show = False
img_size = 1024
RADIUS = 512
FRAMES = 1
offset = 0
add_mark = False
#offset = 50
#add_mark = True

    
Image_Correlator = get_context().getClassByName("Image_Correlator")
correlator = Image_Correlator()



def get_roi_img(radius, offset_x=0, offset_y=0, frames=1):
    x,y,w,h = int(cover_detection.config.center_x-img_size/2 + offset_x), \
              int(cover_detection.config.center_y-img_size/2 + offset_y), \
              img_size, img_size
    if frames>1:
        ip = integrate_frames(samples = frames)
        roi = ImagingUtils.copy(ip.getBufferedImage(), None, Rectangle(x,y,w,h))     
    else:
        roi = ImagingUtils.copy(image.output, None, Rectangle(x,y,w,h))     
    ip = load_image(roi, title="Img")     
    p = ip.getProcessor()
    mask = p.createProcessor(roi.getWidth(), roi.getHeight()) 
    mask.setColor(255)  
    cx, cy = img_size/2 - offset_x, img_size/2 - offset_y
    mask.fillOval(int(cx - radius), int(cy - radius), int(2 * radius), int(2 * radius))  # Draw the circular ROI
    mask.autoThreshold()  # Ensures the mask is binary (if needed)
    p.copyBits(mask, 0, 0, Blitter.AND)  # Apply the mask using a bitwise AND    
    #gaussian_blur(ip)
    p.blurGaussian(1.0)
    return ip.getBufferedImage()

def get_edge_img(ib):
    ed = ImagingUtils.edgeDetect(ib)    
    ret = load_image(ed, title="Refe")
    #auto_threshold(ret, dark_background=True)
    #binary_dilate(ret,  iterations=1, count=1)
    return ret
    
def put_mark(ib):
    for x in range(450, 470):
        for y in range(450, 470):
            ib.setRGB(x,y, 0)




def load_ref_img(reload = False, frames=FRAMES):    
    global ip_ref, ip_ref_e, ip_ref_f, ip_ref_fe
    if reload or "ip_ref_fe" not in globals():        
        print "Loading cover reference image"
        roi =get_roi_img(RADIUS, 0, 0, frames)
        ip_ref = load_image(roi, title="Ref")    
        ip_ref_e =get_edge_img(roi)
        ip_ref_f = image_fft(ip_ref)
        ip_ref_fe = image_fft(ip_ref_e)

load_ref_img()

def load_cur_img(frames=FRAMES):    
    global ip_cur, ip_cur_e, ip_cur_f, ip_cur_fe
    roi =get_roi_img(RADIUS, -offset, -offset, frames)
    if add_mark:
        put_mark(roi)    
    ip_cur = load_image(roi, title="Ref")    
    ip_cur_e =get_edge_img(roi)
    ip_cur_f = image_fft(ip_cur)
    ip_cur_fe = image_fft(ip_cur_e)

load_cur_img()


#show_panel(ip1e.getBufferedImage())
#show_panel(ip2e.getBufferedImage())

coef_img, _ = correlator.getCorrelation(ip_ref, ip_cur)
coef_ed, _ = correlator.getCorrelation(ip_ref_e, ip_cur_e)
coef_fft, _ = correlator.getCorrelation(ip_ref_f, ip_cur_f)
coef_ffte, _ = correlator.getCorrelation(ip_ref_fe, ip_cur_fe)

#show_panel(sub1)

#sub = ImagingUtils.sub(BufferedImage, BufferedImage, boolean)

#sub = load_image(sub, title="sub") 
#sube = load_image(sube, title="sube") 

if show:
    st=create_stack([ip_ref, ip_cur, ip_ref_e, ip_cur_e, ip_ref_f, ip_cur_f, ip_ref_fe, ip_cur_fe])
    st.show()


def get_min(ip1):
    return ip1.getProcessor().getStatistics().min

def mean_abs_error(ip1, ip2):
    sum = 0.0
    for y in range(ip1.getHeight()):
        for x in range(ip1.getWidth()):
            p1 = ip1.getPixel(x, y)
            p2 = ip2.getPixel(x, y)
            sum +=  abs(p1 - p2)
    return sum / (ip1.height  * ip1.width )         

def rms_error(ip1, ip2):
    sum = 0.0
    for y in range(ip1.getHeight()):
        for x in range(ip1.getWidth()):
            p1 = ip1.getPixel(x, y)
            p2 = ip2.getPixel(x, y)
            sum +=    math.pow((p1 - p2),2)
    return sum / (ip1.height  * ip1.width )         


mean_err, mean_erre = mean_abs_error(ip_ref_f.getProcessor(), ip_cur_f.getProcessor()),  mean_abs_error(ip_ref_fe.getProcessor(), ip_cur_fe.getProcessor())
rms_err, rms_erre = rms_error(ip_ref_f.getProcessor(), ip_cur_f.getProcessor()),  rms_error(ip_ref_fe.getProcessor(), ip_cur_fe.getProcessor())

if show:
    #print offset, coef_img, coef_ed, coef_fft, coef_ffte
    print  coef_fft, coef_ffte  
    print  mean_err, mean_erre
    print  rms_err, rms_erre