Made some more progress on Docker Compose

docker-compose.yml

@@ -6,11 +6,11 @@ services:
         container_name: bridge-wyze
         restart: unless-stopped
         image: mrlt8/wyze-bridge:latest
-        # ports:
+        ports:
-        #     - 1935:1935 # RTMP
+            - 1935:1935 # RTMP
-        #     - 8554:8554 # RTSP
+            - 8554:8554 # RTSP
-        #     - 8888:8888 # HLS
+            - 8888:8888 # HLS
-        #     - 5000:5000 # WEB-UI
+            - 5000:5000 # WEB-UI
         environment:
             - WYZE_EMAIL=${WYZE_EMAIL} # Replace with wyze email 
             - WYZE_PASSWORD=${WYZE_PASSWORD} # Replace with wyze password
@@ -47,7 +47,7 @@ services:
       depends_on:
         - bridge
       # Use wait-for-it to wait for the bridge at port 8554 to be ready and then run /app/main.py
-      command: /bin/sh -c "wait-for-it.sh bridge:8554 --timeout=0 --strict -- python /app/main.py"
+      command: /bin/bash -c "wait-for-it.sh -h bridge -p 1935 --timeout=0 --strict -- echo "done" && python /app/main.py"
 
 
 # How can this be run and a .env file passed?

main.py

@@ -6,6 +6,8 @@ from dotenv import load_dotenv
 import os
 import json
 import pathlib
+import requests
+import time
 
 
 load_dotenv()
@@ -82,6 +84,27 @@ else:
 
 print(f"Current config: {config}")
 
+# Try this 5 times, 5 seconds apart. If the stream is not available, exit
+for i in range(5):
+    # Check if HLS stream is available using the requests library
+    # If it is not, print an error and exit
+    try:
+    #    Replace rtsp with http and the port with 8888
+        r = requests.get(URL.replace("rtsp", "http").replace(":8554", ":8888"))
+        if r.status_code != 200:
+            print("HLS stream not available, please check your URL")
+            exit()
+    except requests.exceptions.RequestException as e:
+        print("HLS stream not available, please check your URL")
+        if i == 4:
+            exit()
+        else: 
+            print(f"Retrying in 5 seconds ({i+1}/5)")
+            time.sleep(5)
+            continue
+
+
+
 for face in config["faces"]:
     # Load a sample picture and learn how to recognize it.
     image = face_recognition.load_image_file(config["faces"][face]["image"])
@@ -96,6 +119,9 @@ video_capture = cv2.VideoCapture(URL)
 # However, this means that the video may be choppy
 video_capture.set(cv2.CAP_PROP_BUFFERSIZE, 1)
 
+# Print the resolution of the video
+print(f"Video resolution: {video_capture.get(cv2.CAP_PROP_FRAME_WIDTH)}x{video_capture.get(cv2.CAP_PROP_FRAME_HEIGHT)}")
+
 while True:
     # Grab a single frame of video
     ret, frame = video_capture.read()

requirements.txt

@@ -7,3 +7,5 @@ numpy==1.23.5
 opencv-python==4.6.0.66
 Pillow==9.3.0
 python-dotenv==0.21.0
+urllib3==1.26.13
+requests==2.28.1