Add model type to API request

app.py

@@ -46,21 +46,17 @@ def detect(image_path, model_id, threshold):
     # Encode the image data in base64
     encoded_image = base64.b64encode(image_bytes).decode('utf-8')
 
+    model_name = list_models_simple[model_id]
+
     # Requests arguments
     payload = {
         'body': encoded_image,
         'isBase64Encoded': True,
+        'model': model_name,
     }
     headers = {"Content-Type": "application/json"}
 
-    # Prepare the query string parameters
-    model_name = list_models_simple[model_id]
-    params = {
-        'model': model_name
-    }
-
     response = requests.post(API_endpoint, json=payload, headers=headers)
-    # response = requests.post(API_endpoint, json=payload, headers=headers, params=params)
 
     if response.status_code == 200:
         # Process the response

lambda_function.py

@@ -40,18 +40,11 @@ def detection_pipeline(model_type, image_bytes):
 def lambda_handler(event, context):
     logger.info(f"API event: {event}")
     try:
-        # Get the model name from the query string parameters
-        # Condition for local testing
-        # is_querystringparam = event.get('queryStringParameters')
-        # if is_querystringparam is not None:
-        #     model_query = event['queryStringParameters'].get('model', '').lower()
-        # else:
-        #     model_query = ""
-        # model_type = get_model_type(model_query)
-        # logger.info(f"Model query: {model_query}")
-        # logger.info(f"Model type: {model_type}")
-
-        model_type = get_model_type("")
+        # Retrieve model type
+        model_query = event.get('model', '')
+        model_type = get_model_type(model_query)
+        logger.info(f"Model query: {model_query}")
+        logger.info(f"Model type: {model_type}")
 
         # Decode the base64-encoded image data from the event
         image_data = event['body']