remove login button bug

app/main.py

@@ -23,7 +23,9 @@ LANG_CHOICES = ["ENG", "SWE"]
 
 with gr.Blocks(title="HTRflow", theme=theme, css=css) as demo:
     with gr.Row():
-        local_language = gr.BrowserState(default_value="ENG", storage_key="selected_language")
+        local_language = gr.BrowserState(
+            default_value="ENG", storage_key="selected_language"
+        )
         main_language = gr.State(value="ENG")
 
         with gr.Column(scale=1):
@@ -94,4 +96,4 @@ with gr.Blocks(title="HTRflow", theme=theme, css=css) as demo:
 demo.queue()
 
 if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7861, enable_monitoring=False)
+    demo.launch(server_name="0.0.0.0", server_port=7862, enable_monitoring=False)

app/plot_viewer.py

@@ -0,0 +1,200 @@
+import xml.etree.ElementTree as ET
+from io import BytesIO
+
+import cv2
+import gradio as gr
+import numpy as np
+import requests
+from PIL import Image
+
+
+def parse_alto_xml(xml_file):
+    """Parse the ALTO XML file to extract polygons and text content for each TextLine."""
+    tree = ET.parse(xml_file)
+    root = tree.getroot()
+    ns = {"alto": "http://www.loc.gov/standards/alto/ns-v4#"}
+
+    annotations = []
+    transcriptions = {}
+
+    for text_block in root.findall(".//alto:TextBlock", ns):
+        for text_line in text_block.findall("alto:TextLine", ns):
+            shape = text_line.find("alto:Shape", ns)
+
+            if shape is not None:
+                polygon = shape.find("alto:Polygon", ns)
+                if polygon is not None:
+                    polygon_points = polygon.attrib["POINTS"]
+                    points = [
+                        tuple(map(int, point.split(",")))
+                        for point in polygon_points.split()
+                    ]
+            else:
+                hpos = int(text_line.attrib["HPOS"])
+                vpos = int(text_line.attrib["VPOS"])
+                width = int(text_line.attrib["WIDTH"])
+                height = int(text_line.attrib["HEIGHT"])
+                points = [
+                    (hpos, vpos),
+                    (hpos + width, vpos),
+                    (hpos + width, vpos + height),
+                    (hpos, vpos + height),
+                ]
+
+            content = " ".join(
+                [
+                    string.attrib["CONTENT"]
+                    for string in text_line.findall("alto:String", ns)
+                ]
+            )
+            label = text_line.attrib["ID"]
+
+            annotations.append((points, label))
+            transcriptions[label] = content
+
+    text_area_content = "\n".join(transcriptions[label] for label in transcriptions)
+
+    return annotations, transcriptions, text_area_content
+
+
+def visualize_polygons_on_image(
+    image, annotations, alpha=0.5, include_reading_order=False
+):
+    """Visualize polygons on the image with an optional reading order overlay."""
+    overlay = image.copy()
+    for _, (polygon, label) in enumerate(annotations):
+        color = (
+            np.random.randint(0, 255),
+            np.random.randint(0, 255),
+            np.random.randint(0, 255),
+        )
+        cv2.fillPoly(overlay, [np.array(polygon, dtype=np.int32)], color)
+
+        if include_reading_order:
+            centroid = np.mean(np.array(polygon), axis=0).astype(int)
+            cv2.putText(
+                overlay,
+                str(label),
+                tuple(centroid),
+                cv2.FONT_HERSHEY_SIMPLEX,
+                0.5,
+                (0, 0, 0),
+                1,
+                cv2.LINE_AA,
+            )
+
+    return cv2.addWeighted(overlay, alpha, image, 1 - alpha, 0)
+
+
+def visualize(
+    xml_file, image_source, image_id, uploaded_image, include_reading_order=False
+):
+    if image_source == "Use IIIF image":
+        if not image_id:
+            raise gr.Error("Please enter an Image ID.")
+        image_url = f"https://iiifintern.ra.se/arkis!{image_id}/full/max/0/default.jpg"
+        response = requests.get(image_url)
+        if response.status_code != 200:
+            raise gr.Error(f"Failed to download image from {image_url}")
+        image = np.array(Image.open(BytesIO(response.content)))
+    else:
+        if uploaded_image is None:
+            raise gr.Error("Please upload an image.")
+        image = uploaded_image
+
+    annotations, transcriptions, text_area_content = parse_alto_xml(xml_file)
+    annotated_image = visualize_polygons_on_image(
+        image, annotations, include_reading_order=include_reading_order
+    )
+
+    return annotated_image, annotations, transcriptions, text_area_content
+
+
+def get_transcription_from_coords(annotations, transcriptions, evt: gr.SelectData):
+    """Get the transcription for the polygon clicked in the annotated image."""
+    x, y = evt.index[0], evt.index[1]
+    for points, label in annotations:
+        polygon = np.array(points, dtype=np.int32)
+        if cv2.pointPolygonTest(polygon, (x, y), False) >= 0:
+            return transcriptions.get(label, "No transcription available.")
+    return "No transcription available."
+
+
+with gr.Blocks(title="XML Visualization App") as app:
+    with gr.Tab("Visualize"):
+        annotations_state = gr.State()
+        transcriptions_state = gr.State()
+
+        with gr.Row():
+            with gr.Column():
+                xml_input = gr.File(label="Upload ALTO XML File", file_types=[".xml"])
+            with gr.Column():
+                image_source = gr.Radio(
+                    choices=["Use IIIF image", "Upload your own image"],
+                    label="Image Source",
+                    value="Use IIIF image",
+                )
+                image_id_input = gr.Textbox(
+                    label="Image ID",
+                    placeholder="Enter image ID (e.g., 30003365_00001)",
+                    visible=True,
+                )
+                image_upload = gr.Image(
+                    label="Upload Image", type="numpy", visible=False
+                )
+                include_reading_order_input = gr.Checkbox(label="Include Reading Order")
+                process_button = gr.Button("Visualize Alto", scale=0, variant="primary")
+
+        def update_image_source(choice):
+            if choice == "Use IIIF image":
+                return [gr.update(visible=True), gr.update(visible=False)]
+            else:
+                return [gr.update(visible=False), gr.update(visible=True)]
+
+        image_source.change(
+            update_image_source,
+            inputs=image_source,
+            outputs=[image_id_input, image_upload],
+        )
+
+        with gr.Row():
+            with gr.Column(scale=3):
+                annotated_image_output = gr.Image(
+                    label="Annotated Image", interactive=True
+                )
+            with gr.Column(scale=2):
+                transcription_output = gr.TextArea(
+                    label="Transcription",
+                    interactive=False,
+                    show_copy_button=True,
+                    lines=30,
+                )
+                transcription_selected = gr.Textbox(
+                    label="Selected Polygon", interactive=False, show_copy_button=True
+                )
+
+        process_button.click(
+            visualize,
+            inputs=[
+                xml_input,
+                image_source,
+                image_id_input,
+                image_upload,
+                include_reading_order_input,
+            ],
+            outputs=[
+                annotated_image_output,
+                annotations_state,
+                transcriptions_state,
+                transcription_output,
+            ],
+        )
+
+        annotated_image_output.select(
+            get_transcription_from_coords,
+            inputs=[annotations_state, transcriptions_state],
+            outputs=transcription_selected,
+        )
+
+app.queue()
+app.launch()

