jdsgomes

Deep Learning for Face Recognition (May 2016)

Popular architectures

• FaceNet (Google)
  • They use a triplet loss with the goal of keeping the L2 intra-class distances low and inter-class distances high
• DeepID (Hong Kong University)
  • They use verification and identification signals to train the network. Afer each convolutional layer there is an identity layer connected to the supervisory signals in order to train each layer closely (on top of normal backprop)
• DeepFace (Facebook)
  • Convs followed by locally connected, followed by fully connected

karpathy

"""
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))
data_size, vocab_size = len(data), len(chars)

yohhoy

https://www.ffmpeg.org/doxygen/trunk/dump_8c_source.html#l00454

• fps = st->avg_frame_rate
• tbr = st->r_frame_rate
• tbn = st->time_base
• tbc = st->codec->time_base

AVStream::avg_frame_rate

Average framerate.

• demuxing: May be set by libavformat when creating the stream or in avformat_find_stream_info().
• muxing: May be set by the caller before avformat_write_header().

brandonb927

#!/bin/sh

###
# SOME COMMANDS WILL NOT WORK ON macOS (Sierra or newer)
# For Sierra or newer, see https://github.com/mathiasbynens/dotfiles/blob/master/.macos
###

# Alot of these configs have been taken from the various places
# on the web, most from here
# https://github.com/mathiasbynens/dotfiles/blob/5b3c8418ed42d93af2e647dc9d122f25cc034871/.osx

MohamedAlaa

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname