flow_ x+flow_ y---RGB

#coding:utf -8
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
from PIL import Image
import numpy as np
import math
from numba import jit
import cv2
import time
import glob
from sklearn.preprocessing import MinMaxScaler
np.seterr(divide='ignore',invalid='ignore')

def flow_rgb(x_img,y_img):
    n,m=np.array(x_img).shape
    fuzhi=np.zeros((n,m))
    rgb = np.zeros((n,m,3))
    i=0
    j=0
    while i <n:
        while j<m:
            fuzhi[i,j]=math.sqrt(math.pow(x_img[i,j],2)+math.pow(y_img[i,j],2))
            j+=1
        i+=1
        j=0
    #print fuzhi
    #x_img.show()
# Turn into RGB picture , And normalize ( Subtract the maximum value of the changed channel pixels from the pixels of each channel )    
rgb[:, :, 0] = (x_img- np.ones((n,m))*np.min(x_img)) *1.0 / ( np.ones((n,m))*np.max(x_img) - np.ones((n,m))*np.min(x_img) )
    rgb[:, :, 1] = (y_img- np.ones((n,m))*np.min(y_img)) *1.0 / ( np.ones((n,m))*np.max(y_img) - np.ones((n,m))*np.min(y_img) )
    rgb[:, :, 2] = (fuzhi- np.ones((n,m))*np.min(fuzhi)) *1.0 / ( np.ones((n,m))*np.max(fuzhi) - np.ones((n,m))*np.min(fuzhi) )
    rgb_255=(rgb*225)
    rgb_255 =rgb_255.astype(np.uint8)
    rgb_255 = cv2.cvtColor(rgb_255, cv2.COLOR_BGR2RGB)
    #cv2.imshow('rgb_quanju',rgb_255)
    #cv2.waitKey()
    return rgb_255

path='/media/xuguohan/Elements/shajie/dataset/IsoGD_flows/'
save_path='/media/xuguohan/E/shajie/image/GD/IsoGD/isogd_flow_rgb'
dataset='train'
path=os.path.join(path,dataset)
save_path=os.path.join(save_path,dataset)
if os.path.exists(save_path) is False:
    os.makedirs(save_path)
wenjians=os.listdir(path)#'001'...'010'...'100'
for wenjian in wenjians:#'001'
    wenjian_read=os.path.join(path,wenjian)#'/media/xuguohan/Elements/shajie/dataset/IsoGD_frames/train/001'
    wenjain_save=os.path.join(save_path,wenjian)#'/media/xuguohan/E/shajie/image/GD/IsoGD/isogd_flow_rgb/train/001'
    if os.path.exists(wenjain_save) is False:
        os.makedirs(wenjain_save)
    www=os.listdir(wenjian_read)#'K_00001'...'M_00121'...
    for KM in www:
        if KM.split('_')[0]=='M':#'M_00065'
            M_path=os.path.join(wenjian_read,KM)#'./IsoGD_frames/train/001/M_00065'
            M_path_save=os.path.join(wenjain_save,KM)#'./isogd_flow_rgb/train/001/M_00065'
            if os.path.exists(M_path_save) is False:
                os.makedirs(M_path_save)
            frame_name=os.listdir(M_path)#'flow_y_0005.jpg'...'img_0011.jpg'...'flow_x_0002.jpg'
            for frame_one in frame_name:
                if frame_one.split('_')[1]=='x':#frame_one.split('_')=['flow', 'x', '0001.jpg']
                    x_split=frame_one.split('x')#['flow_', '_0001.jpg']
                    flow_y=x_split[0]+'y'+x_split[-1]
                    flow_x_path = os.path.join(M_path,frame_one)#'./train/001/M_00065/flow_x_0001.jpg'
                    flow_y_path = os.path.join(M_path, flow_y)#'./train/001/M_00065/flow_y_0001.jpg'
                    flow_x = cv2.imread(flow_x_path, 0)
                    flow_y = cv2.imread(flow_y_path, 0)
                    rgb=flow_rgb(flow_x, flow_y)
                    rgb_name='img_{}'.format(x_split[-1])

                    rgb_path = os.path.join(M_path_save, rgb_name)
                    print rgb_path
                    if os.path.exists(rgb_path):
                        print 'rgb_path exists'
                        pass
                    else:
                        print 'rgb_path save'
                        cv2.imwrite(rgb_path, rgb)