daemon: Remove birdnet_miner and call birdnet_output_to_sql at each new model execution
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@ -3,8 +3,9 @@
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- Add docker compose port
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- Improve install script
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- Add base uninstall script (need deeper work)
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- Add ttyd for systemd logging
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## v0.0.1-rc
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## v0.0.1-rc (2022-08-18)
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- Integrate BirdNET-Analyzer as submodule
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- Add birdnet_recording service
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@ -129,7 +129,7 @@ sudo mv /composer.phar /usr/local/bin/composer
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```bash
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cd www
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composer install
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composer install --no-dev --prefer-dist --optimize-autoloader
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```
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### Install nodejs and npm
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@ -147,7 +147,7 @@ nvm use 16
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```
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```bash
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sudo dnf install npm
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sudo apt-get install npm
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```
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```bash
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@ -3,9 +3,7 @@ set -e
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DEBUG=${DEBUG:-1}
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debug() {
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if [ $DEBUG -eq 1 ]; then
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echo "$1"
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fi
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[[ $DEBUG -eq 1 ]] && echo "$@"
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}
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config_filepath="./config/birdnet.conf"
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@ -64,7 +62,9 @@ check_prerequisites() {
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# Get array of audio chunks to be processed
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get_chunk_list() {
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find "${CHUNK_FOLDER}/in" -type f -name '*.wav' -exec basename {} \; ! -size 0 | sort
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chunk_list=($(ls ${CHUNK_FOLDER}/in))
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echo "${chunk_list}"
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# find "${CHUNK_FOLDER}/in" -type f -name '*.wav' -exec basename {} \; ! -size 0 | sort
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}
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# Perform audio chunk analysis on one chunk
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@ -75,13 +75,22 @@ analyze_chunk() {
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mkdir -p "$output_dir"
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date=$(echo $chunk_name | cut -d'_' -f2)
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week=$(./daemon/weekof.sh $date)
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$PYTHON_EXECUTABLE ./analyzer/analyze.py --i $chunk_path --o "$output_dir/model.out.csv" --lat $LATITUDE --lon $LONGITUDE --week $week --min_conf $CONFIDENCE --threads 4 --rtype csv
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if [[ ! -z "${THREADS}" ]]; then
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threads="--threads ${THREADS}"
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else
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threads=""
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fi
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$PYTHON_EXECUTABLE ./analyzer/analyze.py --i $chunk_path --o "$output_dir/model.out.csv" --lat $LATITUDE --lon $LONGITUDE --week $week --min_conf $CONFIDENCE $threads --rtype csv
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debug "Model output written to $output_dir/model.out.csv"
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bash ./daemon/birdnet_output_to_sql.sh "$output_dir/model.out.csv"
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debug "Dumped to SQL database"
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}
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# Perform audio chunk analysis on all recorded chunks
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analyze_chunks() {
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for chunk_name in $(get_chunk_list); do
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local chunks
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chunks="${1}"
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for chunk_name in "${chunks}"; do
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if [[ -f "${CHUNK_FOLDER}/out/$chunk_name.d/model.out.csv" ]]; then
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debug "Skipping $chunk_name, as it has already been analyzed"
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else
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@ -98,4 +107,4 @@ check_prerequisites
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chunks=$(get_chunk_list)
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# Analyze all chunks in working directory
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analyze_chunks $chunks
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analyze_chunks "$chunks"
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@ -1,15 +1,13 @@
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#! /usr/bin/env bash
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# Extract observations from a model output folder
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# Extract observations from a model output file into SQL database
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#
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DEBUG=${DEBUG:-1}
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set -e
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# set -x
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DEBUG=${DEBUG:-1}
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debug() {
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if [ $DEBUG -eq 1 ]; then
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echo "$1"
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fi
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[[ $DEBUG -eq 1 ]] && echo "$@"
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}
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# Load bash library to deal with BirdNET-stream database
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@ -18,16 +16,6 @@ source ./daemon/database/scripts/database.sh
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# Load config
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source ./config/birdnet.conf
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# Check config
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if [[ -z ${CHUNK_FOLDER} ]]; then
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echo "CHUNK_FOLDER is not set"
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exit 1
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else
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if [[ ! -d ${CHUNK_FOLDER}/out ]]; then
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echo "CHUNK_FOLDER does not exist: ${CHUNK_FOLDER}/out"
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echo "Cannot extract observations."
