General fixes - Code quality, Configurable Config Directory, Update Docker

.github/workflows/format.yml

@@ -0,0 +1,31 @@
+name: Format code
+
+on:
+  push:
+    branches: [ master ]
+
+jobs:
+  format:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+      - name: Format code with black
+        run: |
+          pip install black
+          black .
+      - name: Sort imports with isort
+        run: |
+          pip install isort
+          isort .
+      - name: Remove unused imports with autoflake
+        run: |
+          pip install autoflake
+          autoflake --in-place --remove-all-unused-imports --remove-unused-variables --recursive .
+      - name: Commit changes
+        uses: EndBug/add-and-commit@v4
+        with:
+          author_name: ${{ github.actor }}
+          author_email: ${{ github.actor }}@users.noreply.github.com
+          message: "Format code with black"
+          add: "."
+          branch: ${{ github.ref }}

Dockerfile

@@ -1,4 +1,4 @@
-FROM python:3.8
+FROM python:3.9
 RUN apt-get update && apt-get install ffmpeg libsm6 libxext6  -y
 COPY requirements.txt .
 RUN pip install -r requirements.txt
@@ -7,6 +7,7 @@ COPY birdnames.db .
 COPY speciesid.py .
 COPY webui.py .
 COPY queries.py .
+COPY util.py .
 COPY templates/ ./templates/
 COPY static/ ./static/
 

README.md

@@ -1,4 +1,7 @@
 # Who's At My Feeder?
+
+This app acts as sidecar to [Frigate](https://frigate.video/) to identify the species of the birds that Frigate detects. It is using the bird species classifier model found here: https://tfhub.dev/google/lite-model/aiy/vision/classifier/birds_V1/3
+
 ## What's New?
 I'm just about to push a significant update. This will require you to...
 * Delete you current speciesid.db database. If you are attached to that data, just move it somewhere else
@@ -17,9 +20,6 @@ field is currently limited to 20 characters
 
 ![screenshot](screenshot2.jpg)
 
-This app acts as sidecar to [Frigate](https://frigate.video/) to identify the species of
-the birds that Frigate detects. It is using the bird species classifier model found here: https://tfhub.dev/google/lite-model/aiy/vision/classifier/birds_V1/3
-
 **Prequisites**
 
 1. A working & Accessible Frigate Installation with at least 1 Camera configured

config/config.yml

@@ -10,7 +10,10 @@ frigate:
   object: bird
 classification:
   model: model.tflite
+  name_database: birdnames.db
   threshold: 0.7
+database:
+  path: "./data/speciesid.db"
 webui:
   port: 7766
   host: 0.0.0.0

queries.py

@@ -1,61 +1,69 @@
 import sqlite3
 from collections import defaultdict
-from datetime import datetime
 
-DBPATH = './data/speciesid.db'
-NAMEDBPATH = './birdnames.db'
+from util import load_config
+
+config = load_config()
+DBPATH = config["database"]["path"]
+NAMEDBPATH = config["classification"]["name_database"]
 
 
 def get_common_name(scientific_name):
     conn = sqlite3.connect(NAMEDBPATH)
     cursor = conn.cursor()
 
-    cursor.execute("SELECT common_name FROM birdnames WHERE scientific_name = ?", (scientific_name,))
+    cursor.execute(
+        "SELECT common_name FROM birdnames WHERE scientific_name = ?",
+        (scientific_name,),
+    )
     result = cursor.fetchone()
 
     conn.close()
 
     if result:
         return result[0]
     else:
-        print ("No common name for: " + scientific_name, flush=True)
+        print("No common name for: " + scientific_name, flush=True)
         return "No common name found."
 
 
 def recent_detections(num_detections):
     conn = sqlite3.connect(DBPATH)
     cursor = conn.cursor()
 
