test docker

Dockerfile

@@ -33,4 +33,4 @@ WORKDIR $HOME/app
 # Copy the current directory contents into the container at $HOME/app setting the owner to the user
 COPY --chown=user . $HOME/app
 
-CMD ["python", "app.py"]
+CMD ["python", "app/app.py"]

app.py → app/app.py

@@ -6,10 +6,11 @@ import gradio as gr
 from helper.examples.examples import DemoImages
 from helper.gradio_config import css, js, theme
 from helper.text import TextAbout, TextApp, TextHowTo, TextRiksarkivet, TextRoadmap
-from src.htr_pipeline.gradio_backend import CustomTrack, FastTrack, SingletonModelLoader
+from src.htr_pipeline.gradio_backend import CustomTrack, SingletonModelLoader
+
+from .htr_tool import htr_tool_tab
 
 model_loader = SingletonModelLoader()
-fast_track = FastTrack(model_loader)
 custom_track = CustomTrack(model_loader)
 images_for_demo = DemoImages()
 
@@ -18,67 +19,7 @@ with gr.Blocks(title="HTR Riksarkivet", theme=theme, css=css) as demo:
 
     with gr.Tabs():
         with gr.Tab("HTR Tool"):
-            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=3,
-                                )
-
-                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_tool_tab.render()
 
         with gr.Tab("Stepwise HTR Tool"):
             with gr.Tabs():
@@ -394,29 +335,6 @@ with gr.Blocks(title="HTR Riksarkivet", theme=theme, css=css) as demo:
                     with gr.Row():
                         gr.Markdown(TextRiksarkivet.riksarkivet)
 
-    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",
-    )
-
-    # fast_track_input_region_image.change(
-    #     fn=lambda: (gr.Accordion.update(open=False)),
-    #     outputs=[fast_example_accord],
-    # )
-
-    # input_region_image.change(
-    #     fn=lambda: (gr.Accordion.update(open=False)),
-    #     outputs=[example_accord],
-    # )
-
     # 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)

app/htr_tool.py

@@ -0,0 +1,84 @@
+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=3,
+                        )
+
+        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",
+    )

src/htr_pipeline/inferencer.py

@@ -92,7 +92,10 @@ class Inferencer:
 
             if visualize:
                 result_viz = self.seg_model.visualize(
-                    inputs=[image], preds=[result_tl_clean], return_vis=True, no_save_vis=True
+                    inputs=[image],
+                    preds=[result_tl_clean],
+                    return_vis=True,
+                    no_save_vis=True,
                 )[0]
             else:
                 result_viz = None