jeffdonahue

#!/bin/bash

# Script for installing tmux on systems where you don't have root access.
# tmux will be installed in $HOME/local/bin.
# Either wget or curl is required.
# It's assumed that a C/C++ compiler are installed.

# exit on error
set -e

jeffdonahue

#!/bin/bash

# Script for installing tmux on systems where you don't have root access.
# tmux will be installed in $HOME/local/bin.
# It's assumed that wget and a C/C++ compiler are installed.

# exit on error
set -e

# create our directories

jeffdonahue

#!/bin/bash

INDIR=$1
OUTDIR=$2

echo "Cloning leveldb in ${INDIR} to ${OUTDIR}"

INPATH=`realpath ${INDIR}`

mkdir -p ${OUTDIR}

jeffdonahue

sshput () {
	RSAKEY="${HOME}/.ssh/id_rsa.pub"
	DSAKEY="${HOME}/.ssh/id_dsa.pub"

	if [ $# -eq 2 ]; then
		KEY=$1
		if [ ! -r $KEY ]
		then
			echo "'$KEY' does not exist or is not readable"
			return 1

jeffdonahue

I1224 11:43:56.783612  2133 train_net.cpp:26] Starting Optimization
I1224 11:43:56.783983  2133 solver.cpp:26] Creating training net.
I1224 11:43:56.784008  2133 net.cpp:66] Creating Layer data
I1224 11:43:56.784013  2133 net.cpp:101] data -> data
I1224 11:43:56.784023  2133 net.cpp:101] data -> label
I1224 11:43:56.784036  2133 data_layer.cpp:122] Opening leveldb /home/jdonahue/caffe-train-leveldb
I1224 11:43:56.956717  2133 data_layer.cpp:159] output data size: 256,3,227,227
I1224 11:43:56.956765  2133 data_layer.cpp:176] Loading mean file from/home/jiayq/ilsvrc2012_mean.binaryproto
I1224 11:43:57.016316  2133 net.cpp:116] Top shape: 3 227 227
I1224 11:43:57.016341  2133 net.cpp:116] Top shape: 1 1 1

jeffdonahue

layer {
  name: "data"
  type: "DummyData"
  top: "data"
  top: "label"
  dummy_data_param {
    shape { dim: [128, 3, 227, 227] }
    shape { dim: [128] }
  }
}

jeffdonahue

try:
    range = xrange # Python 2
except NameError:
    pass # Python 3

def lazy_product(*iter_funcs, **kwargs):
    """
    If f1, f2, ..., are functions which have no (required) arguments and
    return iterables, then
        lazy_product(f1, f2, ..., repeat=k)

jeffdonahue

#!/usr/bin/env python

# usage: python count_caffemodel_params.py /path/to/my.caffemodel [/path/to/my/other.caffemodel, ...]

from caffe.proto import caffe_pb2
import sys

assert len(sys.argv) >= 2

for caffemodel_filename in sys.argv[1:]:

jeffdonahue

#!/usr/bin/env python

from __future__ import division

import functools
import itertools
import numpy as np
import os
import matplotlib.pyplot as plt
from PIL import Image

jeffdonahue

import numpy as np

def canonical_axis(x, axis):
    def is_int_ndarray(x):
        if not isinstance(x, np.ndarray):
            return False
        dtype = str(x.dtype)
        prefixes = 'int', 'uint'
        return any(dtype.startswith(p) for p in prefixes)
    if axis is None: