diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml index 2425967..f542b8b 100644 --- a/.github/workflows/ci.yaml +++ b/.github/workflows/ci.yaml @@ -32,4 +32,7 @@ jobs: poetry install - name: Run Pre commit hooks - run: make format-code \ No newline at end of file + run: make format-code + + - name: Run Tests + run: poetry run pytest tests \ No newline at end of file diff --git a/README.md b/README.md index baaeb89..b4b077c 100644 --- a/README.md +++ b/README.md @@ -42,3 +42,10 @@ ByteTrack is licensed under the MIT License. See the [LICENSE](LICENSE) file and year={2022} } ``` + +```bibtex +@video{intel-iot-devkit, + author={Intel IoT}, + title={Intel IoT Devkit Sample Videos(https://github.com/intel-iot-devkit/sample-videos)}, + license={Creative Commons Attribution 4.0 International License(https://creativecommons.org/licenses/by/4.0/)} +``` diff --git a/tests/expected_output/objects_detected_and_tracked_video1.txt b/tests/expected_output/objects_detected_and_tracked_video1.txt new file mode 100644 index 0000000..0c137d0 --- /dev/null +++ b/tests/expected_output/objects_detected_and_tracked_video1.txt @@ -0,0 +1,1782 @@ +1 0.43556426884883115 0.77328302 0.5555945999999999 0.933616134 1 2 0.8920609 +1 0.5097041794815526 0.4710114960000001 0.5574228520000001 0.5331648560000001 2 2 0.87958884 +1 0.30967665687427137 0.515491712 0.368265234 0.588124726 3 2 0.87676245 +1 0.20932472635232796 0.6073970599999998 0.319006622 0.7888608799999999 4 2 0.8569984 +1 0.43064804095509635 0.40286853 0.46754843 0.453162686 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0.23476952 2 diff --git a/tests/test_input/objects_detected_video2.txt b/tests/test_input/objects_detected_video2.txt new file mode 100644 index 0000000..d6a3d8c --- /dev/null +++ b/tests/test_input/objects_detected_video2.txt @@ -0,0 +1,21 @@ +40 0.21998224 0.5836777 0.3745204 0.7639922 0.16180652 49 +116 0.9795788 0.53099704 0.9996632 0.7194981 0.51681966 49 +117 0.95138013 0.5041999 0.999584 0.748006 0.83191514 49 +118 0.9269222 0.49708003 0.9995592 0.7467762 0.8575639 49 +119 0.88959634 0.49609375 0.9994829 0.7485177 0.886084 49 +120 0.8366054 0.50106037 0.99332654 0.75461787 0.9059332 49 +121 0.7823308 0.5008052 0.93827456 0.7578524 0.92144907 49 +122 0.73994255 0.50089943 0.89590263 0.76007366 0.9317426 49 +123 0.70718193 0.5019245 0.86416876 0.76115876 0.9288402 49 +124 0.6728785 0.5005684 0.8293528 0.75955844 0.92904073 49 +125 0.624425 0.50280184 0.78042 0.76286423 0.9264275 49 +126 0.5726967 0.5034708 0.72873324 0.7666482 0.93153256 49 +127 0.53285456 0.50363165 0.6897488 0.7668706 0.93632597 49 +128 0.4952455 0.5036848 0.6524906 0.7663839 0.9300204 49 +129 0.44878444 0.50468314 0.60615635 0.7671972 0.927421 49 +130 0.39896855 0.5050585 0.5573927 0.76832783 0.92839193 49 +131 0.35776815 0.5048203 0.51712275 0.76961535 0.93056595 49 +132 0.31567994 0.5045963 0.4752435 0.7699328 0.9226942 49 +133 0.26709083 0.5050746 0.4275921 0.7702349 0.9281332 49 +134 0.22100373 0.5047798 0.3819117 0.77039224 0.92945176 49 +135 0.17729278 0.5041295 0.3402054 0.77022386 0.92946494 49 diff --git a/tests/test_model_regression.py b/tests/test_model_regression.py new file mode 100644 index 0000000..304363c --- /dev/null +++ b/tests/test_model_regression.py @@ -0,0 +1,102 @@ +from pathlib import Path + +import numpy as np +import pytest + +# bytetracker +from bytetracker import BYTETracker + +# static paths +OUTPUT_FOLDER = Path("tests/output") +TEST_INPUT_FOLDER = Path("tests/test_input") +EXPECTED_OUTPUT_FOLDER = Path("tests/expected_output") +OUTPUT_FOLDER = Path("tests/output") + +OUTPUT_FOLDER.mkdir(parents=True, exist_ok=True) + + +def reading_detections_file(video_number): + """Read the detections object file from a specific format + + Args: + video_number (string): string representing the video name in folder + + Returns: + df_detection (ndarray): A list of array of the tuples. + """ + df_detection = np.loadtxt( + TEST_INPUT_FOLDER / f"objects_detected_{video_number}.txt", delimiter=" " + ) + + return df_detection + + +def reading_expected_results_from_txt(video_number): + """Read the detections and tracked objects frames from Yolo and Bytetrack models + + Args: + video_number (str): Video title to import + + Returns: + expected_results_df (ndarray): array of frames detection and tracking imported from expected results. + """ + expected_results_df = np.loadtxt( + EXPECTED_OUTPUT_FOLDER / f"objects_detected_and_tracked_{video_number}.txt" + ) + + return expected_results_df + + +@pytest.mark.parametrize( + "expected_results, test_input, video_number", + [ + ( + reading_expected_results_from_txt("video1"), + reading_detections_file("video1"), + "video1", + ), + ( + reading_expected_results_from_txt("video2"), + reading_detections_file("video2"), + "video2", + ), + ], +) +def test_video_prediction_tracking(expected_results, test_input, video_number): + """Execute the integration test: performing the tracking of test_input, + whose output is to compare with expected_results + + Args: + expected_result (DataFrame): the dataframe of the results expected to match the test result + test_input (array): dataframe that is the import of prediction frames in test_input folder + video_number (string): string component specific to a video + + Returns: + Test assertion results + """ + tracker = BYTETracker(track_thresh=0.15, track_buffer=3, match_thresh=0.85, frame_rate=12) + # first column of test input is the frame id + frame_idx = sorted(np.unique(test_input[:, 0])) + test_results = [] + + for frame_id in frame_idx: + detections = test_input[test_input[:, 0] == frame_id][:, 1:] + tracked_objects = tracker.update(detections, frame_id) + if len(tracked_objects) > 0: + tracked_objects = np.insert( + tracked_objects, 0, np.full(len(tracked_objects), frame_id), axis=1 + ) + test_results.append(tracked_objects) + + if test_results: # Ensure test_results is not empty to avoid errors + combined_array = np.concatenate(test_results) + else: + combined_array = np.array([]) # Or handle the empty case as needed + + output_file_path = OUTPUT_FOLDER / f"{video_number}_test_results.txt" + np.savetxt(output_file_path, combined_array, delimiter=" ", fmt="%s") + + assert np.allclose(expected_results, combined_array) + + # Remove the file if the test is successful + output_file_path.unlink()