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# USAGE
# python build_face_dataset.py --cascade haarcascade_frontalface_default.xml --output dataset/adrian

# import the necessary packages
from imutils.video import VideoStream
import argparse
import imutils
import time
import cv2
import os

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"""
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)

machinelearning147

"""Script to illustrate usage of tf.estimator.Estimator in TF v1.3"""
import tensorflow as tf

from tensorflow.examples.tutorials.mnist import input_data as mnist_data
from tensorflow.contrib import slim
from tensorflow.contrib.learn import ModeKeys
from tensorflow.contrib.learn import learn_runner


# Show debugging output

machinelearning147

import numpy as np
import tensorflow as tf

__author__ = "Sangwoong Yoon"

def np_to_tfrecords(X, Y, file_path_prefix, verbose=True):
    """
    Converts a Numpy array (or two Numpy arrays) into a tfrecord file.
    For supervised learning, feed training inputs to X and training labels to Y.
    For unsupervised learning, only feed training inputs to X, and feed None to Y.

machinelearning147

import cv2
import matplotlib.pyplot as plt
import numpy as np

face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

webcam=cv2.VideoCapture(1)
cv2.namedWindow("faceWindow", cv2.WINDOW_GUI_NORMAL)
PADDING = 10
try:

machinelearning147

# USAGE
# python build_face_dataset.py --cascade haarcascade_frontalface_default.xml --output dataset/shravan

# import the necessary packages
from imutils.video import VideoStream
import argparse
import imutils
import time
import cv2
import os

machinelearning147

# usage:
# python simple_cameratest_opencv.py 1
import numpy as np
import cv2
import sys

n = sys.argv[1]

cap = cv2.VideoCapture(int(n))

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