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Sarthak Sahu ssahu

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ssahu / gist:10276944
Created April 9, 2014 14:29 — forked from frederikhermans/gist:8561382

Installing opencv fails, even though $ brew doctor doesn't have any complaints:

$ brew install opencv
==> Downloading https://github.com/Itseez/opencv/archive/2.4.7.1.tar.gz
Already downloaded: /Library/Caches/Homebrew/opencv-2.4.7.1.tar.gz
==> Patching
patching file cmake/OpenCVFindOpenNI.cmake
Warning: Formula#python is deprecated and will go away shortly.
Error: undefined method `incdir' for #<PythonDependency: "python" []>
@ssahu
ssahu / gist:10288217
Created April 9, 2014 16:18 — forked from gcatlin/gist:1847248
brew update
brew versions FORMULA
cd `brew --prefix`
git checkout HASH Library/Formula/FORMULA.rb # use output of "brew versions"
brew install FORMULA
brew switch FORMULA VERSION
git checkout -- Library/Formula/FORMULA.rb # reset formula
## Example: Using Subversion 1.6.17
#
@ssahu
ssahu / latency.txt
Created May 15, 2014 20:34 — forked from jboner/latency.txt
Latency Comparison Numbers
--------------------------
L1 cache reference 0.5 ns
Branch mispredict 5 ns
L2 cache reference 7 ns 14x L1 cache
Mutex lock/unlock 25 ns
Main memory reference 100 ns 20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy 3,000 ns
Send 1K bytes over 1 Gbps network 10,000 ns 0.01 ms
Read 4K randomly from SSD* 150,000 ns 0.15 ms
@ssahu
ssahu / fb_profile_img.sh
Created June 13, 2015 00:03
Download fb-profile-images
#!/bin/bash
# This script downloads the profile images of facebook profile ids from 1 to 10
# change the start and end ids and use it - does not require any login
for i in {1..10}; do wget http://graph.facebook.com/picture?id=$i&width=10000 -O $i.jpg; done
@ssahu
ssahu / 6986.lines.json
Last active August 29, 2015 14:24
6986.lines.json
{"lines":[{"pid":[0],"image":67522,"s":[366.1640625,1093.109375],"e":[653.8359375,377.515625]},{"pid":[0],"image":67522,"s":[398.8359375,1061.234375],"e":[631.5234375,487.484375]},{"pid":[0],"image":67522,"s":[688.1015625,367.953125],"e":[1061.8359375,916.203125]},{"pid":[0],"image":67522,"s":[698.4609375,420.546875],"e":[1036.3359375,918.59375]},{"pid":[0],"image":67522,"s":[467.3671875,1022.1875],"e":[668.9765625000001,525.734375]},{"pid":[0],"image":67522,"s":[428.3203125000001,1161.6406250000002],"e":[425.1328125000001,1404.6875000000002]},{"pid":[0],"image":67522,"s":[1179.7734375,1113.03125],"e":[1181.3671875,1643.75]},{"pid":[0,1],"image":67522,"s":[1981.4296875,1152.8749999999995],"e":[1981.4296875,1340.9374999999995]},{"pid":[1],"image":67522,"s":[2141.6015625,1093.9062499999986],"e":[2326.4765625,889.1093749999986]},{"pid":[1],"image":67522,"s":[2198.1796875,1067.6093749999986],"e":[2316.9140625,934.5312499999986]},{"pid":[1],"image":67522,"s":[2344.8046875,892.2968749999986],"e":[2482.6640625,1076.
@ssahu
ssahu / min-char-rnn.py
Last active August 29, 2015 14:26 — forked from karpathy/min-char-rnn.py
Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy
"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np
# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
print '%d unique characters in data.' % (len(chars), )
@ssahu
ssahu / notes.txt
Last active November 20, 2015 08:17
install caffe notes - el capitan, matlab r2012a, etc cpu mode only
instructions to set paths after installing mkl
file:///opt/intel/documentation_2016/en/ps2016/getstart_comp_mc.htm
sudo vi /opt/intel/composer_xe_2015/tbb/bin/tbbvars.sh
change == to '=='
disable system integration protection for el capitan: csrutil disable
to use the fallback library path
add the following to the bashrc/zshrc
export DYLD_FALLBACK_LIBRARY_PATH=/usr/local/lib:/usr/lib:/opt/intel/composer_xe_2015.2.132/compiler/lib:/opt/intel/composer_xe_2015.2.132/mkl/lib
@ssahu
ssahu / remove-docker.sh
Created November 20, 2015 07:59
uninstall docker completely
boot2docker stop
boot2docker delete
sudo rm /usr/local/bin/docker
sudo rm /usr/local/bin/boot2docker
sudo rm /usr/local/share/boot2docker/boot2docker.iso
sudo rmdir /usr/local/share/boot2docker
rm -rf ~/.boot2docker
rm ~/.ssh/id_boot2docker*
sudo rm -f /private/var/db/receipts/io.boot2docker.*
sudo rm -f /private/var/db/receipts/io.boot2dockeriso.*
@ssahu
ssahu / classifier_from_little_data_script_3.py
Last active January 14, 2018 07:53 — forked from fchollet/classifier_from_little_data_script_3.py
Fine-tuning a Keras model. Updated to the Keras 2.0 API.
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats
@ssahu
ssahu / classifier_from_little_data_script_2.py
Created April 19, 2017 23:10 — forked from fchollet/classifier_from_little_data_script_2.py
Updated to the Keras 2.0 API.
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats