add favicon

app/content/main_sub_title.md

@@ -1,3 +1,3 @@
-<a href="https://riksarkivet.se">
-<img src="https://raw.githubusercontent.com/Borg93/Riksarkivet_docs/main/docs/assets/fav-removebg-preview.png" width="17%" align="left" margin-left="100" />
+<a href="https://huggingface.co/Riksarkivet">
+<img src="app/assets/images/fav-removebg-preview.png" width="17%" align="right" margin-right="100" />
 </a>

app/main.py

@@ -14,6 +14,7 @@ from app.tabs.templating import (
     TEMPLATE_YAML_FOLDER,
     template_output_yaml_code,
 )
+from gradio_modal import Modal
 
 from htrflow.models.huggingface.trocr import TrOCR
 
@@ -24,6 +25,7 @@ gr.set_static_paths(paths=[TEMPLATE_YAML_FOLDER])
 # TODO add colab
 # TDOO addd eexmaple for api
 
+
 def load_markdown(language, section, content_dir="app/content"):
     """Load markdown content from files."""
     if language is None:
@@ -37,10 +39,29 @@ def load_markdown(language, section, content_dir="app/content"):
     return f"## Content missing for {file_path} in {language}"
 
 
-with gr.Blocks(title="HTRflow", theme=theme, css=css) as demo:
+matomo = """
+<!-- Matomo Tag Manager -->
+<script>
+var _mtm = window._mtm = window._mtm || [];
+_mtm.push({'mtm.startTime': (new Date().getTime()), 'event': 'mtm.Start'});
+(function() {
+var d=document, g=d.createElement('script'), s=d.getElementsByTagName('script')[0];
+g.async=true; g.src='https://matomo.riksarkivet.se/js/container_pWJwXoXG.js';; s.parentNode.insertBefore(g,s);
+})();
+</script>
+<!-- End Matomo Tag Manager -->
+"""
+
+with gr.Blocks(title="HTRflow", theme=theme, css=css, head=matomo) as demo:
     with gr.Row():
         with gr.Column(scale=1):
-            pass
+            help_button = gr.Button("Help", scale=0)
+            with Modal(visible=False) as help_modal:
+                with gr.Tab("How to use App"):
+                    gr.Markdown("# How it works")
+                with gr.Tab("Contact"):
+                    pass
+
         with gr.Column(scale=2):
             gr.Markdown(load_markdown(None, "main_title"))
         with gr.Column(scale=1):
@@ -56,6 +77,10 @@ with gr.Blocks(title="HTRflow", theme=theme, css=css) as demo:
         with gr.Tab(label="Visualize Result") as tab_visualizer:
             visualizer.render()
 
+    @demo.load()
+    def inital_trocr_load():
+        TrOCR("Riksarkivet/trocr-base-handwritten-hist-swe-2")
+
     @demo.load()
     def inital_yaml_code():
         tmp_dir = "tmp/"
@@ -69,10 +94,6 @@ with gr.Blocks(title="HTRflow", theme=theme, css=css) as demo:
     def inital_yaml_code(template_output_yaml_code):
         return template_output_yaml_code
 
-    @demo.load()
-    def inital_trocr_load():
-        return TrOCR("Riksarkivet/trocr-base-handwritten-hist-swe-2")
-
     def sync_gradio_objects(input_value, state_value):
         """Synchronize the YAML state if there is a mismatch."""
         return input_value if input_value != state_value else gr.skip()
@@ -100,6 +121,7 @@ with gr.Blocks(title="HTRflow", theme=theme, css=css) as demo:
         fn=sync_gradio_object_state,
     )
 
+    help_button.click(lambda: Modal(visible=True), None, help_modal)
 
 demo.queue()
 
@@ -108,6 +130,5 @@ if __name__ == "__main__":
         server_name="0.0.0.0",
         server_port=7860,
         enable_monitoring=True,
-        ssr_mode=True
         # show_error=True,
     )

app/tabs/templating.py

@@ -70,7 +70,7 @@ with gr.Blocks() as templating_block:
             with gr.Row():
                 dropdown_selection_template = gr.Dropdown(
                     label="Choose template",
-                    info="template info",
+                    info="Choice a suitable template for your material",
                     value="Simple",
                     choices=["Simple", "Nested", "Custom"],
                     multiselect=False,

app/tabs/visualizer.py

@@ -38,27 +38,28 @@ def load_visualize_state_from_submit(col: Collection, progress):
                 continue
 
             if node.text_result:
-                recog_conf_values[i] = list(zip(
-                    node.text_result.texts,
-                    node.text_result.scores
-                ))
-
-        annotated_image = draw_polygons(
-            image=page_image,
-            polygons=line_polygons
-        )
+                recog_conf_values[i] = list(
+                    zip(node.text_result.texts, node.text_result.scores)
+                )
+
+        annotated_image = draw_polygons(image=page_image, polygons=line_polygons)
         annotated_page_node = np.clip(annotated_image, 0, 255).astype(np.uint8)
 