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exit 1
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fi
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fi
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if [[ -z ${LATITUDE} ]]; then
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echo "LATITUDE is not set"
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@ -39,10 +27,6 @@ if [[ -z ${LONGITUDE} ]]; then
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exit 1
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fi
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model_outputs() {
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ls ${CHUNK_FOLDER}/out/*/model.out.csv
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}
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source_wav() {
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model_output_path=$1
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model_output_dir=$(dirname $model_output_path)
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@ -107,13 +91,6 @@ save_observations() {
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done
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}
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main() {
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# # Remove all junk observations
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# ./daemon/birdnet_clean.sh
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# Get model outputs
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for model_output in $(model_outputs); do
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save_observations $model_output
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done
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}
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model_output_path="$1"
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main
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save_observations $model_output_path
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@ -6,66 +6,79 @@ import matplotlib.pyplot as plt
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from matplotlib.colors import LogNorm
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import seaborn as sns
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from datetime import datetime
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import os
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import glob
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CONFIG = {
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"readings": 10,
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"palette": "Greens",
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"db": "./var/db.sqlite",
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"date": datetime.now().strftime("%Y-%m-%d")
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# "date": "2022-08-15"
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"date": datetime.now().strftime("%Y-%m-%d"),
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"charts_dir": "./var/charts"
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}
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db = sqlite3.connect(CONFIG['db'])
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db = None
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df = pd.read_sql_query("""SELECT common_name, date, location_id, confidence
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def get_database():
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global db
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if db is None:
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db = sqlite3.connect(CONFIG["db"])
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return db
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def chart(date):
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db = get_database()
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df = pd.read_sql_query(f"""SELECT common_name, date, location_id, confidence
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FROM observation
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INNER JOIN taxon
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ON observation.taxon_id = taxon.taxon_id""", db)
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df['date'] = pd.to_datetime(df['date'])
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df['hour'] = df['date'].dt.hour
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df['date'] = df['date'].dt.date
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df['date'] = df['date'].astype(str)
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df_on_date = df[df['date'] == CONFIG['date']]
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ON observation.taxon_id = taxon.taxon_id
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WHERE STRFTIME("%Y-%m-%d", `date`) = '{date}'""", db)
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df['date'] = pd.to_datetime(df['date'])
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df['hour'] = df['date'].dt.hour
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df['date'] = df['date'].dt.date
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df['date'] = df['date'].astype(str)
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df_on_date = df[df['date'] == date]
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top_on_date = (df_on_date['common_name'].value_counts()[:CONFIG['readings']])
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if top_on_date.empty:
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print("No observations on {}".format(CONFIG['date']))
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exit()
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top_on_date = (df_on_date['common_name'].value_counts()[:CONFIG['readings']])
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if top_on_date.empty:
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print("No observations on {}".format(date))
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return
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else:
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print(f"Found observations on {date}")
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df_top_on_date = df_on_date[df_on_date['common_name'].isin(top_on_date.index)]
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df_top_on_date = df_on_date[df_on_date['common_name'].isin(top_on_date.index)]
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# Create a figure with 2 subplots
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fig, axs = plt.subplots(1, 2, figsize=(20, 5), gridspec_kw=dict(
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# Create a figure with 2 subplots
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fig, axs = plt.subplots(1, 2, figsize=(20, 5), gridspec_kw=dict(
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width_ratios=[2, 6]))
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plt.subplots_adjust(left=None, bottom=None, right=None,
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plt.subplots_adjust(left=None, bottom=None, right=None,
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top=None, wspace=0, hspace=0)
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# Get species frequencies
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frequencies_order = pd.value_counts(df_top_on_date['common_name']).iloc[:CONFIG['readings']].index
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# Get min max confidences
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confidence_minmax = df_top_on_date.groupby('common_name')['confidence'].max()
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confidence_minmax = confidence_minmax.reindex(frequencies_order)
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# Norm values for color palette
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norm = plt.Normalize(confidence_minmax.values.min(),
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# Get species frequencies
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frequencies_order = pd.value_counts(df_top_on_date['common_name']).iloc[:CONFIG['readings']].index
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# Get min max confidences
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confidence_minmax = df_top_on_date.groupby('common_name')['confidence'].max()
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confidence_minmax = confidence_minmax.reindex(frequencies_order)
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# Norm values for color palette
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norm = plt.Normalize(confidence_minmax.values.min(),
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confidence_minmax.values.max())
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colors = plt.cm.Greens(norm(confidence_minmax))
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plot = sns.countplot(y='common_name', data=df_top_on_date, palette=colors, order=frequencies_order, ax=axs[0])
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colors = plt.cm.Greens(norm(confidence_minmax))
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plot = sns.countplot(y='common_name', data=df_top_on_date, palette=colors, order=frequencies_order, ax=axs[0])
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plot.set(ylabel=None)
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plot.set(xlabel="Detections")
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plot.set(ylabel=None)
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plot.set(xlabel="Detections")
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heat = pd.crosstab(df_top_on_date['common_name'], df_top_on_date['hour'])
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# Order heatmap Birds by frequency of occurrance
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heat.index = pd.CategoricalIndex(heat.index, categories=frequencies_order)
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heat.sort_index(level=0, inplace=True)
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heat = pd.crosstab(df_top_on_date['common_name'], df_top_on_date['hour'])
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# Order heatmap Birds by frequency of occurrance
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heat.index = pd.CategoricalIndex(heat.index, categories=frequencies_order)
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heat.sort_index(level=0, inplace=True)
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hours_in_day = pd.Series(data=range(0, 24))
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heat_frame = pd.DataFrame(data=0, index=heat.index, columns=hours_in_day)
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heat = (heat + heat_frame).fillna(0)
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hours_in_day = pd.Series(data=range(0, 24))
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heat_frame = pd.DataFrame(data=0, index=heat.index, columns=hours_in_day)
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heat = (heat + heat_frame).fillna(0)
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# Generate heatmap plot
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plot = sns.heatmap(
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# Generate heatmap plot
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plot = sns.heatmap(
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heat,
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norm=LogNorm(),
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annot=True,
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@ -80,16 +93,32 @@ plot = sns.heatmap(
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linecolor="Grey",
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ax=axs[1],
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yticklabels=False)
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plot.set_xticklabels(plot.get_xticklabels(), rotation=0, size=7)
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plot.set_xticklabels(plot.get_xticklabels(), rotation=0, size=7)
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for _, spine in plot.spines.items():
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for _, spine in plot.spines.items():
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spine.set_visible(True)
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plot.set(ylabel=None)
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plot.set(xlabel="Hour of day")
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plt.suptitle(f"Top {CONFIG['readings']} species on {CONFIG['date']}", fontsize=14)
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plt.text(15, 11, f"(Updated on {datetime.now().strftime('%Y/%m-%d %H:%M')})")
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plt.savefig(f"./var/charts/chart_{CONFIG['date']}.png", dpi=300)
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plt.close()
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plot.set(ylabel=None)
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plot.set(xlabel="Hour of day")
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plt.suptitle(f"Top {CONFIG['readings']} species on {CONFIG['date']}", fontsize=14)
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plt.text(15, 11, f"(Updated on {datetime.now().strftime('%Y/%m-%d %H:%M')})")
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plt.savefig(f"./var/charts/chart_{CONFIG['date']}.png", dpi=300)
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print(f"Plot for {date} saved.")
