Hi there,
I'm trying to translate this WORKING Python code for Neural Transfer Style on Java (Android). (the original work is from https://www.pyimagesearch.com/2018/08/27/neural-style-transfer-with-opencv/).
In python the test image shape is uint8 (479, 700, 3) and the output of the DNN is of shape float32 (1,3,480,700).
When I try converting the code to Java (see below), the resulting matrix I get is Mat [ -1*-1*CV_32FC1, isCont=true, isSubmat=true, nativeObj=0x75cf3fd9e0, dataAddr=0x75cea5e000 ], with rows = -1 and columns = -1. It also seems from CV_32FC1 that the output in Java has 1 float32 channel, while on python there are 3 I think. Maybe there's something I'm missing, but I don't know how to solve it.
I post below my working code in python and my initial tentative in Java.
I've searched a lot these days to find a solution, but I cannot find it, please help me!!! Thank you
PYTHON CODE
import cv2
import base64
import numpy as np
// read image directly from file, shape is uint8 (479, 700, 3)
img = cv2.imread("./testImages/bike.jpg")
// load dnn model
net = cv2.dnn.readNetFromTorch("./models/instance_norm/mosaic.t7")
// resize images if width > 700
h, w = img.shape[:2]
width = 700
if w <= width:
dim = (w, h)
else:
ratio = width / float(w)
dim = (width, int(h * ratio))
img = cv2.resize(img, dim, interpolation=cv2.INTER_AREA)
// Feed the neural net
blob = cv2.dnn.blobFromImage(img, 1.0, dim,
(103.939, 116.779, 123.680), swapRB=False, crop=False)
net.setInput(blob)
// Run neural network, out shape is float32 (1,3,480,700)
out = net.forward()
// Add back in the mean subtraction
// output shape is now float32 (3, 480, 700)
out = out.reshape((3, out.shape[2], out.shape[3]))
out[0] += 103.939
out[1] += 116.779
out[2] += 123.680
// output shape is now float32 (480, 700, 3)
out = out.transpose(1,2,0)
// convert image from BGR to RGB and avoid artifacts. output shape is now uint8 (480, 700, 3)
out = cv2.convertScaleAbs(cv2.cvtColor(out, cv2.COLOR_BGR2RGB))
JAVA CODE
// read image directly from file
Mat image = Imgcodecs.imread(filePath);
// load dnn model
Net net = Dnn.readNetFromTorch(modelPath);
// resize images if width > 700
int h = image.height();
int w = image.width();
int width = 700;
int height;
Mat resized;
if(w <= width) {
width = w;
height = h;
resized = image;
} else {
float ratio = width / (float) w;
height = (int)(h * ratio);
resized = new Mat();
Imgproc.resize(image, resized, new Size(width, height), 0, 0, Imgproc.INTER_AREA);
}
// Feed the neural net
net.setInput(Dnn.blobFromImage(resized,
1.0,
new Size(width, height),
new Scalar(103.939, 116.779, 123.680),
false,
false));
// I have problems here with the resulting matrix
Mat stylizedImage = net.forward();
Core.add(stylizedImage, new Scalar(103.939, 116.779, 123.680), stylizedImage);
// ....
