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@trusktr
trusktr / image-grid.md
Last active Jun 6, 2019
Image grid in Markdown
View image-grid.md
screen shot 2017-08-07 at 12 18 15 pm blah screen shot 2017-08-07 at 12 18 15 pm screen shot 2017-08-07 at 12 18 15 pm
screen shot 2017-08-07 at 12 18 15 pm screen shot 2017-08-07 at 12 18 15 pm <img width="1604" alt="screen shot 2017-08-07 at 12 18 15 pm" src="https:/
@oeway
oeway / imageUtils.py
Last active Aug 16, 2019
Improved image transform functions for dense predictions (for pytorch, keras etc.)
View imageUtils.py
import numpy as np
import scipy
import scipy.ndimage
from scipy.ndimage.filters import gaussian_filter
from scipy.ndimage.interpolation import map_coordinates
import collections
from PIL import Image
import numbers
__author__ = "Wei OUYANG"
@ksopyla
ksopyla / ubuntu16_tensorflow_cuda8.sh
Last active May 6, 2019
How to set up tensorflow with CUDA 8 cuDNN 5.1 in virtualenv with Python 3.5 on Ubuntu 16.04 http://ksopyla.com/2017/02/tensorflow-gpu-virtualenv-python3/
View ubuntu16_tensorflow_cuda8.sh
# This is shorthened version of blog post
# http://ksopyla.com/2017/02/tensorflow-gpu-virtualenv-python3/
# update packages
sudo apt-get update
sudo apt-get upgrade
#Add the ppa repo for NVIDIA graphics driver
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get update
@deboc
deboc / inria.py
Created Apr 21, 2016
Inria Person dataset for py-faster-rcnn
View inria.py
# Adapted the following lib/datasets/inria.py for py-faster-rcnn
# https://github.com/zeyuanxy/fast-rcnn/blob/master/lib/datasets/inria.py
# --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
@psycharo
psycharo / read_seq.py
Created May 15, 2014
reading .seq files from caltech pedestrian dataset
View read_seq.py
def read_seq(path):
def read_header(ifile):
feed = ifile.read(4)
norpix = ifile.read(24)
version = struct.unpack('@i', ifile.read(4))
length = struct.unpack('@i', ifile.read(4))
assert(length != 1024)
descr = ifile.read(512)
params = [struct.unpack('@i', ifile.read(4))[0] for i in range(0,9)]
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