Feature/camera deskew

README.md

@@ -1,6 +1,6 @@
-# SUAS-2023
+# SUAS-2025
 
-Missouri S&T Multirotor Robot Design Team's code for the Association for Unmanned Vehicle Systems International's 2023 Student Unmanned Aerial Systems Competition (AUVSI SUAS 2023)
+Missouri S&T Multirotor Drone Design Team's code for the Association for Unmanned Vehicle Systems International's 2025 Student Unmanned Aerial Systems Competition (AUVSI SUAS 2025) hosted by Robonation
 
 ## Table of contents
 
@@ -53,7 +53,7 @@ You will need to install pip with `sudo apt-get install python3-pip`. Pip is use
 
 ### Getting the Repo
 
-Go to your documents folder and clone the repo with `git clone https://github.com/MissouriMRR/SUAS-2023.git`
+Go to your documents folder and clone the repo with `git clone https://github.com/MissouriMRR/SUAS-2025.git`
 
 ### Pre-commit
 

Unittest_camera_distance.py

@@ -0,0 +1,93 @@
+import unittest
+import numpy as np
+from enum import Enum
+from vision.common.constants import Point, CameraParameters, ODLCDict
+from vision.common.bounding_box import BoundingBox, ObjectType
+from vision.deskew.camera_distances import get_coordinates, bounding_area, calculate_distance
+
+
+class TestVisionFunctions(unittest.TestCase):
+    """
+    Tests to verify the functionality of calculations
+    concerning object positioning and distances in images captured by a camera.
+
+    Attributes
+    ----------
+        The dimensions of the image used in tests, specified as (height, width, channels).
+    """
+
+    def setUp(self) -> None:
+        """
+        Initializes common properties for all test methods. Sets up camera parameters
+        and image dimensions that simulate a typical usage scenario.
+
+        """
+        self.camera_params = CameraParameters(
+            focal_length=35.0,
+            rotation_deg=[0, 0, 0],
+            drone_coordinates=[37.7749, -122.4194],
+            altitude_f=1000.0,
+        )
+        self.image_shape = (1080, 1920, 3)  # Image size with 3 color channels
+
+    def test_get_coordinates(self) -> None:
+        """
+
+        Verifies that the accurately calculates  coordinates
+        from a center pixel. Asserts correct type and closeness to expected values.
+
+        Returns
+        -------
+            None: This method does not return a value but asserts the correctness of the output.
+        """
+        center_pixel = (960, 540)
+        expected_coordinates = (37.77, -122.211)
+        result = get_coordinates(center_pixel, self.image_shape, self.camera_params)
+
+        self.assertIsNotNone(result, "Coordinates should not be None")
+        # Check if the result is not None and is of the expected tuple type
+        self.assertIsInstance(result, tuple, "Result should be a tuple")
+        if isinstance(result, tuple):
+            self.assertEqual(len(result), 2, "Result tuple should have two elements")
+            self.assertIsInstance(result[0], float, "Latitude is float")
+            self.assertIsInstance(result[1], float, "Longitude is float")
+        # Make sure to get the expected value
+        if result is not None:
+            self.assertAlmostEqual(result[0], expected_coordinates[0], places=2)
+            self.assertAlmostEqual(result[1], expected_coordinates[1], places=2)
+
+    def test_bounding_area(self) -> None:
+        """
+        Tests the  function to calculate the area of a bounding box
+        within the image, simulating an object detection scenario.
+
+        Returns
+        -------
+            None: This method does not return a value but asserts the area calculation is correct.
+        """
+        obj_type = ObjectType(value="")  # Provide the necessary argument
+        self.box = BoundingBox(
+            obj_type=obj_type,
+            vertices=((100, 200), (200, 200), (200, 300), (100, 300)),
+        )
+        expected_area = 10000
+        result = bounding_area(self.box, self.image_shape, self.camera_params)
+
+        # Ensure result is not None before asserting
+        self.assertIsNotNone(result, "Result should not be None for valid bounding box")
+
+    def test_calculate_distance(self) -> None:
+        """
+        Tests distance calculation between two points in an image. Ensures the method
+        returns a valid result.
+        """
+        pixel1 = (100, 100)
+        pixel2 = (200, 200)  # Valid pixel coordinates
+        result = calculate_distance(pixel1, pixel2, self.image_shape, self.camera_params)
+
+        # Ensure result is not None before asserting
+        self.assertIsNotNone(result, "Result should not be None for valid pixel coordinates")
+
+
+if __name__ == "__main__":
+    unittest.main()

camera.json

@@ -0,0 +1,17 @@
+{
+    "suas2.png": {
+        "focal_length": 10,
+        "rotation_deg": [10, 20, 30],
+        "drone_coordinates": [50.80085, 21.42069],
+        "altitude_f": 100
+    },
+
+
+
+    "suas.png": {
+        "focal_length": 10,
+        "rotation_deg": [10, 20, 30],
+        "drone_coordinates": [50.80085, 21.42069],
+        "altitude_f": 100
+    }
+}