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classification_service/views/classify_view.py

@@ -5,6 +5,7 @@ from flask_classful import FlaskView
 from utils import json_required
 import requests
 import tempfile
+import numpy
 
 from pyAudioAnalysis.audioTrainTest import load_model, load_model_knn, classifier_wrapper
 
@@ -14,25 +15,25 @@ class ClassifyView(FlaskView):
     @json_required
     def post(self):
 
-        request.json
+        task = request.json  # tag, features, model
 
         _, temp_model_name = tempfile.mkstemp()
         temp_means_name = temp_model_name + "MEANS"
 
-        r = requests.get("http://model-service/model/$default/details")
+        r = requests.get(f"http://model-service/model/{task['model']}/details")
         r.raise_for_status()
 
         model_details = r.json()
 
         try:
 
-            r = requests.get("http://model-service/model/$default")
+            r = requests.get(f"http://model-service/model/{task['model']}")
             r.raise_for_status()
 
             with open(temp_model_name, 'wb') as f:
                 f.write(r.content)
 
-            r = requests.get("http://model-service/model/$default?means")
+            r = requests.get(f"http://model-service/model/{task['model']}?means")
             r.raise_for_status()
 
             with open(temp_means_name, 'wb') as f:
@@ -46,7 +47,8 @@ class ClassifyView(FlaskView):
                 classifier, mean, std, classes, mid_window, mid_step, short_window, short_step, compute_beat \
                     = load_model(temp_model_name)
 
-            # class_id, probability = classifier_wrapper(classifier, model_details['type'], feature_vector)
+            feature_vector = (numpy.array(task['features']) - mean) / std
+            class_id, probability = classifier_wrapper(classifier, model_details['type'], feature_vector)
 
         finally:  # bruuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuh
             try:
@@ -59,4 +61,10 @@ class ClassifyView(FlaskView):
             except FileNotFoundError:
                 pass
 
-        return jsonify({})
+        # TODO: Publish to message queue
+        results = {
+            "class_id": class_id,
+            "probability": probability
+        }
+
+        return jsonify({"status": "OK", "msg": "enqueued"})