etrulls

require 'cutorch'
require 'cunn'

-- problem appears with two or more layers
model = nn.Sequential()
model:add( nn.SpatialConvolution(1,10,3,3) )
model:add( nn.SpatialConvolution(10,20,3,3) )
model:cuda()

print( 'This works' )

etrulls

require 'cutorch'
require 'cunn'
require 'cudnn'

torch.setnumthreads(1)
cutorch.setDevice(1)
torch.setdefaulttensortype('torch.FloatTensor')

-- model
c1 = nn.Sequential()

etrulls

| 27%   32C    P8    27W / 189W |     15MiB /  6143MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   5  GeForce GTX TIT...  Off  | 0000:89:00.0     Off |                  N/A |
| 27%   33C    P8    32W / 189W |     15MiB /  6143MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   6  GeForce GTX TIT...  Off  | 0000:8F:00.0     Off |                  N/A |
| 42%   66C    P2   123W / 189W |   3589MiB /  6143MiB |     99%      Default |
+-------------------------------+----------------------+----------------------+
|   7  GeForce GTX TIT...  Off  | 0000:90:00.0     Off |                  N/A |
| 52%   79C    P2   106W / 189W |   3340MiB /  6143MiB |      0%      Default |

etrulls

require 'lfs'
require 'xlua'

-- color output
colors = require 'ansicolors'
COL_LIGHTRED = '%{bright red}'
COL_DARKRED = '%{reset red}'
COL_LIGHTGREEN = '%{bright green}'
COL_DARKGREEN = '%{reset green}'
COL_LIGHTYELLOW = '%{bright yellow}'

etrulls

/cvlabdata1/home/eduard/soft/torch/torch-distro-icc/install/bin/luajit: .../torch-distro-icc/install/share/lua/5.1/nn/Container.lua:67:
In 1 module of nn.Sequential:
In 2 module of nn.ParallelTable:
In 4 module of nn.Sequential:
In 2 module of nn.Sequential:
...torch/torch-distro-icc/install/share/lua/5.1/nn/THNN.lua:110: bad argument #5 to 'v' (2D or 4D weight tensor expected, but got: [] at /cvlabdata1/home/eduard/soft/torch/torch-distro-icc/extra/nn/lib/THNN/generic/SpatialConvolutionMM.c:15)
stack traceback:
        [C]: in function 'v'
        ...torch/torch-distro-icc/install/share/lua/5.1/nn/THNN.lua:110: in function 'SpatialConvolutionMM_updateOutput'
        ...stro-icc/install/share/lua/5.1/nn/SpatialConvolution.lua:79: in function <...stro-icc/install/share/lua/5.1/nn/SpatialConvolution.lua:76>

etrulls

require 'nn'
require 'image'

desc = nn.Sequential()
desc:add( nn.SpatialConvolution( 1, 10, 3, 3, 1, 1 ) )
desc:add( nn.Tanh() )
desc:add( nn.SpatialLPPooling( 10, 2, 2, 2 ) )
desc:add( nn.SpatialSubtractiveNormalization( 10, image.gaussian(5) ) )
desc:add( nn.View( 10, -1 ) )

etrulls

def exhaustive(v):
    n = len(v)

    best = [None, None]
    max_sum = 1e-9
    for i in range(n):
        for j in range(i + 1, n):
            if sum(v[i:j + 1]) > max_sum:
                max_sum = sum(v[i:j + 1])
                best = [i, j + 1]

etrulls

import numpy as np
from colmap.scripts.python.read_model import read_model, qvec2rotmat
from colmap.scripts.python.read_dense import read_array
from imageio import imread
import matplotlib.pyplot as plt
import deepdish as dd
import h5py
import matplotlib.patches as patches
from time import time

etrulls

from glob import glob
import os
import sys

gpu = sys.argv[1]
seqs = sys.argv[2].split(',')

for i, seq in enumerate(seqs):
    src = '/cvlabdata1/cvlab/datasets_eduard/colmap'
    files = glob(f'{src}/{seq}/dense/images/*.jpg')

etrulls

diff --git a/src/compute_inliers_opt.py b/src/compute_inliers_opt.py
index 062c248..aca21e8 100644
--- a/src/compute_inliers_opt.py
+++ b/src/compute_inliers_opt.py
@@ -8,6 +8,7 @@ from utils import loadh5
 import cv2
 import glob
 from IPython import embed
+import os