-        results.append({
-            "page_image": page_node,
-            "annotated_page_node": annotated_page_node,
-            "line_crops": line_crops,
-            "recog_conf_values": _convert_conf_values_to_df(recog_conf_values),
-        })
+        results.append(
+            {
+                "page_image": page_node,
+                "annotated_page_node": annotated_page_node,
+                "line_crops": line_crops,
+                "recog_conf_values": _convert_conf_values_to_df(recog_conf_values),
+            }
+        )
 
     return results
 
-def _convert_conf_values_to_df(conf_values: Dict[int, List[tuple[str, float]]]) -> pd.DataFrame:
+
+def _convert_conf_values_to_df(
+    conf_values: Dict[int, List[tuple[str, float]]]
+) -> pd.DataFrame:
     """Convert recognition confidence values to a pandas DataFrame."""
     return pd.DataFrame(
         [
@@ -68,6 +69,7 @@ def _convert_conf_values_to_df(conf_values: Dict[int, List[tuple[str, float]]])
         ]
     )
 
+
 with gr.Blocks() as visualizer:
     with gr.Column(variant="panel"):
         with gr.Row():
@@ -85,7 +87,7 @@ with gr.Blocks() as visualizer:
                 )
 
                 visualize_button = gr.Button(
-                    "Visualize", scale=0, min_width=200, variant="secondary"
+                    "Visualize", scale=0, min_width=200, variant="primary"
                 )
 
                 progress_bar = gr.Textbox(visible=False, show_label=False)
@@ -95,7 +97,7 @@ with gr.Blocks() as visualizer:
                     interactive=False,
                     preview=True,
                     label="Cropped Polygons",
-                    height=200,
+                    height=400,
                 )
                 df_for_cropped_images = gr.Dataframe(
                     label="Cropped Transcriptions",

pyproject.toml

@@ -23,6 +23,7 @@ dependencies = [
     "pandas>=2.2.3",
     "tqdm>=4.67.1",
     "pillow>=11.1.0",
+    "gradio-modal>=0.0.4",
 ]
 
 [project.urls]

uv.lock

@@ -678,6 +678,18 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/a6/3d/e05202dd42581c2a1e93c730d10a0ef45bc40921332c9aa0d6645bbf0e2b/gradio_client-1.5.4-py3-none-any.whl", hash = "sha256:ad38c9a6f7fc590e822627f5bf5685321a7822b8f1a88b76d00a0621a43162d6", size = 321364 },
 ]
 
+[[package]]
+name = "gradio-modal"
+version = "0.0.4"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "gradio" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/e2/fd/3b383f9ee8d60625e9e26871ba4adcacbedeab132041b94290758e02e543/gradio_modal-0.0.4.tar.gz", hash = "sha256:717ae699072a171648cfa1b84bc153be84e92d04e9ad58c1bc59af68ef332726", size = 1180812 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/05/3d/76f454de84ae1dccbf2b7023e933afb8dde5fdd89e9476786726ef770737/gradio_modal-0.0.4-py3-none-any.whl", hash = "sha256:d96e817d2e934d9e1b835b06474f45fd349b5ccea499d1536bfb4bd38f62dedb", size = 1106241 },
+]
+
 [[package]]
 name = "h11"
 version = "0.14.0"
@@ -719,6 +731,7 @@ source = { editable = "." }
 dependencies = [
     { name = "datasets" },
     { name = "gradio" },
+    { name = "gradio-modal" },
     { name = "htrflow" },
     { name = "pandas" },
     { name = "pillow" },
@@ -737,6 +750,7 @@ dev = [
 requires-dist = [
     { name = "datasets", specifier = ">=3.2.0" },
     { name = "gradio", specifier = ">=5.11.0" },
+    { name = "gradio-modal", specifier = ">=0.0.4" },
     { name = "htrflow", specifier = "==0.2.0" },
     { name = "pandas", specifier = ">=2.2.3" },
     { name = "pillow", specifier = ">=11.1.0" },
@@ -1342,7 +1356,6 @@ name = "nvidia-cublas-cu12"
 version = "12.4.5.8"
 source = { registry = "https://pypi.org/simple" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/7f/7f/7fbae15a3982dc9595e49ce0f19332423b260045d0a6afe93cdbe2f1f624/nvidia_cublas_cu12-12.4.5.8-py3-none-manylinux2014_aarch64.whl", hash = "sha256:0f8aa1706812e00b9f19dfe0cdb3999b092ccb8ca168c0db5b8ea712456fd9b3", size = 363333771 },
     { url = "https://files.pythonhosted.org/packages/ae/71/1c91302526c45ab494c23f61c7a84aa568b8c1f9d196efa5993957faf906/nvidia_cublas_cu12-12.4.5.8-py3-none-manylinux2014_x86_64.whl", hash = "sha256:2fc8da60df463fdefa81e323eef2e36489e1c94335b5358bcb38360adf75ac9b", size = 363438805 },
 ]
 
