save_all_images.py

"""
Run this script if you wish to save the images for any further use
and not load it as a MAT file
"""

import h5py
import os
import numpy as np
import cv2

matPath = './data/nyu_depth_v2_labeled.mat'
img_folder = 'imgs'
dep_folder = 'deps'

if not os.path.exists(img_folder):
    os.makedirs(img_folder)
if not os.path.exists(dep_folder):
    os.makedirs(dep_folder)

f = h5py.File(matPath)

img_dim = 224

def save_image_dep(image_id):
    i = image_id
    print "Processing",i
    img = f['images'][i]
    depth = f['depths'][i]
    img_=np.empty([img_dim,img_dim,3])
    img_[:,:,0] = cv2.resize(img[2,:,:].T,(img_dim,img_dim))
    img_[:,:,1] = cv2.resize(img[1,:,:].T,(img_dim,img_dim))
    img_[:,:,2] = cv2.resize(img[0,:,:].T,(img_dim,img_dim))
    depth_ = np.empty([img_dim, img_dim, 3])
    depth_[:,:,0] = cv2.resize(depth[:,:].T,(img_dim,img_dim))
    depth_[:,:,1] = cv2.resize(depth[:,:].T,(img_dim,img_dim))
    depth_[:,:,2] = cv2.resize(depth[:,:].T,(img_dim,img_dim))
    img_ = img_#/255.0
    print np.amax(depth_)
    depth_ = 255.*cv2.normalize(depth_, 0, 255, cv2.NORM_MINMAX)

    cv2.imwrite(os.path.join(img_folder,'img_{}.jpg'.format(i)), img_)
    cv2.imwrite(os.path.join(dep_folder,'dep_{}.jpg'.format(i)), depth_)


map(save_image_dep, range(len(f['images'])))