Ejemplo n.º 1
0
def gera_GABOR_GLCM_LPB_features(sujeito):
    lstImagens = input.load_image('./Publication_Dataset/' + sujeito +
                                  '/TIFFs/8bitTIFFs/')

    volumeFeatures = []

    for imagem in lstImagens:
        frame_denoise = input.apply_filter(imagem, 'anisotropic')
        bdValue, new = flatten.flat_image(frame_denoise)
        crop = cropping.croppy_mona(new, bdValue)
        image_features = []

        image_features += features_extraction.apply_gabor(crop).tolist()
        crop2 = crop.astype(int)
        image_features += features_extraction.apply_glcm(crop2)
        image_features += features_extraction.apply_lbp(crop).tolist()

        volumeFeatures += image_features

        # features_extraction.apply_sift(crop)
        # lstSIFTFeatures.append(features_extraction.apply_sift(crop))

    print('gabor', len(volumeFeatures))
    # dictionary = features_extraction.apply_BOW(lstSIFTFeatures)
    fileObject = open('./gabor_glcm_lbp_repLine/' + sujeito, 'wb')
    if (fileObject != None):
        print('salvando...')
        pickle.dump(volumeFeatures, fileObject)
        fileObject.close
Ejemplo n.º 2
0
def testarEnquadramento():
    lstImagens = input.load_image(
        './Publication_Dataset/AMD6/TIFFs/8bitTIFFs/')

    for imagem in lstImagens:
        # frame_gauss = input.apply_filter(imagem,'gauss')
        frame_dif = input.apply_filter(imagem, 'anisotropic')
        bdValue, new = flatten.flat_image(frame_dif)
        crop = cropping.croppy_mona(new, bdValue)
Ejemplo n.º 3
0
def extractFeatures(sujeito):
    lstImagens = input.load_image('./base_interpol/' + sujeito)

    lstGeoFeatures = []

    for imagem in lstImagens:
        imagem = np.asarray(imagem)
        frame_denoise = input.apply_filter(imagem, 'anisotropic')
        bdValue, new = flatten.flat_image(frame_denoise)
        crop = cropping.croppy_mona(new, bdValue)
        lstGeoFeatures.append(geo.run((crop), [crop.shape[0], crop.shape[1]]))

    print('geo', len(lstGeoFeatures), len(lstGeoFeatures[0]))
    # dictionary = features_extraction.apply_BOW(lstSIFTFeatures)
    fileObject = open('./geo_features/' + sujeito, 'wb')
    if (fileObject != None):
        print('salvando...')
        pickle.dump(lstGeoFeatures, fileObject)
        fileObject.close
Ejemplo n.º 4
0
def geraGABORFeatures(sujeito):
    lstImagens = input.load_image('./Publication_Dataset/' + sujeito +
                                  '/TIFFs/8bitTIFFs/')

    lstGABORFeatures = []

    for imagem in lstImagens:
        frame_denoise = input.apply_filter(imagem, 'anisotropic')
        bdValue, new = flatten.flat_image(frame_denoise)
        crop = cropping.croppy_mona(new, bdValue)
        lstGABORFeatures.append(features_extraction.apply_gabor(crop).tolist())
        # features_extraction.apply_sift(crop)
        # lstSIFTFeatures.append(features_extraction.apply_sift(crop))

    print('gabor', len(lstGABORFeatures), len(lstGABORFeatures[0]))
    # dictionary = features_extraction.apply_BOW(lstSIFTFeatures)
    fileObject = open('./gabor_features/' + sujeito, 'wb')
    if (fileObject != None):
        print('salvando...')
        pickle.dump(lstGABORFeatures, fileObject)
        fileObject.close
Ejemplo n.º 5
0
        print('tam:', len(volumeInLine))
        featuresGeo.append(volumeInLine)
        vetLabelsGeo.append(getClass(vol))

    print('Gerando arff file for glcm', len(vetLabelsGeo), len(featuresGeo))
    arffGenerator.createArffFile('./geo_features/GEODATASET',
                                 featuresGeo, vetLabelsGeo, 'DME,NORMAL',
                                 len(featuresGeo[0]))


# getBaseFeatures()
# extractFeatures("DME7")
# loadFeatures()
# import math

lstImagens = input.load_image('./base_interpol/DME7')
imagem = lstImagens[2]
# print  lstImagens[3][79][1]
# print  lstImagens[3][76][0]
# map(lambda x: x if x<255 else 0, imagem)

imagem = np.asarray(imagem)
frame_denoise = input.apply_filter(imagem, 'anisotropic')
bdValue, new = flatten.flat_image(frame_denoise)

crop = cropping.croppy_mona(new, bdValue)
plt.figure()
plt.subplot(121)
plt.imshow(crop, 'gray')
plt.show()