def main(args):
srcnn = SRCNN(
image_size=args.image_size,
c_dim=args.c_dim,
is_training=False)
X_pre_test, X_test, Y_test, color = load_test(scale=args.scale)
predicted_list = []
for img in X_test:
predicted = srcnn.process(img.reshape(1,img.shape[0],img.shape[1],1))
predicted_list.append(predicted.reshape(predicted.shape[1],predicted.shape[2],1))
n_img = len(predicted_list)
dirname = './result'
for i in range(n_img):
imgname = 'image{:02}'.format(i)
# print(color[i].shape)
# print(predicted_list[i].clip(min=0, max=255))
# print(np.concatenate((predicted_list[i] / 255.0, color[i] / 255.0), axis=2))
# cv2.imshow('result', X_test[i])
# cv2.imshow('result', cv2.cvtColor(np.concatenate((Y_test[i], color[i]), axis=2), cv2.COLOR_YCrCb2BGR))
# cv2.imshow('result', cv2.cvtColor(np.concatenate((predicted_list[i] / 255.0, color[i] / 255.0), axis=2).astype(np.float32), cv2.COLOR_YCrCb2BGR))
# cv2.waitKey(0)
cv2.imwrite(os.path.join(dirname,imgname+'_original.bmp'), X_pre_test[i])
cv2.imwrite(os.path.join(dirname,imgname+'_input.bmp'), cv2.cvtColor(np.concatenate((X_test[i], color[i]), axis=2), cv2.COLOR_YCrCb2BGR))
cv2.imwrite(os.path.join(dirname,imgname+'_answer.bmp'), cv2.cvtColor(np.concatenate((Y_test[i], color[i]), axis=2), cv2.COLOR_YCrCb2BGR))
float_predicted = (predicted_list[i] / 255.0).clip(min=0., max=1.).astype(np.float64)
normalized_predicted = np.expand_dims(cv2.normalize(float_predicted, None, 255, 0, cv2.NORM_MINMAX, cv2.CV_8UC1), axis=2)
print(normalized_predicted.shape)
cv2.imwrite(os.path.join(dirname,imgname+'_predicted.bmp'), cv2.cvtColor(np.concatenate((normalized_predicted, color[i]), axis=2), cv2.COLOR_YCrCb2BGR))
def main(args):
srcnn = SRCNN(
image_size=args.image_size,
c_dim=args.c_dim,
is_training=False)
X_pre_test, X_test, Y_test = load_test(scale=args.scale)
predicted_list = []
for img in X_test:
predicted = srcnn.process(img.reshape(1,img.shape[0],img.shape[1],1))
predicted_list.append(predicted.reshape(predicted.shape[1],predicted.shape[2],1))
n_img = len(predicted_list)
dirname = './static'
for i in range(n_img):
imgname='image00'
#imgname = 'image{:02}'.format(i)
#cv2.imwrite(os.path.join(dirname,imgname+'_original.bmp'), X_pre_test[i])
cv2.imwrite(os.path.join(dirname,imgname+'_input.bmp'), X_test[i])
cv2.imwrite(os.path.join(dirname,imgname+'_answer.bmp'), Y_test[i])