@@ -1351,7 +1364,6 @@ name = "nvidia-cuda-cupti-cu12"
 version = "12.4.127"
 source = { registry = "https://pypi.org/simple" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/93/b5/9fb3d00386d3361b03874246190dfec7b206fd74e6e287b26a8fcb359d95/nvidia_cuda_cupti_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:79279b35cf6f91da114182a5ce1864997fd52294a87a16179ce275773799458a", size = 12354556 },
     { url = "https://files.pythonhosted.org/packages/67/42/f4f60238e8194a3106d06a058d494b18e006c10bb2b915655bd9f6ea4cb1/nvidia_cuda_cupti_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = "sha256:9dec60f5ac126f7bb551c055072b69d85392b13311fcc1bcda2202d172df30fb", size = 13813957 },
 ]
 
@@ -1360,7 +1372,6 @@ name = "nvidia-cuda-nvrtc-cu12"
 version = "12.4.127"
 source = { registry = "https://pypi.org/simple" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/77/aa/083b01c427e963ad0b314040565ea396f914349914c298556484f799e61b/nvidia_cuda_nvrtc_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:0eedf14185e04b76aa05b1fea04133e59f465b6f960c0cbf4e37c3cb6b0ea198", size = 24133372 },
     { url = "https://files.pythonhosted.org/packages/2c/14/91ae57cd4db3f9ef7aa99f4019cfa8d54cb4caa7e00975df6467e9725a9f/nvidia_cuda_nvrtc_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = "sha256:a178759ebb095827bd30ef56598ec182b85547f1508941a3d560eb7ea1fbf338", size = 24640306 },
 ]
 
@@ -1369,7 +1380,6 @@ name = "nvidia-cuda-runtime-cu12"
 version = "12.4.127"
 source = { registry = "https://pypi.org/simple" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/a1/aa/b656d755f474e2084971e9a297def515938d56b466ab39624012070cb773/nvidia_cuda_runtime_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:961fe0e2e716a2a1d967aab7caee97512f71767f852f67432d572e36cb3a11f3", size = 894177 },
     { url = "https://files.pythonhosted.org/packages/ea/27/1795d86fe88ef397885f2e580ac37628ed058a92ed2c39dc8eac3adf0619/nvidia_cuda_runtime_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = "sha256:64403288fa2136ee8e467cdc9c9427e0434110899d07c779f25b5c068934faa5", size = 883737 },
 ]
 
@@ -1392,7 +1402,6 @@ dependencies = [
     { name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux' and sys_platform != 'win32')" },
 ]
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/7a/8a/0e728f749baca3fbeffad762738276e5df60851958be7783af121a7221e7/nvidia_cufft_cu12-11.2.1.3-py3-none-manylinux2014_aarch64.whl", hash = "sha256:5dad8008fc7f92f5ddfa2101430917ce2ffacd86824914c82e28990ad7f00399", size = 211422548 },
     { url = "https://files.pythonhosted.org/packages/27/94/3266821f65b92b3138631e9c8e7fe1fb513804ac934485a8d05776e1dd43/nvidia_cufft_cu12-11.2.1.3-py3-none-manylinux2014_x86_64.whl", hash = "sha256:f083fc24912aa410be21fa16d157fed2055dab1cc4b6934a0e03cba69eb242b9", size = 211459117 },
 ]
 