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plt.close()
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db.close()
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def main():
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done_charts = glob.glob(f"{CONFIG['charts_dir']}/*.png")
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last_modified = max(done_charts, key=os.path.getctime)
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last_modified_date = last_modified.split("_")[-1].split(".")[0]
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missing_dates = pd.date_range(start=last_modified_date, end=CONFIG['date'], freq='D')
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print(missing_dates)
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for missing_date in missing_dates:
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date = missing_date.strftime("%Y-%m-%d")
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chart(date)
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chart(CONFIG['date'])
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if db is not None:
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db.close()
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print("Done.")
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if __name__ == "__main__":
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main()
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@ -1,13 +0,0 @@
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[Unit]
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Description=BirdNET-stream miner service
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[Service]
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Type=simple
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User=<USER>
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Group=<GROUP>
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WorkingDirectory=<DIR>
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ExecStart=bash ./daemon/birdnet_miner.sh
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RemainAfterExit=yes
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[Install]
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WantedBy=multi-user.target
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@ -1,9 +0,0 @@
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[Unit]
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Description=BirdNET-stream miner Timer
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[Timer]
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OnCalendar=*:0/15
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Unit=birdnet_miner.service
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[Install]
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WantedBy=timers.target
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@ -34,10 +34,13 @@ Then, create your dotenv file and populate it with your own configuration (for i
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cp .env.example .env
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```
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Then, run docker-compose:
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You may need to adapt the listening ports of the services or other configuration parameters.
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In general all variables stated with ${VARIABLE:-default} inside [../docker-compose.yml](../docker-compose.yml) can be override in the .env file using `VARIABLE=value`.
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Once that is done, you can build and start docker services:
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```bash
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# Build image (first time only)
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# Build images (first time only)
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docker compose build
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# Run
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docker compose up # add `-d`, to run in background
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@ -67,7 +67,7 @@ install_birdnetstream_services() {
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DIR="$WORKDIR"
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cd "$WORKDIR"
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debug "Setting up BirdNET stream systemd services"
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services="birdnet_recording.service birdnet_analyzis.service birdnet_miner.timer birdnet_miner.service birdnet_plotter.service birdnet_plotter.timer"
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services="birdnet_recording.service birdnet_analyzis.service birdnet_plotter.service birdnet_plotter.timer"
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read -r -a services_array <<<"$services"
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for service in ${services_array[@]}; do
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sudo cp "daemon/systemd/templates/$service" "/etc/systemd/system/"
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@ -78,7 +78,7 @@ install_birdnetstream_services() {
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done
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sudo sed -i "s|<VENV>|$WORKDIR/$PYTHON_VENV|g" "/etc/systemd/system/birdnet_plotter.service"
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sudo systemctl daemon-reload
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enabled_services="birdnet_recording.service birdnet_analyzis.service birdnet_miner.timer birdnet_plotter.timer"
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enabled_services="birdnet_recording.service birdnet_analyzis.service birdnet_plotter.timer"
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read -r -a services_array <<<"$services"
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for service in ${services_array[@]}; do
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debug "Enabling $service"
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@ -163,7 +163,7 @@ setup_http_server() {
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fi
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debug "Enable birdnet.lan domain"
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sudo ln -s /etc/nginx/sites-available/birdnet-stream.conf /etc/nginx/sites-enabled/birdnet-stream.conf
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debug "Info: Please edit /etc/nginx/sites-available/birdnet-stream.conf to set the correct server name and paths"
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debug "INFO: Please edit /etc/nginx/sites-available/birdnet-stream.conf to set the correct server name and paths"
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debug "Setup nginx variables the best way possible"
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sudo sed -i "s|<SYMFONY_PUBLIC>|$WORKDIR/www/public/|g" /etc/nginx/sites-available/birdnet-stream.conf
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sudo sed -i "s|<RECORDS_DIR>|$CHUNK_FOLDER/out|g" /etc/nginx/sites-available/birdnet-stream.conf
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@ -38,3 +38,12 @@ uninstall_webapp() {
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sudo unlink /etc/nginx/sites-enabled/birdnet-stream.conf
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sudo systemctl restart nginx
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}
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main() {
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echo "WARNING: This will remove all BirdNET-stream related files and services. \
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Note that it may forget some special configuration."
