Add the inspireface project to cpp-package.

cpp-package/inspireface/python/test/unit/test_base_module.py

@@ -0,0 +1,51 @@
+from test import *
+import unittest
+import inspireface as ifac
+from inspireface.param import *
+import cv2
+
+
+class CameraStreamCase(unittest.TestCase):
+    def setUp(self) -> None:
+        """Shared area for priority execution"""
+        pass
+
+    def test_image_codec(self) -> None:
+        image = cv2.imread(get_test_data("bulk/kun.jpg"))
+        self.assertIsNotNone(image)
+
+    def test_stream_rotation(self) -> None:
+        # Prepare material
+        engine = ifac.InspireFaceSession(HF_ENABLE_NONE, HF_DETECT_MODE_IMAGE)
+        # Prepare rotation images
+        rotation_images_filenames = ["rotate/rot_0.jpg", "rotate/rot_90.jpg", "rotate/rot_180.jpg","rotate/rot_270.jpg"]
+        rotation_images = [cv2.imread(get_test_data(path)) for path in rotation_images_filenames]
+        self.assertEqual(True, all(isinstance(item, np.ndarray) for item in rotation_images))
+
+        # Detecting face images without rotation
+        rot_0 = rotation_images[0]
+        h, w, _ = rot_0.shape
+        self.assertIsNotNone(rot_0, "Image is empty")
+        rot_0_faces = engine.face_detection(image=rot_0)
+        self.assertEqual(True, len(rot_0_faces) > 0)
+        rot_0_face_box = rot_0_faces[0].location
+        num_of_faces = len(rot_0_faces)
+
+        # Detect images with other rotation angles
+        rotation_tags = [HF_CAMERA_ROTATION_90, HF_CAMERA_ROTATION_180, HF_CAMERA_ROTATION_270]
+        streams = [ifac.ImageStream.load_from_cv_image(img, rotation=rotation_tags[idx]) for idx, img in enumerate(rotation_images[1:])]
+        results = [engine.face_detection(stream) for stream in streams]
+        # No matter how many degrees the image is rotated, the same number of faces should be detected
+        self.assertEqual(True, all(len(item) == num_of_faces for item in results))
+        # Select all the first face box
+        rot_other_faces_boxes = [face[0].location for face in results]
+        # We need to restore the rotated face box
+        restored_boxes = [restore_rotated_box(w, h, rot_other_faces_boxes[idx], rotation_tags[idx]) for idx, box in enumerate(rot_other_faces_boxes)]
+        # IoU is performed with the face box of the original image to calculate the overlap
+        iou_results = [calculate_overlap(box, rot_0_face_box) for box in restored_boxes]
+        # The face box position of all rotated images is detected to be consistent with that of the original image
+        self.assertEqual(all(0.95 < iou < 1.0 for iou in iou_results), True)
+
+
+if __name__ == '__main__':
+    unittest.main()