working version!

machine-learning-client/Dockerfile

@@ -11,7 +11,6 @@ WORKDIR /usr/src/app
 
 COPY . /usr/src/app
 
-RUN pip install --retries=5 --default-timeout=300 opencv-python
 RUN pip install --retries=3 --default-timeout=150 -r requirements.txt
 
 

machine-learning-client/api.py

@@ -12,19 +12,18 @@
 def analyze_image(img_path):
     """
     Analyze an image for age and gender using DeepFace.
-
     Parameters:
         img_path (str): Path to the image file
-
     Returns:
         list: Analysis results including age
     """
     try:
-        logging.info("Analyzing the image at path: %s", img_path)
-        result = DeepFace.analyze(img_path=img_path, actions=["age", "gender", "emotion", "race"])
-        logging.info("Analysis result: %s", result)
-        # Updated to access dictionary values directly
-        return [result[0]["age"], result[0]["dominant_gender"], result[0]["dominant_emotion"], result[0]["dominant_race"]]
+         logging.info("Analyzing the image at path: %s", img_path)
+         result = DeepFace.analyze(img_path=img_path, actions=["age", "gender", "emotion", "race"])
+         logging.info("Analysis result: %s", result)
+
+         return [result[0]["age"], result[0]["dominant_gender"], result[0]["dominant_emotion"], result[0]["dominant_race"]]
+
     except Exception as e:
          logging.error("An error occurred during image analysis: %s", e)
          raise

machine-learning-client/api_server.py

@@ -12,9 +12,9 @@
 app = Flask(__name__)
 
 serverOptions = {
-    "socketTimeoutMS": 6000000,  # 10 minutes
-    "connectTimeoutMS": 3000000,  # 30 seconds
-    "serverSelectionTimeoutMS": 3000000,  # 30 seconds
+    "socketTimeoutMS": 600000,  # 10 minutes
+    "connectTimeoutMS": 300000,  # 30 seconds
+    "serverSelectionTimeoutMS": 300000,  # 30 seconds
 }
 
 client = MongoClient("mongodb://mongodb:27017/", **serverOptions)