Problems with resampling

[jingaoyin]

Thank you for the source code，They're really good.
But when I run the resampling code，The entire compressed file was found to be missing flow.npy，I wonder what kind of document this is，If it is a pre-trained model, the address you provided is no longer available for download, And how to use .pkl that you have trained.
Thank you so much for watching,And give me some help.

[hanchengyu3]

Hello, which version of tensorflow compatible environment needs to be configured, and has your problem been solved？ Thank you very much！

[nikhilparmar]

Thank you for the source code，They're really good. But when I run the resampling code，The entire compressed file was found to be missing flow.npy，I wonder what kind of document this is，If it is a pre-trained model, the address you provided is no longer available for download, And how to use .pkl that you have trained. Thank you so much for watching,And give me some help.

Hi, did you find the flow.npy file ?

[ZarrarAhmedKhan]

run this eval.py @nikhilparmar
change these

testImgPath = 'images/'
saveFlowPath = 'outputs'
image_name

`import torch
from torch.autograd import Variable
import torch.nn as nn
import skimage
import skimage.io as io
from torchvision import transforms
import numpy as np
from PIL import Image
import scipy.io as scio
import cv2
from resample.resampling import rectification
from modelNetM import EncoderNet, DecoderNet, ClassNet, EPELoss
transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))])
model_en = EncoderNet([1,1,1,1,2])
model_de = DecoderNet([1,1,1,1,2])
model_class = ClassNet()
if torch.cuda.device_count() > 1:
print("Let's use", torch.cuda.device_count(), "GPUs!")
model_en = nn.DataParallel(model_en)
model_de = nn.DataParallel(model_de)
model_class = nn.DataParallel(model_class)
if torch.cuda.is_available():
model_en = model_en.cuda()
model_de = model_de.cuda()
model_class = model_class.cuda()
model_en.load_state_dict(torch.load('models/model_en.pkl'), strict=False)
model_de.load_state_dict(torch.load('models/model_de.pkl'), strict=False)
model_class.load_state_dict(torch.load('models/model_class.pkl'), strict=False)
model_en.eval()
model_de.eval()
model_class.eval()

testImgPath = 'images/'
saveFlowPath = 'outputs'`

correct = 0

`
for k in range(1):

image_name = "1.jpg"
imgPath = testImgPath + image_name
disimgs = io.imread(imgPath)
disimgs = Image.open(imgPath).convert('RGB')
im_npy = np.asarray(disimgs.resize((256, 256)))
# disimgs.astype(np.float32)
# disimgs = cv2.resize(disimgs,(256,256), np.float32)
disimgs = transform(disimgs)

use_GPU = torch.cuda.is_available()
if use_GPU:
    disimgs = disimgs.cuda()

disimgs = disimgs.view(1,3,256,256)
disimgs = Variable(disimgs)

middle = model_en(disimgs)
flow_output = model_de(middle)
clas = model_class(middle)

_, predicted = torch.max(clas.data, 1)
if predicted.cpu().numpy()[0] == index:
    correct += 1

u = flow_output.data.cpu().numpy()[0][0]
v = flow_output.data.cpu().numpy()[0][1]

multi = 2
resImg, resMsk = rectification(im_npy, flow_output.data.cpu().numpy()[0]*multi)
img_out = Image.fromarray(resImg)

img_out.save('outputs/' + 'res_' + image_name)

# saveMatPath =  '%s%s%s%s%s%s' % (saveFlowPath, '/',types,'_', str(k).zfill(6), '.mat')
# scio.savemat(saveMatPath, {'u': u,'v': v}) `

[faviasono]

Hi, I don't have a GPU available. How can I make it work? I get error with cuda in the resampling file ... @xiaoyu258

[lzk9508]

Hi, I meet a bug during resampling.py as follow:
Traceback (most recent call last):
File "resampling.py", line 209, in
resImg, resMsk = rectification(distortedImg, flow)
File "resampling.py", line 194, in rectification
iterSearch[blockspergrid, threadsperblock](padu, padv, paddistorted, resultImg, maxIter, precision, resultMsk)
File "/home/liaozk/anaconda3/lib/python3.8/site-packages/numba/cuda/compiler.py", line 833, in call
kernel = self.specialize(*args)
File "/home/liaozk/anaconda3/lib/python3.8/site-packages/numba/cuda/compiler.py", line 844, in specialize
kernel = self.compile(argtypes)
File "/home/liaozk/anaconda3/lib/python3.8/site-packages/numba/cuda/compiler.py", line 863, in compile
kernel.bind()
File "/home/liaozk/anaconda3/lib/python3.8/site-packages/numba/cuda/compiler.py", line 604, in bind
self._func.get()
File "/home/liaozk/anaconda3/lib/python3.8/site-packages/numba/cuda/compiler.py", line 480, in get
ptx = self.ptx.get()
File "/home/liaozk/anaconda3/lib/python3.8/site-packages/numba/cuda/compiler.py", line 450, in get
ptx = nvvm.llvm_to_ptx(self.llvmir, opt=3, arch=arch,
File "/home/liaozk/anaconda3/lib/python3.8/site-packages/numba/cuda/cudadrv/nvvm.py", line 515, in llvm_to_ptx
ptx = cu.compile(**opts)
File "/home/liaozk/anaconda3/lib/python3.8/site-packages/numba/cuda/cudadrv/nvvm.py", line 232, in compile
self._try_error(err, 'Failed to compile\n')
File "/home/liaozk/anaconda3/lib/python3.8/site-packages/numba/cuda/cudadrv/nvvm.py", line 250, in _try_error
self.driver.check_error(err, "%s\n%s" % (msg, self.get_log()))
File "/home/liaozk/anaconda3/lib/python3.8/site-packages/numba/cuda/cudadrv/nvvm.py", line 140, in check_error
raise exc
numba.cuda.cudadrv.error.NvvmError: Failed to compile
(26, 54): parse expected comma after getelementptr's type
NVVM_ERROR_COMPILATION
@xiaoyu258

[psj-yyds]

run this eval.py

Thank you for your work, I also changed as you said, and ran eval.py only generated a picture, no .npy generated