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uninstall_webapp
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uninstall_birdnet_services
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}
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main
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@ -25,11 +25,15 @@ class HomeController extends AbstractController
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* @Route("", name="home")
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* @Route("/{_locale<%app.supported_locales%>}/", name="home_i18n")
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*/
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public function index()
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public function index(Request $request)
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{
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$date = $request->get("on");
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if ($date == null) {
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$date = date("Y-m-d");
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}
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return $this->render('index.html.twig', [
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"stats" => $this->get_stats(),
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"charts" => $this->last_chart_generated(),
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"stats" => $this->get_stats($date),
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"charts" => $this->last_chart_generated($date),
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]);
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}
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@ -42,11 +46,12 @@ class HomeController extends AbstractController
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return $this->render('about/index.html.twig', []);
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}
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private function get_stats()
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private function get_stats($date)
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{
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$stats = array();
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$stats["most-recorded-species"] = $this->get_most_recorded_species();
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$stats["last-detected-species"] = $this->get_last_recorded_species();
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$stats["number-of-species-detected"] = $this->get_number_of_species_detected($date);
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return $stats;
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}
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@ -86,6 +91,27 @@ class HomeController extends AbstractController
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return $species;
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}
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||||
private function get_number_of_species_detected($date)
|
||||
{
|
||||
$count = 0;
|
||||
$sql = "SELECT COUNT(`taxon_id`) AS contact_count
|
||||
FROM `observation`
|
||||
WHERE STRFTIME('%Y-%m-%d', `date`) = :date
|
||||
GROUP BY `taxon_id`";
|
||||
try {
|
||||
$stmt = $this->connection->prepare($sql);
|
||||
$stmt->bindValue(":date", $date);
|
||||
$result = $stmt->executeQuery();
|
||||
$output = $result->fetchAllAssociative();
|
||||
if ($output != null) {
|
||||
$count = $output[0]["contact_count"];
|
||||
}
|
||||
} catch (\Exception $e) {
|
||||
$this->logger->error($e->getMessage());
|
||||
}
|
||||
return $count;
|
||||
}
|
||||
|
||||
private function last_chart_generated()
|
||||
{
|
||||
$files = glob($this->getParameter('kernel.project_dir') . '/../var/charts/*.png');
|
||||
|
||||
@ -1,49 +1,77 @@
|
||||
<div id="stats">
|
||||
<h2>{{ "Quick Stats" | trans }}</h2>
|
||||
<h2>
|
||||
{{ 'Quick Stats'|trans }}
|
||||
</h2>
|
||||
<ul>
|
||||
<li class="most-recorded-species">
|
||||
{{ "Most recorded species" | trans }}:
|
||||
{% if stats["most-recorded-species"] is defined and stats["most-recorded-species"]|length > 0 %}
|
||||
<li class="stat">
|
||||
{{ 'Most recorded species'|trans }}:{% if
|
||||
stats['most-recorded-species'] is defined
|
||||
and (stats['most-recorded-species']|length) > 0 %}
|
||||
<span class="scientific-name">
|
||||
{{ stats["most-recorded-species"]["scientific_name"] }}
|
||||
{{ stats['most-recorded-species']['scientific_name'] }}
|
||||
</span>
|
||||
(<span class="common_name">{{ stats["most-recorded-species"]["common_name"] }}</span>)
|
||||
{{ "with" | trans }}
|
||||
(<span class="common_name">
|
||||
{{ stats['most-recorded-species']['common_name'] }}
|
||||
</span>)
|
||||
{{ 'with'|trans }}
|
||||
<span class="observation-count">
|
||||
{{ stats["most-recorded-species"]["contact_count"] }}
|
||||
{{ stats['most-recorded-species']['contact_count'] }}
|
||||
</span>
|
||||
{{ "contacts" | trans }}.
