텐서보드로 파이토치 학습 모니터링 하기
파이썬으로 Homomorphic Filtering 하기
import cv2 # For OpenCV modules (For Image I/O and Contour Finding) import numpy as np # For general purpose array manipulation import scipy . fftpack # For FFT2 #### imclearborder definition def imclearborder ( imgBW , radius ): # Given a black and white image, first find all of its contours imgBWcopy = imgBW . copy () contours , hierarchy = cv2 . findContours ( imgBWcopy . copy (), cv2 . RETR_LIST , cv2 . CHAIN_APPROX_SIMPLE ) # Get dimensions of image imgRows = imgBW . shape [ 0 ] imgCols = imgBW . shape [ 1 ] contourList = [] # ID list of contours that touch the border # For each contour... for idx in np . arange ( len ( contours )): # Get the i'th contour cnt = contours [ idx ] # Look at each point in the contour for pt in cnt : rowCnt = pt [ 0 ][ 1 ] colCnt = pt [ 0 ][ 0 ] # If this is within the radius of th...
#============ TensorBoard logging ============#
답글삭제# (1) Log the scalar values
info = {
'loss': loss.data[0],
'accuracy': accuracy.data[0]
}
for tag, value in info.items():
logger.scalar_summary(tag, value, step+1)
# (2) Log values and gradients of the parameters (histogram)
for tag, value in net.named_parameters():
tag = tag.replace('.', '/')
logger.histo_summary(tag, to_np(value), step+1)
logger.histo_summary(tag+'/grad', to_np(value.grad), step+1)
# (3) Log the images
info = {
'images': to_np(images.view(-1, 28, 28)[:10])
}
for tag, images in info.items():
logger.image_summary(tag, images, step+1)