better description
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app.py
CHANGED
@@ -51,17 +51,31 @@ def query_image(input_img, query, binarize, eval_threshold):
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# Gradio interface
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description = """
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</div>
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"""
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demo = gr.Interface(
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@@ -79,12 +93,15 @@ demo = gr.Interface(
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cache_examples=False,
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allow_flagging = "never",
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css = """
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.row {
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display: flex;
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}
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.column {
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flex:
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}
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"""
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)
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# Gradio interface
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description = """
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<div class="body">
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Gradio demo for an object detection architecture, introduced in my <a href="https://www.google.com/">bachelor thesis</a> (link will be added).
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\n\n
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You can use this architecture to detect objects using textual queries. To use it, simply upload an image and enter any query you want.
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It can be a single word or in the form of a sentence. The model is trained to recognize only 80 categories from the COCO Detection 2017 dataset.
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Refer to <a href="https://tech.amikelive.com/node-718/what-object-categories-labels-are-in-coco-dataset/">this</a> website
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or the original <a href="https://arxiv.org/pdf/1405.0312.pdf">COCO</a> paper to see the full list of categories.
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\n\n
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Best results are obtained using one of these sentences, which were used during training:
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<div class="row">
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<div class="column">
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<ul>
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<li>Find a {class}.</li>
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<li>Tea</li>
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<li>Milk</li>
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</ul>
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</div>
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<div class="column">
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<ul>
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<li>Coffee</li>
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<li>Tea</li>
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<li>Milk</li>
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</ul>
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</div>
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</div>
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</div>
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"""
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demo = gr.Interface(
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cache_examples=False,
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allow_flagging = "never",
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css = """
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.body {
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font-size: 14px;
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}
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.row {
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display: flex;
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}
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.column {
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flex: 30%;
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}
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"""
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)
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