test_mse.py

import os
import sys
import numpy as np

import glob
import fnmatch

import cv2

from keras.models import Sequential
from keras.layers import Dense
from keras.models import model_from_json

#from model import VGG_16

import theano
theano.config.openmp = True


from keras import backend as K
def get_activations(model, layer, X_batch):
    get_activations = K.function([model.layers[0].input, K.learning_phase()], model.layers[layer].output)
    activations = get_activations([X_batch,0])
    return activations


def loadImages(folder):
    imgs = []
    matches = []
    for root, dirnames, filenames in os.walk(folder):
        for filename in fnmatch.filter(filenames, '*'):
            matches.append(os.path.join(root, filename))
   
    return matches

batch_size = 1


def loadModel(home):
# load json and create model
    json_file = open('./erika.json', 'r')
    loaded_model_json = json_file.read()
    json_file.close()
    model = model_from_json(loaded_model_json)
    # load weights into new model
    model.load_weights("./erika_unstable.h5")
    return model


def test(home):
    model = loadModel(home)
    for imname in loadImages(sys.argv[1]):
        print(imname)
        src = cv2.imread(imname,cv2.IMREAD_GRAYSCALE)

        rows = int(src.shape[0]/16 + 1)*16
        cols = int(src.shape[1]/16 + 1)*16

    

        patch = np.empty((1,1,rows,cols),dtype="float32")
        patch[0,0,:,:] = np.ones((rows,cols),dtype="float32")*255.0
        patch[0,0,0:src.shape[0],0:src.shape[1]] = src

        out = model.predict(patch, batch_size=batch_size)
        if isinstance(out, list):
            out = out[0]

        result = np.zeros((rows,cols),dtype=np.float32)

        result = out[0,0,:,:] 
    
        print(np.amax(result), np.amin(result))

        result2 = cv2.normalize(result,0,255)

        head, tail = os.path.split(imname)
        #misc.imsave(sys.argv[2]+"/"+prefix+"_"+tail,result2[0:src.shape[0],0:src.shape[1]])

        result[result>255] = 255
        result[result<0] = 0
        cv2.imwrite(sys.argv[2]+"/"+tail+".png",result[0:src.shape[0],0:src.shape[1]])

if __name__ == "__main__":
    test(sys.argv[1])