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* colors expression by KMean algorithm * object detection by imageai * object detection by cvlib * add encapsulation of object detection * remove encapsulation of objdetect v0 * objects expression to dict * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * added imageai to requirements * add objects to dictionary * update for AnalysisMethod baseline * add objects dection support explore_analysis display * extend python version of misinf to allow imageai * account for older python * use global functionality for dict to csv convert * update for docker build * docker will build now but ipywidgets still not working * test code * include test data folder in repo * add some sample images * load cvs labels to dict * add test data * retrigger checks * add map to human coding * get orders from dict, missing dep * add module to test accuracy * retrigger checks * retrigger checks * now removing imageai * removed imageai * move labelmanager to analyse * multiple faces in mydict * fix pre-commit issues * map mydict * hide imageai * objects default using cvlib, isolate and disable imageai * correct python version * refactor faces tests * refactor objects tests * sonarcloud issues * refactor utils tests * address code smells * update readme * update notebook without imageai Co-authored-by: Ma Xianghe <825074348@qq.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: iulusoy <inga.ulusoy@uni-heidelberg.de>
32 строки
889 B
Python
32 строки
889 B
Python
import json
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import pytest
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import misinformation
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import misinformation.objects as ob
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import misinformation.objects_cvlib as ob_cvlib
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@pytest.fixture()
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def default_objects():
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return ob.init_default_objects()
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def test_objects_from_cvlib(default_objects):
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objects_list = ["cell phone", "motorcycle", "traffic light"]
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objects = ob_cvlib.objects_from_cvlib(objects_list)
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out_objects = default_objects
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for obj in objects_list:
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out_objects[obj] = "yes"
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assert str(objects) == str(out_objects)
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def test_analyse_image_cvlib():
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mydict = {"filename": "./test/data/IMG_2809.png"}
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ob_cvlib.ObjectCVLib().analyse_image(mydict)
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with open("./test/data/example_objects_cvlib.json", "r") as file:
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out_dict = json.load(file)
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for key in mydict.keys():
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print(key)
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assert mydict[key] == out_dict[key]
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