app/tabs/adv_htrflow_tab.py

@@ -6,7 +6,13 @@ with gr.Blocks() as adv_htrflow_pipeline:
     with gr.Row(variant="panel"):
         with gr.Column(scale=2):
             image_mask2 = gr.ImageEditor(
-                label="Uploaded image", interactive=True, layers=False, eraser=False, brush=False, height=400
+                label="Uploaded image",
+                interactive=True,
+                layers=False,
+                eraser=False,
+                brush=False,
+                height=500,
+                canvas_size=(300, 300),
             )
 
             image_mask = gr.Gallery(
@@ -20,12 +26,14 @@ with gr.Blocks() as adv_htrflow_pipeline:
 
             with gr.Group():
                 with gr.Row(visible=True) as yaml_pipeline:
-                    with gr.Accordion(label="Insert Yaml", open=False):
+                    with gr.Accordion(label="Insert Yaml here:", open=True):
                         custom_template_yaml = gr.Code(
                             value="Paste your custom pipeline here",
                             language="yaml",
                             label="yaml",
+                            # show_label=False,
                             interactive=True,
+                            lines=3,
                         )
                     gr.Checkbox(value=True, label="Batch", container=True, scale=0)
 

app/tabs/data_explorer_tab.py

@@ -2,22 +2,27 @@ import gradio as gr
 
 
 def display_dataset(dataset_repo):
-    return gr.HTML(f"""<iframe
+    return gr.HTML(
+        f"""<iframe
     src="https://huggingface.co/datasets/{dataset_repo}/embed/viewer/default/train"
     frameborder="0"
     width="100%"
     height="700px"
-></iframe>""")
+></iframe>"""
+    )
 
 
 with gr.Blocks() as data_explorer:
     with gr.Row(variant="panel"):
         with gr.Column(scale=0, min_width=160):
             input_datasets_path = gr.Textbox(
-                label="HF datasets", placeholder="Gabriel/linkoping", scale=0, container=False
+                label="HF datasets",
+                placeholder="Gabriel/linkoping",
+                scale=0,
+                container=False,
             )
             view_dataset = gr.Button("View dataseet", variant="primary", scale=0)
-            gr.LoginButton("Login to HF", variant="secondary", scale=0)
+            # gr.LoginButton("Login to HF", variant="secondary", scale=0)
         with gr.Column():
             iframe_output = gr.HTML()
 

pyproject.toml

@@ -17,9 +17,8 @@ classifiers = [
 requires-python = ">=3.10,<3.13"
 
 dependencies = [
-    "torch==2.0.1",
     "htrflow==0.1.3",
-    "gradio[oauth]>=5.11.0",
+    "gradio>=5.11.0",
     "datasets>=3.2.0",
     "pandas>=2.2.3",
     "jinja2>=3.1.4",