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# A yaml constructor is for loading from a yaml node.
# This is taken from @misha 's answer: http://stackoverflow.com/a/15942429
def opencv_matrix_constructor(loader, node):
    mapping = loader.construct_mapping(node, deep=True)
    mat = np.array(mapping["data"])
    mat.resize(mapping["rows"], mapping["cols"])
    return mat
yaml.add_constructor(u"tag:yaml.org,2002:opencv-matrix", opencv_matrix_constructor)

# A yaml representer is for dumping structs into a yaml node.

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# The network is used for the video description experiments of S2VT [1].
# Please consider citing S2VT [1] if you use this example in your work.
#
# [1] S. Venugopalan, M. Rohrbach, J. Donahue, R. Mooney, T. Darrell,
#     K. Saenko. "Sequence to Sequence - Video to Text." ICCV 2015.

# The data is prepared using framefc7_stream_text_to_hdf5.py
# It is in (32)  parallel streams.
name: "s2vt"
layer {

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#!/usr/bin/env python
# encoding: utf-8


"""Minimal python commad line."""

import sys
import argparse
import logging

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# coding: utf-8

import matplotlib.pyplot as plt
import Image

img = Image.open('truman-stairs.jpg')
fig, ax = plt.subplots(figsize=(12,12))
ax.imshow(img, aspect='equal')

ax.add_patch(

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#################################################################################
# Authors: Keiller Nogueira, Victor de Melo
#################################################################################

# nvidia-docker seems more stable now and several images are starting to adopt it (including 
# [kaixhin](https://github.com/NVIDIA/nvidia-docker/issues/85).
# hence, we suggest to use it instead, as it solves a few issues with gpu passthrough.
# usage: it is only required when creating a container, i.e, with `run` and related arguments
# you're not required to provide $DOCKER_NVIDIA_DEVICES as it will find the devices itself