Add info boxes to tabs

birdnet_analyzer/gui/assets/gui.css

@@ -46,4 +46,20 @@ footer {
     resize: none !important;
     text-overflow: ellipsis !important;
     text-align: left !important;
+}
+
+.info-accordion-dark {
+    background-color: #2980b9;
+}
+
+.info-accordion {
+    background-color: rgba(17, 38, 224, 0.6);
+}
+
+.info-accordion p {
+    color: white;
+}
+
+.info-accordion button {
+    color: white;
 }

birdnet_analyzer/gui/embeddings.py

@@ -117,6 +117,11 @@ def build_embeddings_tab() -> gu.TAB_BUILDER_RESULT:
         input_directory_state = gr.State()
         db_directory_state = gr.State()
 
+        gu.info_box(
+            description=loc.localize("embeddings-tab-info-text"),
+            title=loc.localize("embeddings-tab-info-title"),
+        )
+
         def select_directory_to_state_and_tb(current, state_key=None):
             path = (
                 gu.select_directory(collect_files=False, state_key=state_key)
@@ -324,7 +329,7 @@ def select_file_output_directory_and_update_tb(current):
 
         progress_plot = gr.Plot(show_label=False)
         start_btn = gr.Button(
-            loc.localize("embeddings-tab-start-button-label"), variant="huggingface"
+            loc.localize("embeddings-tab-start-button-label"), variant="primary"
         )
 
         start_btn.click(

birdnet_analyzer/gui/evaluation.py

@@ -387,6 +387,11 @@ def update_selections(
         prediction_files_state = gr.State()
         plot_name_state = gr.State()
 
+        gu.info_box(
+            description=loc.localize("eval-tab-info-text"),
+            title=loc.localize("eval-tab-info-title"),
+        )
+
         def get_selection_tables(directory):
             from pathlib import Path
 
@@ -668,7 +673,7 @@ def select_directory_on_empty():
 
         calculate_button = gr.Button(
             loc.localize("eval-tab-calculate-metrics-button-label"),
-            variant="huggingface",
+            variant="primary",
         )
 
         with gr.Column(visible=False) as action_col:

birdnet_analyzer/gui/multi_file.py

@@ -111,6 +111,11 @@ def build_multi_analysis_tab() -> gu.TAB_BUILDER_RESULT:
         input_directory_state = gr.State()
         output_directory_predict_state = gr.State()
 
+        gu.info_box(
+            description=loc.localize("multi-tab-info-text"),
+            title=loc.localize("multi-tab-info-title"),
+        )
+
         with gr.Group(), gr.Row(equal_height=True):
             select_directory_btn = gr.Button(
                 loc.localize("multi-tab-input-selection-button-label"),
@@ -222,7 +227,7 @@ def select_directory_wrapper():
 
         bs_number, producers_number, workers_number = gu.computing_settings()
         start_batch_analysis_btn = gr.Button(
-            loc.localize("analyze-start-button-label"), variant="huggingface"
+            loc.localize("analyze-start-button-label"), variant="primary"
         )
         result_grid = gr.List(headers=[""])
         inputs = [

birdnet_analyzer/gui/review.py

@@ -148,6 +148,11 @@ def create_log_plot(positives, negatives, fig_num=None):
             }
         )
 
+        gu.info_box(
+            description=loc.localize("review-tab-info-text"),
+            title=loc.localize("review-tab-info-title"),
+        )
+
         select_directory_btn = gr.Button(
             loc.localize("review-tab-input-directory-button-label")
         )

birdnet_analyzer/gui/search.py

@@ -112,6 +112,11 @@ def build_search_tab() -> gu.TAB_BUILDER_RESULT:
         export_state = gr.State({})
         hidden_audio = gr.Audio(visible="hidden", autoplay=True, type="numpy")
 
+        gu.info_box(
+            description=loc.localize("embeddings-search-tab-info-text"),
+            title=loc.localize("embeddings-search-tab-info-title"),
+        )
+
         with gr.Row():
             with gr.Column():
                 with gr.Group(), gr.Row(equal_height=True):
@@ -236,7 +241,7 @@ def build_search_tab() -> gu.TAB_BUILDER_RESULT:
                 )
                 search_btn = gr.Button(
                     loc.localize("embeddings-search-start-button-label"),
-                    variant="huggingface",
+                    variant="primary",
                 )
 
             with gr.Column():

birdnet_analyzer/gui/segments.py

@@ -80,6 +80,11 @@ def build_segments_tab() -> gu.TAB_BUILDER_RESULT:
         result_directory_state = gr.State()
         output_directory_state = gr.State()
 
