morphology_test.py

import numpy as np
import cv2
import time
import torch
import torch.nn.functional as F

kernel = np.ones((41, 41) ).astype(np.float32)
cv_input = (np.random.random(size=(500,500))>0).astype(np.float32)

kernel_tensor = torch.Tensor(kernel).cuda().unsqueeze(0).unsqueeze(0)  
torch_input = torch.Tensor(cv_input).cuda().unsqueeze(0).unsqueeze(0) 
padding = (int(41/2), int(41/2))

t = time.time()
for i in range(100):
    for _ in range(10):
        cv_input = cv2.morphologyEx(cv_input, cv2.MORPH_CLOSE, kernel )
print("cv",time.time()-t)

t = time.time()    
for i in range(100):    
    for _ in range(10):
        torch_input  = 1-torch.clamp(F.conv2d(1-torch.clamp(F.conv2d(torch_input, kernel_tensor, padding=padding), 0, 1), kernel_tensor, padding=padding), 0, 1)
print("cuda",time.time()-t)