Add dockerfile

.dockerignore

@@ -0,0 +1,3 @@
+venv
+docker/
+.idea

README.md

@@ -1,5 +1,15 @@
 # CVZone MQTT Tracker
 
+## Run with docker
+```
+docker run \
+  --device /dev/video0 \
+  -e MQTT_ADDRESS="10.1.1.100" \
+  -e MQTT_PORT="1883" \
+  -e MQTT_CLIENT_ID="cvzone_tracker_01" \
+  -e MIN_FACE_SCORE="0.5" \
+  cvzone-mqtt-tracker:latest
+```
 
 ## Install on Raspberry Pi
 *Required*: Raspberry Pi OS 64-bit

docker/Dockerfile

@@ -0,0 +1,10 @@
+FROM python:3.7
+
+RUN apt-get update \
+    && apt-get install -y python3-opencv
+
+WORKDIR /app
+COPY . /app
+RUN pip install -r requirements.txt
+
+CMD python main.py

main.py

@@ -1,8 +1,16 @@
+import os
 from tracker import Tracker
 
+mqtt_address = os.environ.get("MQTT_ADDRESS", "10.1.1.100")
+mqtt_port = int(os.environ.get("MQTT_PORT", 1883))
+mqtt_client_id = os.environ.get("MQTT_CLIENT_ID", "cvzone_tracker_01")
+min_face_score = float(os.environ.get("MIN_FACE_SCORE", 0.5))
+
 tracker = Tracker(
-    mqtt_address="10.1.1.100",
+    mqtt_address=mqtt_address,
-    mqtt_client_id="cvzone_tracker_01",
+    mqtt_port=mqtt_port,
+    mqtt_client_id=mqtt_client_id,
+    min_face_score=min_face_score,
     show_img=False)
 
 while True:

requirements.txt

@@ -1,3 +1,5 @@
 cvzone==1.5.6
-mediapipe==0.8.10
+mediapipe==0.8.9.1
+opencv-contrib-python==4.5.5.64
+opencv-python==4.5.5.64
 paho-mqtt==1.6.1

requirements_rpi.txt

@@ -1,6 +0,0 @@
-cvzone==1.5.6
-mediapipe==0.8.9.1
-numpy==1.22.3
-opencv-contrib-python==4.5.5.64
-opencv-python==4.5.5.64
-paho-mqtt==1.6.1

tracker.py

@@ -7,9 +7,16 @@ from debounce import debounce
 
 
 class Tracker(object):
-    def __init__(self, mqtt_address="", mqtt_port=1883, mqtt_client_id="", show_img=False):
+    def __init__(
+            self,
+            mqtt_address="",
+            mqtt_port=1883,
+            mqtt_client_id="",
+            min_face_score=0.5,
+            show_img=False):
+
         self.show_img = show_img
-        self.min_face_score = 0.5
+        self.min_face_score = min_face_score
         self.cap = cv2.VideoCapture(0)
         self.face_detector = FaceDetector()
         self.img = None
@@ -56,8 +63,6 @@ class Tracker(object):
 
                 score = face_bboxs[0]["score"][0]
                 return score >= self.min_face_score
-        else:
-            print('Image not usable')
         return False
 
     def loop(self):