+        gu.info_box(
+            description=loc.localize("segments-tab-info-text"),
+            title=loc.localize("segments-tab-info-title"),
+        )
+
         def select_directory_to_state_and_tb(state_key):
             selection = gu.select_directory(collect_files=False, state_key=state_key)
             if selection:
@@ -244,7 +249,7 @@ def select_directory_to_state_and_tb(state_key):
             )
 
         extract_segments_btn = gr.Button(
-            loc.localize("segments-tab-extract-button-label"), variant="huggingface"
+            loc.localize("segments-tab-extract-button-label"), variant="primary"
         )
         result_grid = gr.List(headers=[""])
 

birdnet_analyzer/gui/single_file.py

@@ -185,7 +185,7 @@ def build_single_analysis_tab() -> gu.TAB_BUILDER_RESULT:
 
         single_file_analyze = gr.Button(
             loc.localize("analyze-start-button-label"),
-            variant="huggingface",
+            variant="primary",
             interactive=False,
         )
 
@@ -304,7 +304,7 @@ def try_generate_spectrogram(audio_path, generate_spectrogram):
             try_generate_spectrogram,
             inputs=[audio_path_state, generate_spectrogram_cb],
             outputs=[spectrogram_group, spectrogram_output],
-            show_progress_on=generate_spectrogram_cb
+            show_progress_on=generate_spectrogram_cb,
         )
 
         select_file_button.click(

birdnet_analyzer/gui/species.py

@@ -31,6 +31,11 @@ def build_species_tab() -> gu.TAB_BUILDER_RESULT:
     with gr.Tab(loc.localize("species-tab-title")) as species_tab:
         output_directory_state = gr.State()
 
+        gu.info_box(
+            description=loc.localize("species-tab-info-text"),
+            title=loc.localize("species-tab-info-title"),
+        )
+
         with gr.Group(), gr.Row(equal_height=True):
             select_directory_btn = gr.Button(
                 loc.localize("species-tab-select-output-directory-button-label"),
@@ -86,7 +91,7 @@ def select_directory_and_update_tb(name_tb):
         locale = gu.locale()
 
         start_btn = gr.Button(
-            loc.localize("species-tab-start-button-label"), variant="huggingface"
+            loc.localize("species-tab-start-button-label"), variant="primary"
         )
         start_btn.click(
             run_species_list,

birdnet_analyzer/gui/train.py

@@ -253,6 +253,11 @@ def build_train_tab() -> gu.TAB_BUILDER_RESULT:
         output_directory_state = gr.State()
         test_data_dir_state = gr.State()
 
+        gu.info_box(
+            description=loc.localize("training-tab-info-text"),
+            title=loc.localize("training-tab-info-title"),
+        )
+
         with gr.Group(), gr.Row(equal_height=True):
             select_directory_btn = gr.Button(
                 loc.localize("training-tab-input-selection-button-label"),
@@ -808,7 +813,7 @@ def on_autotune_change(value):
         )
         start_training_button = gr.Button(
             loc.localize("training-tab-start-training-button-label"),
-            variant="huggingface",
+            variant="primary",
         )
 
         def train_and_show_metrics(*args):

birdnet_analyzer/gui/utils.py

@@ -8,6 +8,7 @@
 import warnings
 from collections.abc import Callable
 from contextlib import suppress
+from html import escape
 from typing import Literal, cast, get_args
 
 import gradio as gr
@@ -1017,6 +1018,22 @@ def computing_settings():
     return bs_number, producers_number, workers_number
 
 
+def info_box(description: str, title="Info") -> gr.HTML:
+    title = escape(title)
+    description = escape(description)
+
+    with gr.Accordion(
+        title,
+        elem_classes="info-accordion-dark"
+        if settings.theme() == "dark"
+        else "info-accordion",
+        open=False,
+    ) as c:
+        gr.Markdown(description)
+
+        return c
+
+
 def slider_to_value(value: float):
     return max(0.1, 1.0 / (value * -1)) if value < 0 else max(1.0, float(value))
 
@@ -1111,4 +1128,4 @@ def update_plots(*args):
             ctypes.sizeof(wintypes.BOOL),
         )
 
