Added test for emotion detector

test/udfs/test_emotion_detector.py

@@ -0,0 +1,64 @@
+# coding=utf-8
+# Copyright 2018-2022 EVA
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+from pathlib import Path
+from test.util import EVA_TEST_DATA_DIR
+
+import cv2
+import pandas as pd
+
+from eva.models.storage.batch import Batch
+
+
+class EmotionDetector(unittest.TestCase):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.base_path = Path(EVA_TEST_DATA_DIR) / "data" / "emotion_detector"
+
+    def _load_image(self, path):
+        assert path.exists(), f"File does not exist at the path {str(path)}"
+        img = cv2.imread(str(path))
+        return cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+
+    def test_should_return_correct_emotion(self):
+        from eva.udfs.emotion_detector import EmotionDetector
+
+        happy_img = self.base_path / "happy.jpg"
+        sad_img = self.base_path / "sad.jpg"
+        angry_img = self.base_path / "angry.jpg"
+
+        frame_happy = {
+            "id": 1,
+            "data": self._load_image(happy_img),
+        }
+
+        frame_sad = {
+            "id": 2,
+            "data": self._load_image(sad_img),
+        }
+
+        frame_angry = {
+            "id": 3,
+            "data": self._load_image(angry_img),
+        }
+
+        frame_batch = Batch(pd.DataFrame([frame_happy, frame_sad, frame_angry]))
+        detector = EmotionDetector()
+        result = detector.classify(frame_batch.project(["data"]).frames)
+
+        self.assertEqual("happy", result.iloc[0]["labels"])
+        self.assertEqual("sad", result.iloc[1]["labels"])
+        self.assertEqual("angry", result.iloc[2]["labels"])