qinhaifangpku
commented
5 years ago I guess the image should be resize to (437, 437) either?
I use the code beyond could genrate the edge.
python code
import cv2 import numpy as np from matplotlib import pyplot as plt import numpy as np import sys
import os
img_path = sys.argv[2] #parsing_annotation maps out_path = sys.argv[3] #result used for training and prediction out_vis_path = sys.argv[4] #just for visulization with open(sys.argv[1], 'r') as fin: # val_id.txt lines = fin.readlines() for line in lines: ids = line.strip('\n') + '.png' img = cv2.imread(os.path.join(img_path, ids)) sobelx = cv2.Sobel(img,cv2.CV_64F,1,0) # Find x and y gradients sobely = cv2.Sobel(img,cv2.CV_64F,0,1)
# Find magnitude and angle
magnitude = np.sqrt(sobelx**2.0 + sobely**2.0)
angle = np.arctan2(sobely, sobelx) * (180 / np.pi)
magnitude[np.where(magnitude > 0)] = 1
temp = magnitude.astype(np.uint8)
cv2.imwrite(os.path.join(out_path, line.strip('\n')+'.png'), temp)
cv2.imwrite(os.path.join(out_vis_path, line.strip('\n')+'.png'), temp*255.0)
LayneH
rxqy
Hi, thanks for open-soursing this work.
I found that the sizes of edge ground truth you provide are always 473x473, which raises an exception when batch size is greater than 1. I resize the edge GT before it further being processed, which solves this problem.
However, doing this will result in inaccurate edge GT (since the edge GT is interpolated). I was wondering if you could give some details about edge generation or kindly share your code of generating edge GT.