|
||||
{{ 'contacts'|trans }}.
|
||||
{% else %}
|
||||
{{ "No species in database." | trans }}
|
||||
{{ 'No species in database.'|trans }}
|
||||
{% endif %}
|
||||
</li>
|
||||
<li class="last-recorded-species">
|
||||
{{ "Last detected species" | trans }}:
|
||||
{% if stats["last-detected-species"] is defined and stats["last-detected-species"]|length > 0 %}
|
||||
<li class="stat">
|
||||
{{ 'Last detected species'|trans }}:{% if
|
||||
stats['last-detected-species'] is defined
|
||||
and (stats['last-detected-species']|length) > 0 %}
|
||||
<span class="scientific-name">
|
||||
{{ stats["last-detected-species"]["scientific_name"] }}
|
||||
{{ stats['last-detected-species']['scientific_name'] }}
|
||||
</span>
|
||||
(<span class="common_name">{{ stats["last-detected-species"]["common_name"] }}</span>)
|
||||
{{ "with" | trans }}
|
||||
(<span class="common_name">
|
||||
{{ stats['last-detected-species']['common_name'] }}
|
||||
</span>)
|
||||
{{ 'with'|trans }}
|
||||
<span class="confidence">
|
||||
{{ stats["last-detected-species"]["confidence"] }}
|
||||
{{ stats['last-detected-species']['confidence'] }}
|
||||
</span>
|
||||
{{ "AI confidence" | trans }}
|
||||
{{ 'AI confidence'|trans }}
|
||||
<span class="datetime">
|
||||
{% set date = stats["last-detected-species"]["date"] %}
|
||||
{% if date | date("Y-m-d") == "now" | date("Y-m-d") %}
|
||||
{{ "today" | trans }}
|
||||
{% set date = stats['last-detected-species']['date'] %}
|
||||
{% if (date|date('Y-m-d')) == ('now'|date('Y-m-d')) %}
|
||||
{{ 'today'|trans }}
|
||||
{% else %}
|
||||
{{ "on" | trans }}
|
||||
{{ date | format_datetime("full", "none") }}
|
||||
{% endif %}
|
||||
at
|
||||
<span class="time">
|
||||
{{ date | date("H:i") }}
|
||||
</span>
|
||||
{{ 'on'|trans }}
|
||||
{{ date|format_datetime('full', 'none') }}
|
||||
{% endif %}at
|
||||
<span class="time">{{ date|date('H:i') }}</span>
|
||||
</span>.
|
||||
{% else %}
|
||||
{{ "No species in database" | trans }}
|
||||
{{ 'No species in database'|trans }}
|
||||
{% endif %}
|
||||
</li>
|
||||
<li class="stat">
|
||||
{% set today = 'now'|date('Y-m-d') %}
|
||||
{% set date = app.request.get('on') %}
|
||||
{% if
|
||||
stats['number-of-species-detected'] is defined
|
||||
and stats['number-of-species-detected'] > 0 %}
|
||||
{% if today == date %}
|
||||
{{ 'Number of species detected today: '|trans }}
|
||||
{% else %}
|
||||
{{ 'Number of species detected on '|trans }}
|
||||
{{ date|format_datetime('full', 'none') }}:
|
||||
{% endif %}
|
||||
<span>{{ stats['number-of-species-detected'] }}</span>.
|
||||
{% else %}
|
||||
{# {{ 'No species detected today'|trans }} #}
|
||||
{% if today == date %}
|
||||
{{ 'No species detected today.'|trans }}
|
||||
{% else %}
|
||||
{{ 'No species detected on '|trans }}
|
||||
{{ date|format_datetime('full', 'none') }}
|
||||
{% endif %}
|
||||
{% endif %}
|
||||
</li>
|
||||
</ul>
|
||||
|
||||
Loading…
Reference in New Issue
Block a user