Fixing/Adding tests

edge_model_serving/tflite_serving/src/tflite_serving/utils/yolo_postprocessing.py

@@ -50,9 +50,9 @@ def compute_box_severity(image: np.array, box: List):
     # Looking at severity as mean darkness
     dark_colors = image_detection[mask_dark_pixels].flatten()
     if dark_colors.size == 0:
-        return 0.09
+        return 0.1
     else:
-        severity = (0.5 - dark_colors.mean()) * 2
+        severity = round((0.5 - dark_colors.mean()) * 2, 2)
         return severity
 
 

edge_model_serving/tflite_serving/tests/data/utils/test_yolo_postprocessing.py

@@ -0,0 +1,112 @@
+import numpy as np
+from tflite_serving.utils.yolo_postprocessing import (
+    yolo_extract_boxes_information,
+    nms,
+    compute_severities,
+)
+
+
+class TestYoloPostprocessing:
+    def test_yolo_extract_boxes_information(self):
+        # Given
+        model_outputs = np.array(
+            [
+                [100, 120, 50, 30, 0.8, 0.1, 0.001],
+                [300, 220, 30, 26, 0.01, 0.99, 0.001],
+                [110, 125, 40, 20, 0.9, 0.01, 0.01],
+            ]
+        )
+        expected_boxes = [
+            [75, 105, 125, 135],
+            [285, 207, 315, 233],
+            [90, 115, 130, 135],
+        ]
+        expected_scores = [0.8, 0.99, 0.9]
+        expected_classes = [0, 1, 0]
+
+        # When
+        boxes, scores, classes = yolo_extract_boxes_information(model_outputs)
+
+        # Then
+        assert boxes == expected_boxes
+        assert scores == expected_scores
+        assert classes == expected_classes
+
+    def test_nms(self):
+        # Given
+        boxes = [
+            [75, 105, 125, 135],
+            [285, 207, 315, 233],
+            [90, 115, 130, 135],
+            [90, 115, 130, 135],
+            [120, 130, 200, 155],
+        ]
+        scores = [0.8, 0.99, 0.9, 0.34, 0.75]
+        classes = [0, 1, 0, 2, 0]
+
+        # When
+        expected_boxes = [
+            [285, 207, 315, 233],
+            [90, 115, 130, 135],
+            [120, 130, 200, 155],
+        ]
+        expected_scores = [0.99, 0.9, 0.75]
+        expected_classes = [1, 0, 0]
+
+        nms_boxes, nms_scores, nms_classes = nms(
+            boxes, scores, classes, score_threshold=0.4, iou_threshold=0.45
+        )
+
+        # Then
+        assert nms_boxes == expected_boxes
+        assert nms_scores == expected_scores
+        assert nms_classes == expected_classes
+
+    def test_compute_severities(self):
+        # Given
+        image = np.array(
+            [
+                [
+                    [1, 1, 1],
+                    [1, 1, 1],
+                    [0.8, 0.8, 0.8],
+                    [1, 1, 1],
+                    [1, 1, 1]],
+                [
+                    [0.8, 0.8, 0.8],
+                    [0.8, 0.8, 0.8],
+                    [0.6, 0.6, 0.6],
+                    [0.8, 0.8, 0.8],
+                    [0.8, 0.8, 0.8],
+                ],
+                [
+                    [0.6, 0.6, 0.6],
+                    [0.2, 0.2, 0.2],
+                    [0.0, 0.0, 0.0],
+                    [0.2, 0.2, 0.2],
+                    [0.6, 0.6, 0.6],
+                ],
+                [
+                    [0.6, 0.6, 0.6],
+                    [0.2, 0.2, 0.2],
+                    [0.0, 0.0, 0.0],
+                    [0.2, 0.2, 0.2],
+                    [0.6, 0.6, 0.6],
+                ],
+                [
+                    [0.8, 0.8, 0.8],
+                    [0.8, 0.8, 0.8],
+                    [0.0, 0.0, 0.0],
+                    [0.0, 0.0, 0.0],
+                    [0.8, 0.8, 0.8],
+                ],
+            ]
+        )
+        boxes = [[0.23, 0.23, 1, 1], [0.1, 0.05, 0.4, 0.2]]
+        expected_severities = [0.8, 0.1]
+
+        # When
+        severities = compute_severities(image, boxes)
+
+        # Then
+        assert severities == expected_severities

edge_orchestrator/tests/functional_tests/supervisor_configs_routes.feature

@@ -22,6 +22,7 @@ Feature: The client set an active configuration
     Then the active configuration is
     """
     {
+      "name": "test_name",
       "cameras": {
         "camera_id3": {
           "type": "fake",

edge_orchestrator/tests/functional_tests/supervisor_inventory_route.feature

@@ -49,6 +49,7 @@ Feature: The client requests the inventory available on the station
       "mobilenet_v1_640x640": {
         "category": "object_detection",
         "version": 1,
+        "model_type": "Mobilnet",
         "class_names_path": "test_detection_labels",
         "output": {
           "boxes_coordinates": "detection_boxes",
@@ -61,6 +62,7 @@ Feature: The client requests the inventory available on the station
       "mobilenet_v1_640x640_detect_classif": {
         "category": "object_detection_with_classification",
         "version": 1,
+        "model_type": "Mobilnet",
         "class_names_path": "test_detection_labels",
         "output": {
           "boxes_coordinates": "detection_boxes",