camera_reader_and_beautify.py 文件源码

def face_beautify(image,cascade, cascade2, processed_image):
    for (x, y, w, h) in processed_image:
        image1 = image[y:y+h, x:x+w]
        image_high = image1
        eyes = cascade2.detectMultiScale(image1)
        for (ex, ey, ew, eh) in eyes:
            center_x = ex + ew * 0.5
            center_y = ey + eh * 0.5
            eyes1 = image1[ey:ey+eh, ex:ex+ew]
            eyes2 = eyes1
            kernel_radius = min(ew, eh) * 0.4
            for r in range(eh):
                for c in range(ew):
                    diff_x = c - ew*0.5
                    diff_y = r - eh*0.5
                    distance = math.sqrt(diff_x * diff_x + diff_y * diff_y)
                    p_x = 0
                    p_y = 0
                    if distance <= kernel_radius:
                        re = (1 - math.cos(distance / kernel_radius * 2 * math.pi)) * 2.5
                        p_x = -diff_x * (re / kernel_radius)
                        p_y = -diff_y * (re / kernel_radius)
                    if p_x < 0 : 
                        p_x  = 0
                    if p_y < 0 : 
                        p_y = 0
                    eyes2[r,c] = eyes1[int(r + p_y),int(c + p_x)]
            image1[ey:ey+eh, ex:ex+ew] = eyes2  
        image_high1 = cv2.bilateralFilter(image_high, 15, 37, 37)
        #image_high2 = image_high1 - image1 + 128 
        image_high3 = cv2.GaussianBlur(image_high1,(1, 1),0)
        #image_high4 = image1 + 2 * image_high3 - 255
        #final = image1 * 0.45 + image_high4 * 0.55
        c_x = x + w * 0.5
        c_y = y + h * 0.5
        radius = min(w, h) * 2
        image_high4 = image_high3
        for row in range(h):
            for col in range(w):
                diff_x = col - w * 0.5
                diff_y = col - h * 0.5
                distance = math.sqrt(square(col - w*0.5) + square(row - h*0.5))
                m_x = 0
                m_y = 0
                if distance <= radius:
                    re = (1 - math.cos(distance / radius * 2 * math.pi)) * 2
                    m_x = -diff_x * (re / radius)
                    m_y = -diff_y * (re / radius)
                if m_x < 0:
                    m_x = 0
                if m_y < 0:
                    m_y = 0
                image_high4[row,col] = image_high3[int(row + m_y), int(col + m_x)]
        image[y:y+h, x:x+w] = image_high4
    return image