-    webview.start(private_mode=False)
+    webview.start(private_mode=False, debug=True)

birdnet_analyzer/lang/de.json

@@ -389,5 +389,21 @@
     "validation-no-valid-classifier-name": "Bitte geben Sie einen gültigen Namen für den Klassifikator an.",
     "validation-no-valid-epoch-number": "Bitte geben Sie eine gültige Anzahl von Epochen an.",
     "validation-no-valid-frequency": "Bitte geben Sie eine gültige Frequenz an",
-    "validation-no-valid-learning-rate": "Bitte geben Sie eine gültige Lernrate an."
+    "validation-no-valid-learning-rate": "Bitte geben Sie eine gültige Lernrate an.",
+    "multi-tab-info-text": "Analyze all audio files in a directory recursively. Select an input folder, review the sample list, choose an output location and result formats, adjust settings if needed, then start the batch run.",
+    "multi-tab-info-title": "Info",
+    "embeddings-search-tab-info-text": "Search an embeddings database with a query sample. Select the database and audio root, choose a query clip, tune the search options, then review or export the closest matches.",
+    "embeddings-search-tab-info-title": "Info",
+    "embeddings-tab-info-text": "Build an embeddings database from a directory of audio files. Choose the source audio and database location, adjust settings if needed, then generate the database for later search and review.",
+    "embeddings-tab-info-title": "Info",
+    "eval-tab-info-text": "Compare prediction files against annotations. Upload both sets, confirm the column mapping, calculate the metrics, then inspect plots and export the result tables if needed.",
+    "eval-tab-info-title": "Info",
+    "review-tab-info-text": "Review extracted segments one species at a time. Select a directory, step through the clips, mark each item as positive or negative, and use the history and regression plot to track progress.",
+    "review-tab-info-title": "Info",
+    "segments-tab-info-text": "Extract segments from analysis results. Select the source audio, result files, and output folder, set the collection filters, then create a segment set for review or training.",
+    "segments-tab-info-title": "Info",
+    "species-tab-info-text": "Generate a species list for a location. Choose where to save the file, set the coordinates and seasonal filters, then export the list for later analysis.",
+    "species-tab-info-title": "Info",
+    "training-tab-info-text": "Train a custom classifier from labeled folders. Select the training data and output location, optionally add test data and preprocessing settings, then run training and review the metrics.",
+    "training-tab-info-title": "Info"
 }

birdnet_analyzer/lang/en.json

@@ -163,6 +163,8 @@
     "multi-tab-additional-column-week-label": "Week",
     "multi-tab-additional-columns-checkbox-info": "Adds additional columns to the output. \"Start (s)\", \"End (s)\", \"Scientific name\", \"Common name\", \"Confidence\", \"File\" are already included.",
     "multi-tab-additional-columns-checkbox-label": "Additional columns for CSV",
+    "multi-tab-info-text": "Analyze all audio files in a directory recursively. Select an input folder, review the sample list, choose an output location and result formats, adjust settings if needed, then start the batch run.",
+    "multi-tab-info-title": "Info",
     "multi-tab-input-selection-button-label": "Select input directory (recursive)",
     "multi-tab-input-selection-textbox-placeholder": "No input directory selected",
     "multi-tab-more-files-label": "more...",
@@ -389,5 +391,19 @@
     "validation-no-valid-classifier-name": "Please enter a valid name for the classifier.",
     "validation-no-valid-epoch-number": "Please enter a valid number of epochs.",
     "validation-no-valid-frequency": "Please enter a valid frequency in",
-    "validation-no-valid-learning-rate": "Please enter a valid learning rate."
+    "validation-no-valid-learning-rate": "Please enter a valid learning rate.",
+    "embeddings-search-tab-info-text": "Search an embeddings database with a query sample. Select the database and audio root, choose a query clip, tune the search options, then review or export the closest matches.",
+    "embeddings-search-tab-info-title": "Info",
+    "embeddings-tab-info-text": "Build an embeddings database from a directory of audio files. Choose the source audio and database location, adjust settings if needed, then generate the database for later search and review.",
+    "embeddings-tab-info-title": "Info",
+    "eval-tab-info-text": "Compare prediction files against annotations. Upload both sets, confirm the column mapping, calculate the metrics, then inspect plots and export the result tables if needed.",
+    "eval-tab-info-title": "Info",
+    "review-tab-info-text": "Review extracted segments one species at a time. Select a directory, step through the clips, mark each item as positive or negative, and use the history and regression plot to track progress.",
+    "review-tab-info-title": "Info",
+    "segments-tab-info-text": "Extract segments from analysis results. Select the source audio, result files, and output folder, set the collection filters, then create a segment set for review or training.",
+    "segments-tab-info-title": "Info",
+    "species-tab-info-text": "Generate a species list for a location. Choose where to save the file, set the coordinates and seasonal filters, then export the list for later analysis.",
+    "species-tab-info-title": "Info",
+    "training-tab-info-text": "Train a custom classifier from labeled folders. Select the training data and output location, optionally add test data and preprocessing settings, then run training and review the metrics.",
+    "training-tab-info-title": "Info"
 }

