Merge branch 'BirdNET-pi-main' into New-UI-API

README.md

@@ -63,7 +63,7 @@ Currently listening in these countries . . . that I know of . . .
 
 ## Features
 * **24/7 recording and automatic identification** of bird songs, chirps, and peeps using BirdNET machine learning
-* **Automatic extraction and cataloguing** of bird sounds
+* **Automatic extraction and cataloguing** of bird clips from full-length recordings
 * **Tools to visualize your recorded bird data** and analyze trends
 * **Live audio stream and spectrogram**
 * **Automatic disk space management** that periodically purges old audio files

scripts/config.php

@@ -418,7 +418,7 @@ function runProcess() {
       <dt>BirdNET_6K_GLOBAL_MODEL (2020)</dt><br>
       <dd id="ddnewline">This is the BirdNET-Lite model, with bird sound recognition for more than 6,000 species worldwide. This is the default option and will generally work very for people in most of the world.</dd>
     <br>
-      <dt>BirdNET_GLOBAL_3K_V2.3_Model_FP16 (2022)</dt><br>
+      <dt>BirdNET_GLOBAL_3K_V2.3_Model_FP16 (2023)</dt><br>
       <dd id="ddnewline">This is the BirdNET-Analyzer model, a newer work-in-progress project with aims to improve on the BirdNET-Lite model. Currently it only supports about 3,500 species worldwide, meaning for some regions (North America, Europe, Australia) it will usually outperform the BirdNET-Lite model, but for other regions it will be worse.</dd><br>
       <dt>[ In-depth technical write-up on the models <a target="_blank" href="https://github.com/mcguirepr89/BirdNET-Pi/wiki/BirdNET-Pi:-some-theory-on-classification-&-some-practical-hints">here</a> ]</dt>
       </dl>

scripts/daily_plot.py

@@ -81,24 +81,25 @@ plot.set(xlabel="Detections")
 
 
 # Generate crosstab matrix for heatmap plot
-
 heat = pd.crosstab(df_plt_top10_today['Com_Name'], df_plt_top10_today['Hour of Day'])
+
 # Order heatmap Birds by frequency of occurrance
 heat.index = pd.CategoricalIndex(heat.index, categories=freq_order)
 heat.sort_index(level=0, inplace=True)
 
-
 hours_in_day = pd.Series(data=range(0, 24))
 heat_frame = pd.DataFrame(data=0, index=heat.index, columns=hours_in_day)
 heat = (heat + heat_frame).fillna(0)
 
-# Generatie heatmap plot
+# Get current hour
+current_hour = now.hour
+
+# Generate heatmap plot
 plot = sns.heatmap(
     heat,
     norm=LogNorm(),
     annot=True,
-    annot_kws={
+    annot_kws={"fontsize": 7},
-        "fontsize": 7},
     fmt="g",
     cmap=pal,
     square=False,
@@ -106,9 +107,18 @@ plot = sns.heatmap(
     linewidths=0.5,
     linecolor="Grey",
     ax=axs[1],
-    yticklabels=False)
+    yticklabels=False
+)
+
+# Set color and weight of tick label for current hour
+for label in plot.get_xticklabels():
+    if int(label.get_text()) == current_hour:
+        label.set_color('yellow')
+
 plot.set_xticklabels(plot.get_xticklabels(), rotation=0, size=7)
 
+
+
 # Set heatmap border
 for _, spine in plot.spines.items():
     spine.set_visible(True)

scripts/email_template

@@ -4,7 +4,9 @@ Below is the information I would like to use to request a BirdWeather ID
 %0A%0A
 Latitude={{ LATITUDE }}%0A
 Longitude={{ LONGITUDE }}%0A
-Location= [ Create a location name ]%0A
+City= [ City ]%0A
+State= [ State ]%0A
+Country= [ Country ]%0A
 %0A%0A
 Thank you so much!%0A
 [ Your Name Here ]

scripts/server.py

@@ -585,7 +585,7 @@ def handle_client(conn, addr):
                                         post_scientificName = "\"scientificName\": \"" + entry[0].split('_')[0] + "\","
 
                                         if model == "BirdNET_GLOBAL_3K_V2.3_Model_FP16":
-                                            post_algorithm = "\"algorithm\": " + "\"2p2\"" + ","
+                                            post_algorithm = "\"algorithm\": " + "\"2p3\"" + ","
                                         else:
                                             post_algorithm = "\"algorithm\": " + "\"alpha\"" + ","