ssahu’s gists

ssahu / keybase.md

Created March 2, 2019 03:47

keybase.md

I hereby claim:

To claim this, I am signing this object:

ssahu / git_config.txt

Created December 18, 2017 21:15

git config desktop

	#git config --list
	filter.lfs.clean=git-lfs clean -- %f
	filter.lfs.smudge=git-lfs smudge -- %f
	filter.lfs.process=git-lfs filter-process
	filter.lfs.required=true
	user.name=Sarthak Sahu
	[email protected]
	filter.lfs.process=git-lfs filter-process
	filter.lfs.required=true
	filter.lfs.clean=git-lfs clean -- %f

ssahu / HomographyDecomposition.as

Created October 17, 2017 20:44 — forked from inspirit/HomographyDecomposition.as

Decompose Homography into Rotation matrix & Translation vector

	var intrinsic:Vector.<Number> = new Vector.<Number>(9, true);
	var intrinsicInverse:Vector.<Number> = new Vector.<Number>(9, true);

	var R:Vector.<Number> = new Vector.<Number>( 9, true );
	var t:Vector.<Number> = new Vector.<Number>( 3, true );

	// SVD routine
	var svd:SVD = new SVD();

	// input homography[9] - 3x3 Matrix

ssahu / tensorflow_opencv_ubuntu_deps.sh.txt

Created May 7, 2017 05:18 — forked from CapCap/tensorflow_opencv_ubuntu_deps.sh.txt

Paperspace tensorflow+opencv setup for both python2 and python3 on ubuntu 16

	#!/bin/bash


	# Don't require you to constantly enter password for sudo:
	sudo visudo
	# In the bottom of the file, paste the following (without the `#`):
	# paperspace ALL=(ALL) NOPASSWD: ALL
	# Then press `ctl+o` then `enter` to save your changes, and `ctr+x` to exit nano

	# Allow connection from your IP to any port- default seems to be just 22 (ssh)

ssahu / classifier_from_little_data_script_1.py

Created April 19, 2017 23:12 — forked from fchollet/classifier_from_little_data_script_1.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

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

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 / 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 / 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 / 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), )

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