birdnet_analyzer/lang/fi.json

@@ -389,5 +389,21 @@
     "validation-no-valid-classifier-name": "Anna kelvollinen nimi luokittelijalle.",
     "validation-no-valid-epoch-number": "Anna kelvollinen aikakausien määrä.",
     "validation-no-valid-frequency": "Anna kelvollinen taajuus",
-    "validation-no-valid-learning-rate": "Anna kelvollinen oppimistahti."
+    "validation-no-valid-learning-rate": "Anna kelvollinen oppimistahti.",
+    "multi-tab-info-text": "Analyze all audio files in a directory recursively. Select an input folder, review the sample list, choose an output location and result formats, adjust settings if needed, then start the batch run.",
+    "multi-tab-info-title": "Info",
+    "embeddings-search-tab-info-text": "Search an embeddings database with a query sample. Select the database and audio root, choose a query clip, tune the search options, then review or export the closest matches.",
+    "embeddings-search-tab-info-title": "Info",
+    "embeddings-tab-info-text": "Build an embeddings database from a directory of audio files. Choose the source audio and database location, adjust settings if needed, then generate the database for later search and review.",
+    "embeddings-tab-info-title": "Info",
+    "eval-tab-info-text": "Compare prediction files against annotations. Upload both sets, confirm the column mapping, calculate the metrics, then inspect plots and export the result tables if needed.",
+    "eval-tab-info-title": "Info",
+    "review-tab-info-text": "Review extracted segments one species at a time. Select a directory, step through the clips, mark each item as positive or negative, and use the history and regression plot to track progress.",
+    "review-tab-info-title": "Info",
+    "segments-tab-info-text": "Extract segments from analysis results. Select the source audio, result files, and output folder, set the collection filters, then create a segment set for review or training.",
+    "segments-tab-info-title": "Info",
+    "species-tab-info-text": "Generate a species list for a location. Choose where to save the file, set the coordinates and seasonal filters, then export the list for later analysis.",
+    "species-tab-info-title": "Info",
+    "training-tab-info-text": "Train a custom classifier from labeled folders. Select the training data and output location, optionally add test data and preprocessing settings, then run training and review the metrics.",
+    "training-tab-info-title": "Info"
 }

birdnet_analyzer/lang/fr.json

@@ -389,5 +389,21 @@
     "validation-no-valid-classifier-name": "Veuillez saisir un nom valide pour le classificateur.",
     "validation-no-valid-epoch-number": "Veuillez saisir un nombre valide d'époques.",
     "validation-no-valid-frequency": "Veuillez saisir une fréquence valide dans",
-    "validation-no-valid-learning-rate": "Veuillez saisir un taux d'apprentissage valide."
+    "validation-no-valid-learning-rate": "Veuillez saisir un taux d'apprentissage valide.",
+    "multi-tab-info-text": "Analyze all audio files in a directory recursively. Select an input folder, review the sample list, choose an output location and result formats, adjust settings if needed, then start the batch run.",
+    "multi-tab-info-title": "Info",
+    "embeddings-search-tab-info-text": "Search an embeddings database with a query sample. Select the database and audio root, choose a query clip, tune the search options, then review or export the closest matches.",
+    "embeddings-search-tab-info-title": "Info",
+    "embeddings-tab-info-text": "Build an embeddings database from a directory of audio files. Choose the source audio and database location, adjust settings if needed, then generate the database for later search and review.",
+    "embeddings-tab-info-title": "Info",
+    "eval-tab-info-text": "Compare prediction files against annotations. Upload both sets, confirm the column mapping, calculate the metrics, then inspect plots and export the result tables if needed.",
+    "eval-tab-info-title": "Info",
+    "review-tab-info-text": "Review extracted segments one species at a time. Select a directory, step through the clips, mark each item as positive or negative, and use the history and regression plot to track progress.",
+    "review-tab-info-title": "Info",
+    "segments-tab-info-text": "Extract segments from analysis results. Select the source audio, result files, and output folder, set the collection filters, then create a segment set for review or training.",
+    "segments-tab-info-title": "Info",
+    "species-tab-info-text": "Generate a species list for a location. Choose where to save the file, set the coordinates and seasonal filters, then export the list for later analysis.",
+    "species-tab-info-title": "Info",
+    "training-tab-info-text": "Train a custom classifier from labeled folders. Select the training data and output location, optionally add test data and preprocessing settings, then run training and review the metrics.",
+    "training-tab-info-title": "Info"
 }