diff --git a/README.md b/README.md index ecdd3e19..a6e1498b 100644 --- a/README.md +++ b/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 diff --git a/Unittest_camera_distance.py b/Unittest_camera_distance.py new file mode 100644 index 00000000..4a2d8d86 --- /dev/null +++ b/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() diff --git a/camera.json b/camera.json new file mode 100644 index 00000000..e02ea4cf --- /dev/null +++ b/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 + } +} diff --git a/poetry.lock b/poetry.lock index 70f2541b..2b18d8a1 100644 --- a/poetry.lock +++ b/poetry.lock @@ -16,17 +16,18 @@ grpcio = ">=1.12.0" [[package]] name = "astroid" -version = "2.12.10" +version = "2.15.8" description = "An abstract syntax tree for Python with inference support." optional = false python-versions = ">=3.7.2" files = [ - {file = "astroid-2.12.10-py3-none-any.whl", hash = "sha256:997e0c735df60d4a4caff27080a3afc51f9bdd693d3572a4a0b7090b645c36c5"}, - {file = "astroid-2.12.10.tar.gz", hash = "sha256:81f870105d892e73bf535da77a8261aa5bde838fa4ed12bb2f435291a098c581"}, + {file = "astroid-2.15.8-py3-none-any.whl", hash = "sha256:1aa149fc5c6589e3d0ece885b4491acd80af4f087baafa3fb5203b113e68cd3c"}, + {file = "astroid-2.15.8.tar.gz", hash = "sha256:6c107453dffee9055899705de3c9ead36e74119cee151e5a9aaf7f0b0e020a6a"}, ] [package.dependencies] lazy-object-proxy = ">=1.4.0" +typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""} wrapt = [ {version = ">=1.14,<2", markers = "python_version >= \"3.11\""}, {version = ">=1.11,<2", markers = "python_version < \"3.11\""}, @@ -60,121 +61,123 @@ uvloop = ["uvloop (>=0.15.2)"] [[package]] name = "certifi" -version = "2022.9.14" +version = "2024.8.30" description = "Python package for providing Mozilla's CA Bundle." optional = false python-versions = ">=3.6" files = [ - {file = "certifi-2022.9.14-py3-none-any.whl", hash = "sha256:e232343de1ab72c2aa521b625c80f699e356830fd0e2c620b465b304b17b0516"}, - {file = "certifi-2022.9.14.tar.gz", hash = "sha256:36973885b9542e6bd01dea287b2b4b3b21236307c56324fcc3f1160f2d655ed5"}, + {file = "certifi-2024.8.30-py3-none-any.whl", hash = "sha256:922820b53db7a7257ffbda3f597266d435245903d80737e34f8a45ff3e3230d8"}, + {file = "certifi-2024.8.30.tar.gz", hash = "sha256:bec941d2aa8195e248a60b31ff9f0558284cf01a52591ceda73ea9afffd69fd9"}, ] [[package]] name = "charset-normalizer" -version = "3.0.1" +version = "3.3.2" description = "The Real First Universal Charset Detector. 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b/vision/.DS_Store new file mode 100644 index 00000000..8d56551d Binary files /dev/null and b/vision/.DS_Store differ diff --git a/vision/standard_object/odlc_classify_shape.py b/vision/standard_object/odlc_classify_shape.py index 6e9f85a4..d5a4759c 100644 --- a/vision/standard_object/odlc_classify_shape.py +++ b/vision/standard_object/odlc_classify_shape.py @@ -1,15 +1,13 @@ """Takes the contour of an ODLC shape and determine which shape it is in the certain file path""" import json -from typing import List, Tuple, TypeAlias - import cv2 import numpy as np import scipy from nptyping import NDArray, Shape, Float64 from scipy import signal import scipy.interpolate - +from typing import List, Tuple, TypeAlias from vision.common import constants as consts from vision.common import odlc_characteristics as chars from vision.common.bounding_box import BoundingBox as bbox diff --git a/vision/standard_object/odlc_contour_detection.py b/vision/standard_object/odlc_contour_detection.py index 4d095575..453613af 100644 --- a/vision/standard_object/odlc_contour_detection.py +++ b/vision/standard_object/odlc_contour_detection.py @@ -29,7 +29,7 @@ def fetch_shape_contours( image: Image, draw_contours: bool = False, resulting_file_name: str = "" -) -> list[np.ndarray[np.dtype[np.uint8], np.dtype[np.uint8]]]: +) -> list[Contour]: """ Detects the boundaries of potential shapes based on a pixel or region's brightness and saturation, finding only the darkest, brightest, and diff --git a/vision/unit_tests/photo_model_test.py b/vision/unit_tests/photo_model_test.py index fb25a7a9..8772066c 100644 --- a/vision/unit_tests/photo_model_test.py +++ b/vision/unit_tests/photo_model_test.py @@ -50,7 +50,7 @@ def flyover_pipeline(camera_data_path: str) -> None: image_parameters: dict[str, consts.CameraParameters] = pipe_utils.read_parameter_json( camera_data_path ) - + print(image_parameters) # Loop through all images in the json - if it hasn't been processed, process it for image_path in image_parameters.keys(): print(image_path) @@ -108,4 +108,5 @@ def flyover_pipeline(camera_data_path: str) -> None: logging.basicConfig(filename="/dev/stdout", level=logging.INFO) -flyover_pipeline("flight/data/camera.json") +# flyover_pipeline("flight/data/camera.json") +flyover_pipeline("camera.json")