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| import gradio as gr | |
| from helper.examples.examples import DemoImages | |
| from src.htr_pipeline.gradio_backend import FastTrack, SingletonModelLoader | |
| model_loader = SingletonModelLoader() | |
| fast_track = FastTrack(model_loader) | |
| images_for_demo = DemoImages() | |
| with gr.Blocks() as htr_tool_tab: | |
| with gr.Row(equal_height=True): | |
| with gr.Column(scale=2): | |
| with gr.Row(): | |
| fast_track_input_region_image = gr.Image( | |
| label="Image to run HTR on", type="numpy", tool="editor", elem_id="image_upload", height=395 | |
| ) | |
| with gr.Row(): | |
| # with gr.Group(): | |
| # callback = gr.CSVLogger() | |
| # # hf_writer = gr.HuggingFaceDatasetSaver(HF_API_TOKEN, "htr_pipelin_flags") | |
| # flagging_button = gr.Button( | |
| # "Flag", | |
| # variant="secondary", | |
| # visible=True, | |
| # ).style(full_width=True) | |
| # radio_file_input = gr.Radio( | |
| # value="Text file", choices=["Text file ", "Page XML file "], label="What kind file output?" | |
| # ) | |
| radio_file_input = gr.CheckboxGroup( | |
| choices=["Txt", "XML"], | |
| value=["Txt"], | |
| label="Output file extension", | |
| # info="Only txt and page xml is supported for now!", | |
| ) | |
| htr_pipeline_button = gr.Button( | |
| "Run HTR", | |
| variant="primary", | |
| visible=True, | |
| elem_id="run_pipeline_button", | |
| ).style(full_width=False) | |
| with gr.Group(): | |
| with gr.Row(): | |
| fast_file_downlod = gr.File(label="Download output file", visible=False) | |
| with gr.Row(): | |
| with gr.Accordion("Example images to use:", open=False) as fast_example_accord: | |
| fast_name_files_placeholder = gr.Markdown(visible=False) | |
| gr.Examples( | |
| examples=images_for_demo.examples_list, | |
| inputs=[fast_name_files_placeholder, fast_track_input_region_image], | |
| label="Example images", | |
| examples_per_page=5, | |
| ) | |
| with gr.Row(): | |
| gr.Markdown( | |
| """ | |
| Image viewer for xml output: | |
| <p align="center"> | |
| <a href="https://huggingface.co/spaces/Riksarkivet/Viewer_demo"> | |
| <img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-xl-dark.svg" alt="Badge 1"> | |
| </a> | |
| </p> | |
| """ | |
| ) | |
| with gr.Column(scale=4): | |
| fast_track_output_image = gr.Image(label="HTR results visualizer", type="numpy", tool="editor", height=650) | |
| with gr.Row(visible=False) as api_placeholder: | |
| htr_pipeline_button_api = gr.Button( | |
| "Run pipeline", | |
| variant="primary", | |
| visible=False, | |
| ).style(full_width=False) | |
| xml_rendered_placeholder_for_api = gr.Textbox(visible=False) | |
| htr_pipeline_button.click( | |
| fast_track.segment_to_xml, | |
| inputs=[fast_track_input_region_image, radio_file_input], | |
| outputs=[fast_track_output_image, fast_file_downlod, fast_file_downlod], | |
| ) | |
| htr_pipeline_button_api.click( | |
| fast_track.segment_to_xml_api, | |
| inputs=[fast_track_input_region_image], | |
| outputs=[xml_rendered_placeholder_for_api], | |
| api_name="predict", | |
| ) | |
| # callback.setup([fast_track_input_region_image], "flagged_data_points") | |
| # flagging_button.click(lambda *args: callback.flag(args), [fast_track_input_region_image], None, preprocess=False) | |
| # flagging_button.click(lambda: (gr.update(value="Flagged")), outputs=flagging_button) | |
| # fast_track_input_region_image.change(lambda: (gr.update(value="Flag")), outputs=flagging_button) | |