structural_similarity函数返回两个值:ssim_value和diff(如果full=True)。ssim_value是一个介于0和1之间的浮点数,表示两个图像的结构相似度。值越接近1,表示两个图像越相似。 python print(f"SSIM: {ssim_value}") 你可以根据ssim_value的值来判断两个图像的相似程度,或者将其用于进一步的处理或决策。 综上所...
返回两个参数:score和 diff: The score represents the structural similarity index between the two input images. This value can fall into the range [-1, 1] with a value of one being a “perfect match”. The diff image contains the actual image differences between the two input images that w...
structural_similarity() SRCC 0.5544, KRCC 0.3883 structural_similarity() with downsampling SRCC 0.7201, KRCC 0.5271 peak_signal_noise_ratio() SRCC 0.6869, KRCC 0.4958 So current code measures "perceptual simularity" even worse than simple MSE between images. 😞 Exact reasons for such behaviour ...
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scikit-image升级后改变了库函数的结构,函数 skimage.measure.compare_ssim已经被 skimage.metrics.structural_similarity 取代。 只需要将: 代码语言:javascript 复制 from skimage.measureimportcompare_ssim 修改为: 代码语言:javascript 复制 from skimage.metricsimportstructural_similarity ...
fromskimage.metricsimportstructural_similarity But I get the following in error logs: 2021-06-0306:45:04,266:ErrorrunningWSGIapplication2021-06-0306:45:04,273:ImportError:/home/vaya/.virtualenvs/ve/lib/python3.8/site-packages/scipy/special/../../scipy.libs/libopenblasp-r0-085ca80a.3.9.so:ca...
#from skimage.measure import structural_similarity as ssim from skimage import measure . . . #s = ssim(imageA, imageB) s = measure.compare_ssim(imageA
新的Python编程,并遇到一个问题,导入模块。我有一个导入的主应用程序(compare.py),如下所示:from skimage.measure import structural_similarityiofrom epilib import mse我在epilib中定义了两个函数当我执行‘pyt 浏览4提问于2015-08-26得票数 0 回答已采纳 ...
import name 'compare_ssim' from 'skimage.measure' 解决方案 scikit-image...升级后改变了库函数的结构,函数 skimage.measure.compare_ssim已经被 skimage.metrics.structural_similarity 取代。...只需要将: from skimage.measure import compare_ssim 修改为: from skimage.metrics import structural_similarity ...
返回两个参数:score和 diff: The score represents the structural similarity index between the two input images. This value can fall into the range [-1, 1] with a value of one being a “perfect match”. The diff image contains the actual image differences between the two input images that w...