lab_global_optimisation.py 文件源码

def likelihood_map(prob_map,image) :
    '''This functon generates the likelihood map based on either obj-surr/dist model
       input: probability map
       output:likelihood map, an image(each pixel value=corresponding probability)'''

    global h_img,w_img,bin
    sf=256.0/bin
    image_10=image/sf 
    image_10=image_10.astype('uint8')
    # creating a likelihood image acc. to obj-surr or obj-distractor model
    a=image_10[:,:,0]
    a=a.ravel()
    b=image_10[:,:,1]
    b=b.ravel()
    c_=image_10[:,:,2]
    c_=c_.ravel()
    prob_image=prob_map[a,b,c_]
    prob_image=prob_image.reshape((h_img,w_img))
    prob_image1=prob_image*255
    prob_image1=prob_image1.astype('uint8')
    likemap=cv2.applyColorMap(prob_image1, cv2.COLORMAP_JET)
    return likemap,prob_image1