // 1000ms = 1 second delay. Adjust as needed.
                });
            </script>
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        Thanks Huggingface Spaces 🤗
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