locsec/AMMICO
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commented new heavy tests in test_multimodal_search.py

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Этот коммит содержится в:
Petr Andriushchenko 2023-03-30 14:19:07 +02:00
родитель f7081d6878
Коммит ecc0d814bb
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206
misinformation/test/test_multimodal_search.py
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@ -447,109 +447,109 @@ def test_parsing_images(
cuda.empty_cache()
def test_itm():
test_my_dict = {
"IMG_2746": {
"filename": "../misinformation/test/data/IMG_2746.png",
"rank A bus": 1,
"A bus": 0.15640679001808167,
"rank ../misinformation/test/data/IMG_3758.png": 1,
"../misinformation/test/data/IMG_3758.png": 0.7533495426177979,
},
"IMG_2809": {
"filename": "../misinformation/test/data/IMG_2809.png",
"rank A bus": 0,
"A bus": 0.1970970332622528,
"rank ../misinformation/test/data/IMG_3758.png": 0,
"../misinformation/test/data/IMG_3758.png": 0.8907483816146851,
},
}
search_query3 = [
{"text_input": "A bus"},
{"image": "../misinformation/test/data/IMG_3758.png"},
]
image_keys = ["IMG_2746", "IMG_2809"]
sorted_list = [[1, 0], [1, 0]]
for itm_model in ["blip_base", "blip_large"]:
(
itm_scores,
image_gradcam_with_itm,
) = ms.MultimodalSearch.image_text_match_reordering(
test_my_dict,
search_query3,
itm_model,
image_keys,
sorted_list,
batch_size=1,
need_grad_cam=True,
)
for i, itm in zip(
range(len(dict_itm_scores_for_blib[itm_model])),
dict_itm_scores_for_blib[itm_model],
):
assert (
math.isclose(itm_scores[0].tolist()[i], itm, rel_tol=10 * related_error)
is True
)
for i, grad_cam in zip(
range(len(dict_image_gradcam_with_itm_for_blip[itm_model])),
dict_image_gradcam_with_itm_for_blip[itm_model],
):
assert (
math.isclose(
image_gradcam_with_itm["A bus"]["IMG_2809"][0][0].tolist()[i],
grad_cam,
rel_tol=10 * related_error,
)
is True
)
del itm_scores, image_gradcam_with_itm
cuda.empty_cache()
# def test_itm():
# test_my_dict = {
# "IMG_2746": {
# "filename": "../misinformation/test/data/IMG_2746.png",
# "rank A bus": 1,
# "A bus": 0.15640679001808167,
# "rank ../misinformation/test/data/IMG_3758.png": 1,
# "../misinformation/test/data/IMG_3758.png": 0.7533495426177979,
# },
# "IMG_2809": {
# "filename": "../misinformation/test/data/IMG_2809.png",
# "rank A bus": 0,
# "A bus": 0.1970970332622528,
# "rank ../misinformation/test/data/IMG_3758.png": 0,
# "../misinformation/test/data/IMG_3758.png": 0.8907483816146851,
# },
# }
# search_query3 = [
# {"text_input": "A bus"},
# {"image": "../misinformation/test/data/IMG_3758.png"},
# ]
# image_keys = ["IMG_2746", "IMG_2809"]
# sorted_list = [[1, 0], [1, 0]]
# for itm_model in ["blip_base", "blip_large"]:
# (
# itm_scores,
# image_gradcam_with_itm,
# ) = ms.MultimodalSearch.image_text_match_reordering(
# test_my_dict,
# search_query3,
# itm_model,
# image_keys,
# sorted_list,
# batch_size=1,
# need_grad_cam=True,
# )
# for i, itm in zip(
# range(len(dict_itm_scores_for_blib[itm_model])),
# dict_itm_scores_for_blib[itm_model],
# ):
# assert (
# math.isclose(itm_scores[0].tolist()[i], itm, rel_tol=10 * related_error)
# is True
# )
# for i, grad_cam in zip(
# range(len(dict_image_gradcam_with_itm_for_blip[itm_model])),
# dict_image_gradcam_with_itm_for_blip[itm_model],
# ):
# assert (
# math.isclose(
# image_gradcam_with_itm["A bus"]["IMG_2809"][0][0].tolist()[i],
# grad_cam,
# rel_tol=10 * related_error,
# )
# is True
# )
# del itm_scores, image_gradcam_with_itm
# cuda.empty_cache()
def test_itm_blip2_coco():
test_my_dict = {
"IMG_2746": {
"filename": "../misinformation/test/data/IMG_2746.png",
"rank A bus": 1,
"A bus": 0.15640679001808167,
"rank ../misinformation/test/data/IMG_3758.png": 1,
"../misinformation/test/data/IMG_3758.png": 0.7533495426177979,
},
"IMG_2809": {
"filename": "../misinformation/test/data/IMG_2809.png",
"rank A bus": 0,
"A bus": 0.1970970332622528,
"rank ../misinformation/test/data/IMG_3758.png": 0,
"../misinformation/test/data/IMG_3758.png": 0.8907483816146851,
},
}
search_query3 = [
{"text_input": "A bus"},
{"image": "../misinformation/test/data/IMG_3758.png"},
]
image_keys = ["IMG_2746", "IMG_2809"]
sorted_list = [[1, 0], [1, 0]]
# def test_itm_blip2_coco():
# test_my_dict = {
# "IMG_2746": {
# "filename": "../misinformation/test/data/IMG_2746.png",
# "rank A bus": 1,
# "A bus": 0.15640679001808167,
# "rank ../misinformation/test/data/IMG_3758.png": 1,
# "../misinformation/test/data/IMG_3758.png": 0.7533495426177979,
# },
# "IMG_2809": {
# "filename": "../misinformation/test/data/IMG_2809.png",
# "rank A bus": 0,
# "A bus": 0.1970970332622528,
# "rank ../misinformation/test/data/IMG_3758.png": 0,
# "../misinformation/test/data/IMG_3758.png": 0.8907483816146851,
# },
# }
# search_query3 = [
# {"text_input": "A bus"},
# {"image": "../misinformation/test/data/IMG_3758.png"},
# ]
# image_keys = ["IMG_2746", "IMG_2809"]
# sorted_list = [[1, 0], [1, 0]]
(
itm_scores,
image_gradcam_with_itm,
) = ms.MultimodalSearch.image_text_match_reordering(
test_my_dict,
search_query3,
"blip2_coco",
image_keys,
sorted_list,
batch_size=1,
need_grad_cam=False,
)
for i, itm in zip(
range(len(dict_itm_scores_for_blib["blip2_coco"])),
dict_itm_scores_for_blib["blip2_coco"],
):
assert (
math.isclose(itm_scores[0].tolist()[i], itm, rel_tol=10 * related_error)
is True
)
del itm_scores, image_gradcam_with_itm
cuda.empty_cache()
# (
# itm_scores,
# image_gradcam_with_itm,
# ) = ms.MultimodalSearch.image_text_match_reordering(
# test_my_dict,
# search_query3,
# "blip2_coco",
# image_keys,
# sorted_list,
# batch_size=1,
# need_grad_cam=False,
# )
# for i, itm in zip(
# range(len(dict_itm_scores_for_blib["blip2_coco"])),
# dict_itm_scores_for_blib["blip2_coco"],
# ):
# assert (
# math.isclose(itm_scores[0].tolist()[i], itm, rel_tol=10 * related_error)
# is True
# )
# del itm_scores, image_gradcam_with_itm
# cuda.empty_cache()