U ?h@sddlZddlZedddlmZmZmZmZddZ ddZ dd Z d d Z d d Z ddZddZddZddZddZddZddZddZdS)NZsklearn) learn_gmm fisher_vectorFisherVectorExceptionDescriptorExceptionc Cs&tttdddW5QRXdS)z\Test that DescriptorException is raised when wrong type for descriptions is passed. zcompletely wrong testn_modesNpytestraisesrrr r Z/var/www/html/venv/lib/python3.8/site-packages/skimage/feature/tests/test_fisher_vector.py"test_gmm_wrong_descriptor_format_1 s rc Cs6tt"ttdtdgddW5QRXdS)zbTest that DescriptorException is raised when descriptors are of different dimensionality. )  rrNr r rrnpzerosr r r r "test_gmm_wrong_descriptor_format_2s rc Cs6tt"ttdtdgddW5QRXdS)zXTest that DescriptorException is raised when not all descriptors are of rank 2. rr)rrrrrNrr r r r "test_gmm_wrong_descriptor_format_3s rc Cs6tt"tdddgdddggddW5QRXdS)zTest that DescriptorException is raised when elements of descriptor list are of the incorrect type (i.e. not a NumPy ndarray). rrNr r r r r "test_gmm_wrong_descriptor_format_4(s rc Cs6tt"ttdtdgddW5QRXdS)zyTest that FisherVectorException is raised when incorrect type for n_modes is passed into the learn_gmm function. rrZ not_validrNr r rrrrr r r r !test_gmm_wrong_num_modes_format_11s rc Cs6tt"ttdtdgddW5QRXdS)zTest that FisherVectorException is raised when a number that is not a positive integer is passed into the n_modes argument of learn_gmm. rrrNrr r r r !test_gmm_wrong_num_modes_format_2:s r c Cs4tt ttjddddidW5QRXdS)zqTest that FisherVectorException is raised when wrong covariance type is passed in as a keyword argument. rrrcovariance_typefullrZgm_argsN)r r rrrrandomr r r r test_gmm_wrong_covariance_typeCs   r&cCsHttjddddid}|jdk s(t|jdk s6t|jdk sDtdS)ztTest that GMM estimation is successful when the correct covariance type is passed in as a keyword argument. r!rr"Zdiagr$Nrrr%Zmeans_AssertionErrorZ covariances_Zweights_gmmr r r test_gmm_correct_covariance_typeOs r+cCsBttjddd}|jdk s"t|jdk s0t|jdk s>tdS)a Test the GMM estimation. Since this is essentially a wrapper for the scikit-learn GaussianMixture class, the testing of the actual inner workings of the GMM estimation is left to scikit-learn and its dependencies. We instead simply assert that the estimation was successful based on the fact that the GMM object will have associated mixture weights, means, and variances after estimation is successful/complete. )d@rrNr'r)r r r test_gmm_e2e^s r.c Cs^zddlm}Wntk r,tdYnXtttddddgg|W5QRXdS) z Test that DescriptorException is raised when the incorrect type for the descriptors is passed into the fisher_vector function. rGaussianMixturezmscikit-learn is not installed. Please ensure it is installed in order to use the Fisher vector functionality.rrrrN)Zsklearn.mixturer0 ImportErrorprintr r rrr/r r r test_fv_wrong_descriptor_typesqs  r3c Cs:Gddd}ttttd|W5QRXdS)z Test that FisherVectorException is raised when a GMM not of type sklearn.mixture.GaussianMixture is passed into the fisher_vector function. c@s eZdZdS)z:test_fv_wrong_gmm_type..MyDifferentGaussianMixtureN)__name__ __module__ __qualname__r r r r MyDifferentGaussianMixturesr7r!N)r r rrrr)r7r r r test_fv_wrong_gmm_types r8cs\dd}d||}fddtdD}t||d}t|d|}t||ksXtd S) a Test the Fisher vector computation given a GMM returned from the learn_gmm function. We simply assert that the dimensionality of the resulting Fisher vector is correct. The dimensionality of a Fisher vector is given by 2KD + K, where K is the number of Gaussians specified in the associated GMM, and D is the dimensionality of the descriptors using to estimate the GMM. rcs&g|]}tjtjddfqSrrr%randint.0_dimr r sztest_fv_e2e..rrrNrangerrlenr(Z num_modesZ expected_dimZ descriptorsr*Z fisher_vecr rBr test_fv_e2es   rIcs`dd}d||}fddtdD}t||d}t|d|d d }t||ks\td S) a Test the improved Fisher vector computation given a GMM returned from the learn_gmm function. We simply assert that the dimensionality of the resulting Fisher vector is correct. The dimensionality of a Fisher vector is given by 2KD + K, where K is the number of Gaussians specified in the associated GMM, and D is the dimensionality of the descriptors using to estimate the GMM. r9r:rcs&g|]}tjtjddfqSr;r=r?rBr r rDsz(test_fv_e2e_improved..rrrT)ZimprovedNrErHr rBr test_fv_e2e_improveds   rJ)r numpyrZ importorskipZskimage.feature.fisher_vectorrrrrrrrrrr r&r+r.r3r8rIrJr r r r s