import numpy as np
import h5py
import cv2

def normalize_intrinsic(x,K):
    #print(x,K)
    return (x-K[:2,2])/np.diag(K)[:2]

def normalize_size(x,size,scale=1):
    size=size.reshape([1,2])
    norm_fac=size.max()
    return (x-size/2+0.5)/(norm_fac*scale)

def np_skew_symmetric(v):
    zero = np.zeros_like(v[:, 0])
    M = np.stack([
        zero, -v[:, 2], v[:, 1],
        v[:, 2], zero, -v[:, 0],
        -v[:, 1], v[:, 0], zero,
    ], axis=1)
    return M

def draw_points(img,points,color=(0,255,0),radius=3):
    dp = [(int(points[i, 0]), int(points[i, 1])) for i in range(points.shape[0])]
    for i in range(points.shape[0]):
        cv2.circle(img, dp[i],radius=radius,color=color)
    return img
    

def draw_match(img1, img2, corr1, corr2,inlier=[True],color=None,radius1=1,radius2=1,resize=None):
    if resize is not None:
        scale1,scale2=[img1.shape[1]/resize[0],img1.shape[0]/resize[1]],[img2.shape[1]/resize[0],img2.shape[0]/resize[1]]
        img1,img2=cv2.resize(img1, resize, interpolation=cv2.INTER_AREA),cv2.resize(img2, resize, interpolation=cv2.INTER_AREA) 
        corr1,corr2=corr1/np.asarray(scale1)[np.newaxis],corr2/np.asarray(scale2)[np.newaxis]
    corr1_key = [cv2.KeyPoint(corr1[i, 0], corr1[i, 1], radius1) for i in range(corr1.shape[0])]
    corr2_key = [cv2.KeyPoint(corr2[i, 0], corr2[i, 1], radius2) for i in range(corr2.shape[0])]

    assert len(corr1) == len(corr2)

    draw_matches = [cv2.DMatch(i, i, 0) for i in range(len(corr1))]
    if color is None:
        color = [(0, 255, 0) if cur_inlier else (0,0,255) for cur_inlier in inlier]
    if len(color)==1:
        display = cv2.drawMatches(img1, corr1_key, img2, corr2_key, draw_matches, None,
                              matchColor=color[0],
                              singlePointColor=color[0],
                              flags=4
                              )
    else:
        height,width=max(img1.shape[0],img2.shape[0]),img1.shape[1]+img2.shape[1]
        display=np.zeros([height,width,3],np.uint8)
        display[:img1.shape[0],:img1.shape[1]]=img1
        display[:img2.shape[0],img1.shape[1]:]=img2
        for i in range(len(corr1)):
            left_x,left_y,right_x,right_y=int(corr1[i][0]),int(corr1[i][1]),int(corr2[i][0]+img1.shape[1]),int(corr2[i][1])
            cur_color=(int(color[i][0]),int(color[i][1]),int(color[i][2]))
            cv2.line(display, (left_x,left_y), (right_x,right_y),cur_color,1,lineType=cv2.LINE_AA)
    return display