@@ -1401,7 +1410,6 @@ name = "nvidia-curand-cu12"
 version = "10.3.5.147"
 source = { registry = "https://pypi.org/simple" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/80/9c/a79180e4d70995fdf030c6946991d0171555c6edf95c265c6b2bf7011112/nvidia_curand_cu12-10.3.5.147-py3-none-manylinux2014_aarch64.whl", hash = "sha256:1f173f09e3e3c76ab084aba0de819c49e56614feae5c12f69883f4ae9bb5fad9", size = 56314811 },
     { url = "https://files.pythonhosted.org/packages/8a/6d/44ad094874c6f1b9c654f8ed939590bdc408349f137f9b98a3a23ccec411/nvidia_curand_cu12-10.3.5.147-py3-none-manylinux2014_x86_64.whl", hash = "sha256:a88f583d4e0bb643c49743469964103aa59f7f708d862c3ddb0fc07f851e3b8b", size = 56305206 },
 ]
 
@@ -1415,7 +1423,6 @@ dependencies = [
     { name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux' and sys_platform != 'win32')" },
 ]
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/46/6b/a5c33cf16af09166845345275c34ad2190944bcc6026797a39f8e0a282e0/nvidia_cusolver_cu12-11.6.1.9-py3-none-manylinux2014_aarch64.whl", hash = "sha256:d338f155f174f90724bbde3758b7ac375a70ce8e706d70b018dd3375545fc84e", size = 127634111 },
     { url = "https://files.pythonhosted.org/packages/3a/e1/5b9089a4b2a4790dfdea8b3a006052cfecff58139d5a4e34cb1a51df8d6f/nvidia_cusolver_cu12-11.6.1.9-py3-none-manylinux2014_x86_64.whl", hash = "sha256:19e33fa442bcfd085b3086c4ebf7e8debc07cfe01e11513cc6d332fd918ac260", size = 127936057 },
 ]
 
@@ -1427,7 +1434,6 @@ dependencies = [
     { name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux' and sys_platform != 'win32')" },
 ]
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/96/a9/c0d2f83a53d40a4a41be14cea6a0bf9e668ffcf8b004bd65633f433050c0/nvidia_cusparse_cu12-12.3.1.170-py3-none-manylinux2014_aarch64.whl", hash = "sha256:9d32f62896231ebe0480efd8a7f702e143c98cfaa0e8a76df3386c1ba2b54df3", size = 207381987 },
     { url = "https://files.pythonhosted.org/packages/db/f7/97a9ea26ed4bbbfc2d470994b8b4f338ef663be97b8f677519ac195e113d/nvidia_cusparse_cu12-12.3.1.170-py3-none-manylinux2014_x86_64.whl", hash = "sha256:ea4f11a2904e2a8dc4b1833cc1b5181cde564edd0d5cd33e3c168eff2d1863f1", size = 207454763 },
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@@ -1444,7 +1450,6 @@ name = "nvidia-nvjitlink-cu12"
 version = "12.4.127"
 source = { registry = "https://pypi.org/simple" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/02/45/239d52c05074898a80a900f49b1615d81c07fceadd5ad6c4f86a987c0bc4/nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:4abe7fef64914ccfa909bc2ba39739670ecc9e820c83ccc7a6ed414122599b83", size = 20552510 },
     { url = "https://files.pythonhosted.org/packages/ff/ff/847841bacfbefc97a00036e0fce5a0f086b640756dc38caea5e1bb002655/nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = "sha256:06b3b9b25bf3f8af351d664978ca26a16d2c5127dbd53c0497e28d1fb9611d57", size = 21066810 },
 ]
 
@@ -1453,7 +1458,6 @@ name = "nvidia-nvtx-cu12"
 version = "12.4.127"
 source = { registry = "https://pypi.org/simple" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/06/39/471f581edbb7804b39e8063d92fc8305bdc7a80ae5c07dbe6ea5c50d14a5/nvidia_nvtx_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:7959ad635db13edf4fc65c06a6e9f9e55fc2f92596db928d169c0bb031e88ef3", size = 100417 },
     { url = "https://files.pythonhosted.org/packages/87/20/199b8713428322a2f22b722c62b8cc278cc53dffa9705d744484b5035ee9/nvidia_nvtx_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = "sha256:781e950d9b9f60d8241ccea575b32f5105a5baf4c2351cab5256a24869f12a1a", size = 99144 },
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