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from inference import * |
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import gradio as gr |
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import glob |
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def gradio_app(image_path): |
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"""Helper function to run inference on provided image""" |
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predictions, out_pil = run_inference(image_path) |
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return out_pil |
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title = "MBARI Monterey Bay Benthic Supercategory" |
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description = "Gradio demo for MBARI Monterey Bay Benthic Supercategory: This " \ |
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"is a RetinaNet model fine-tuned from the Detectron2 object " \ |
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"detection platform's ResNet backbone to identify 20 benthic " \ |
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"supercategories drawn from MBARI's remotely operated vehicle " \ |
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"image data collected in Monterey Bay off the coast of Central " \ |
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"California. The data is drawn from FathomNet and consists of " \ |
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"32779 images that contain a total of 80683 localizations. The " \ |
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"model was trained on an 85/15 train/validation split at the " \ |
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"image level. DOI: 10.5281/zenodo.5571043. " |
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examples = glob.glob("images/*.png") |
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gr.Interface(run_inference, |
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inputs=[gr.inputs.Image(type="filepath")], |
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outputs=gr.outputs.Image(type="pil"), |
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enable_queue=True, |
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title=title, |
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description=description, |
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examples=examples).launch() |
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