| import warnings | |
| warnings.filterwarnings("ignore") | |
| import extract_info as ei | |
| import glob | |
| import gradio as gr | |
| title = "Reciepts Information Extraction using LayoutLMv3 Model" | |
| description = "Reciepts information extraction - Here we use Microsoft's LayoutLMv3 trained on WildReceipt Dataset to predict the keys and values. To use it, simply upload an image or use the example image below. Results will show up in a few seconds." | |
| css = """.output_image, .input_image {height: 600px !important}""" | |
| iface = gr.Interface(fn=ei.main, | |
| inputs=gr.Image(type="pil"), | |
| outputs=gr.Image(type="pil", label="annotated image"), | |
| title=title, | |
| description=description, | |
| css=css, | |
| analytics_enabled = True) | |
| iface.launch(inline=False, share=True, debug=False) |