train.py 文件源码

def dirClassificationSentiment(dirName, modelName, modelType):
    types = ('*.jpg', '*.png',)
    filesList = []
    for files in types:
        filesList.extend(glob.glob(os.path.join(dirName, files)))

    filesList = sorted(filesList)
    print filesList
    Features = []
    plt.close('all');    
    ax = plt.gca()
    plt.hold(True)
    for fi in filesList:
        P, classNames = fileClassification(fi, modelName, modelType)
        im = cv2.imread(fi, cv2.CV_LOAD_IMAGE_COLOR)    
        Width = 0.1;  Height = 0.1; startX = P[classNames.index("positive")]; startY = 0;
        myaximage = ax.imshow(cv2.cvtColor(im, cv2.cv.CV_RGB2BGR), extent=(startX-Width/2.0, startX+Width/2.0, startY-Height/2.0, startY+Height/2.0), alpha=1.0, zorder=-1)
        plt.axis((0,1,-0.1,0.1))
        plt.show(block = False);
        plt.draw()
    plt.show(block = True);