-    cursor.execute("SELECT * FROM detections ORDER BY detection_time DESC LIMIT ?", (num_detections,))
+    cursor.execute(
+        "SELECT * FROM detections ORDER BY detection_time DESC LIMIT ?",
+        (num_detections,),
+    )
     results = cursor.fetchall()
 
     conn.close()
 
     formatted_results = []
     for result in results:
         detection = {
-            'id': result[0],
-            'detection_time': result[1],
-            'detection_index': result[2],
-            'score': result[3],
-            'display_name': result[4],
-            'category_name': result[5],
-            'frigate_event': result[6],
-            'camera_name': result[7],
-            'common_name': get_common_name(result[4])
+            "id": result[0],
+            "detection_time": result[1],
+            "detection_index": result[2],
+            "score": result[3],
+            "display_name": result[4],
+            "category_name": result[5],
+            "frigate_event": result[6],
+            "camera_name": result[7],
+            "common_name": get_common_name(result[4]),
         }
         formatted_results.append(detection)
 
     return formatted_results
 
 
 def get_daily_summary(date):
-    date_str = date.strftime('%Y-%m-%d')
+    date_str = date.strftime("%Y-%m-%d")
     conn = sqlite3.connect(DBPATH)
     conn.row_factory = sqlite3.Row
     cursor = conn.cursor()
 
-    query = '''  
+    query = """  
         SELECT display_name,  
                COUNT(*) AS total_detections,  
                STRFTIME('%H', detection_time) AS hour,  
@@ -67,24 +75,28 @@ def get_daily_summary(date):
         ) AS subquery  
         GROUP BY display_name, hour  
         ORDER BY total_detections DESC, display_name, hour  
-    '''
+    """
 
     cursor.execute(query, (date_str,))
     rows = cursor.fetchall()
 
-    summary = defaultdict(lambda: {
-        'scientific_name': '',
-        'common_name': '',
-        'total_detections': 0,
-        'hourly_detections': [0] * 24
-    })
+    summary = defaultdict(
+        lambda: {
+            "scientific_name": "",
+            "common_name": "",
+            "total_detections": 0,
+            "hourly_detections": [0] * 24,
+        }
+    )
 
     for row in rows:
-        display_name = row['display_name']
-        summary[display_name]['scientific_name'] = display_name
-        summary[display_name]['common_name'] = get_common_name(display_name)
-        summary[display_name]['total_detections'] += row['hourly_detections']
-        summary[display_name]['hourly_detections'][int(row['hour'])] = row['hourly_detections']
+        display_name = row["display_name"]
+        summary[display_name]["scientific_name"] = display_name
+        summary[display_name]["common_name"] = get_common_name(display_name)
+        summary[display_name]["total_detections"] += row["hourly_detections"]
+        summary[display_name]["hourly_detections"][int(row["hour"])] = row[
+            "hourly_detections"
+        ]
 
     conn.close()
     return dict(summary)
@@ -96,22 +108,26 @@ def get_records_for_date_hour(date, hour):
     cursor = conn.cursor()
 
     # The SQL query to fetch records for the given date and hour, sorted by detection_time
-    query = '''    
+    query = """    
         SELECT *    
         FROM detections    
         WHERE strftime('%Y-%m-%d', detection_time) = ? AND strftime('%H', detection_time) = ?    
         ORDER BY detection_time    
-    '''
+    """
 
     cursor.execute(query, (date, str(hour).zfill(2)))
     records = cursor.fetchall()
 
     # Append the common name for each record
     result = []
     for record in records:
-        common_name = get_common_name(record['display_name'])  # Access the field by name
+        common_name = get_common_name(
+            record["display_name"]
+        )  # Access the field by name
         record_dict = dict(record)  # Convert the record to a dictionary
-        record_dict['common_name'] = common_name  # Add the 'common_name' key to the record dictionary
+        record_dict[
+            "common_name"
+        ] = common_name  # Add the 'common_name' key to the record dictionary
         result.append(record_dict)
 
     conn.close()
@@ -125,22 +141,26 @@ def get_records_for_scientific_name_and_date(scientific_name, date):
     cursor = conn.cursor()
 
     # The SQL query to fetch records for the given display_name and date, sorted by detection_time
-    query = '''    
+    query = """    
         SELECT *    
         FROM detections    
         WHERE display_name = ? AND strftime('%Y-%m-%d', detection_time) = ?    
         ORDER BY detection_time    
-    '''
+    """
 
     cursor.execute(query, (scientific_name, date))
     records = cursor.fetchall()
 
     # Append the common name for each record
     result = []
     for record in records:
-        common_name = get_common_name(record['display_name'])  # Access the field by name
+        common_name = get_common_name(
+            record["display_name"]
+        )  # Access the field by name
         record_dict = dict(record)  # Convert the record to a dictionary
-        record_dict['common_name'] = common_name  # Add the 'common_name' key to the record dictionary
+        record_dict[
+            "common_name"
+        ] = common_name  # Add the 'common_name' key to the record dictionary
         result.append(record_dict)
 
     conn.close()