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help

could you please provide the trainning code ?

Here is small python inference code for denoise

Here I wrote python inference code for denoise, so one can use it as guideline:

import caffe

from PIL import Image
import numpy as np
import cv2



# load model

caffe.set_mode_cpu() # the model is very greedy for GPU ram, it does not want to work on my 4G GPU

net = caffe.Net('model/REDNet_ch1.prototxt','model/denoising/30.caffemodel', caffe.TEST)

img = np.array(Image.open('256x256.png').convert('YCbCr'))

y =img[...,0]
res8cb =img[...,1]
res8cr = img[...,2]


img = y/255.0

net.blobs['data'].reshape(*(1,1, img.shape[0], img.shape[1]))



img_out = np.zeros(shape=(img.shape[0], img.shape[1],8), dtype=np.float32);

for i in range(1, 5):
    i1 = np.rot90(img, i-1)[np.newaxis, np.newaxis,...]
    net.blobs['data'].data[...] = i1
    net.forward()
    res = net.blobs['d15'].data[...]

    img_out[:,:,i-1] = np.rot90(res[0,0,:,:], 5-i) + img;

    print('-')
for i in range(5, 8):
    i1 = np.rot90(np.fliplr(img), i-5)[np.newaxis, np.newaxis,...]
    net.blobs['data'].data[...] = i1
    net.forward()
    res = net.blobs['d15'].data[...]

    img_out[:,:,i-1] = np.rot90(res[0,0,:,:], 9-i) + img;
    print('-')



img_out = np.mean(img_out,axis=-1);


res8y = (img_out*255.0).astype(np.uint8)






# Optional: color histogram becomes dark, need to fix it.
# But this may highlight remaining noise


clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))
res8y = clahe.apply(res8y)




res_out = np.concatenate([res8y[...,np.newaxis], res8cb[...,np.newaxis], res8cr[...,np.newaxis]], axis=-1)

Image.fromarray(res_out, mode='YCbCr').convert('RGB').save('out.png')

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