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| from inference import prediction | |
| import gradio as gr | |
| import json | |
| title = "Interactive demo: LayoutLMv3 for receipts" | |
| description = "Demo for Microsoft's LayoutLMv3, a Transformer for state-of-the-art document image understanding tasks. This particular space uses an instance of the model fine-tuned on a dataset that combines CORD and SROIE.\n To use it, simply upload an image or use the example image below. Results will show up in a few seconds." | |
| examples = [['image.jpg'],['image.PNG']] | |
| css = """.output_image, .input_image {height: 600px !important}, .output_json { color: black; }""" | |
| # gradio interface that takes in input an image and return a JSON file that contains its info | |
| # for now it shows also the intermediate steps | |
| iface = gr.Interface(theme=gr.themes.Monochrome(), | |
| fn=prediction, | |
| inputs=gr.Image(type="pil"), | |
| outputs=[ | |
| #gr.Image(type="pil", label="annotated image"), | |
| gr.JSON(label="final output")], | |
| title=title, | |
| description=description, | |
| examples=examples, | |
| css=css) | |
| iface.launch() | |