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a5c43b6488
* deleted lavis from utils * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fixed test_objects * added 'not gcv' to CI * fixed multimodal search and summary tests * disable doc build on PR for now * restrict ipywidgets version to avoid dummycomm error * limit deepface version * original repositories for retinaface lavis * update gcv test results * update display test outputs * update test env * run all tests * wo xdist to avoid segfault * remove widgets ref * skip long-running tests * skip long * verbose codecov upload * refactor summary test 2 * finish summary test refactor * reduce memory overhead of SummaryDetector * remove VQA models from self * remove VQA models from self * update notebook for changes * update notebook for changes * fixed multimodal search tests * fixed tests in multimodal search after precommit * run all tests * update doc notebook for summary changes * skip long-running multimodal * exclude blip2 from testing --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Inga Ulusoy <inga.ulusoy@uni-heidelberg.de>
94 строки
2.6 KiB
Python
94 строки
2.6 KiB
Python
import json
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import pytest
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import misinformation.objects as ob
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import misinformation.objects_cvlib as ob_cvlib
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OBJECT_1 = "cell phone"
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OBJECT_2 = "motorcycle"
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OBJECT_3 = "traffic light"
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TEST_IMAGE_1 = "IMG_2809.png"
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JSON_1 = "example_objects_cvlib.json"
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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 = [OBJECT_1, OBJECT_2, OBJECT_3]
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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(get_path):
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mydict = {"filename": get_path + TEST_IMAGE_1}
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ob_cvlib.ObjectCVLib().analyse_image(mydict)
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with open(get_path + JSON_1, "r") as file:
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out_dict = json.load(file)
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out_dict["filename"] = get_path + out_dict["filename"]
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for key in mydict.keys():
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assert mydict[key] == out_dict[key]
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def test_init_default_objects():
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default_obj_list = [
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"person",
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"bicycle",
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"car",
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OBJECT_2,
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"airplane",
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"bus",
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"train",
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"truck",
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"boat",
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OBJECT_3,
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OBJECT_1,
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]
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init_objects = ob_cvlib.init_default_objects()
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for obj in default_obj_list:
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assert init_objects[obj] == "no"
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def test_analyse_image_from_file_cvlib(get_path):
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file_path = get_path + TEST_IMAGE_1
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objs = ob_cvlib.ObjectCVLib().analyse_image_from_file(file_path)
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with open(get_path + JSON_1, "r") as file:
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out_dict = json.load(file)
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out_dict["filename"] = get_path + out_dict["filename"]
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for key in objs.keys():
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assert objs[key] == out_dict[key]
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def test_detect_objects_cvlib(get_path):
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file_path = get_path + TEST_IMAGE_1
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objs = ob_cvlib.ObjectCVLib().detect_objects_cvlib(file_path)
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with open(get_path + JSON_1, "r") as file:
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out_dict = json.load(file)
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for key in objs.keys():
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assert objs[key] == out_dict[key]
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def test_set_keys(default_objects, get_path):
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mydict = {"filename": get_path + TEST_IMAGE_1}
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key_objs = ob.ObjectDetector(mydict).set_keys()
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assert str(default_objects) == str(key_objs)
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def test_analyse_image(get_path):
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mydict = {"filename": get_path + TEST_IMAGE_1}
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ob.ObjectDetector.set_client_to_cvlib()
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ob.ObjectDetector(mydict).analyse_image()
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with open(get_path + JSON_1, "r") as file:
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out_dict = json.load(file)
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out_dict["filename"] = get_path + out_dict["filename"]
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assert str(mydict) == str(out_dict)
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