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Update app.py
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app.py
CHANGED
@@ -169,14 +169,7 @@ TITLE = "<h1 style='font-size: 2.5em; text-align: center;'>Identify objects in c
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DESCRIPTION = """<p style='font-size: 1.5em; line-height: 1.6em; text-align: left;'>Welcome to the object
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identification application. This tool allows you to upload an image, and it will identify and annotate objects within
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the image. Additionally, you can perform OCR analysis on the detected objects.</p>
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<ol style='font-size: 1.2em; line-height: 1.6em; text-align: left;'>
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<li>Upload an image by clicking on the "Upload Image" button.</li>
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<li>Adjust the "Confidence Threshold" and "IOU Threshold" sliders to set the detection sensitivity.</li>
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<li>Click on the "Predict" button to run the object detection model.</li>
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<li>The detected objects will be displayed in the "Detected Mark Object" gallery.</li>
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<li>To analyze the detected objects, click on the "Analysis" button. The results will be shown in the "Results" table.</li>
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</ol>
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"""
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CSS = """
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#output {
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@@ -187,11 +180,6 @@ CSS = """
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h1 {
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text-align: center;
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}
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p, h2, ol {
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text-align: left;
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margin: 0 auto;
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max-width: 800px;
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}
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"""
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EXAMPLES = [
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['examples/train1.png', 0.6, 0.25],
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DESCRIPTION = """<p style='font-size: 1.5em; line-height: 1.6em; text-align: left;'>Welcome to the object
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identification application. This tool allows you to upload an image, and it will identify and annotate objects within
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the image. Additionally, you can perform OCR analysis on the detected objects.</p>
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"""
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CSS = """
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#output {
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h1 {
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text-align: center;
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}
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"""
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EXAMPLES = [
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['examples/train1.png', 0.6, 0.25],
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