Version ready for live

This commit is contained in:
Ruben 2017-12-04 21:47:24 +01:00
parent 3b0e0eda16
commit 7379b2df12
7 changed files with 978 additions and 17 deletions

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Start two processes: Start two processes:
gphoto2 to capture images: gphoto2 to capture images every 2 sec:
`gphoto2 --port usb: --capture-image-and-download -I 1 --filename=/home/crowd/output/frame%06n.jpg` `gphoto2 --port usb: --capture-image-and-download -I 2 --filename=/home/crowd/output/frame%06n.jpg`
SET FPS IN parse_output.py
If using Sony A7s/r, Ubuntu 14.04 has a too old version of gphoto2, so use vm-host with gphoto. Mount pictures dir to vbox:
`sudo mount -t vboxsf pictures ~/pictures -o rw,uid=1000,gid=1000`
The modified 'webcam demo' to analyse and generate json: The modified 'webcam demo' to analyse and generate json:
`/home/crowd/build/opencv-webcam-demo/opencv-webcam-demo --data /home/crowd/affdex-sdk/data --faceMode 1 --numFaces 80 -o /home/crowd/output-backup/ --draw 0` `/home/crowd/build/opencv-webcam-demo/opencv-webcam-demo --data /home/crowd/affdex-sdk/data --faceMode 1 --numFaces 80 -o /home/crowd/output/segments/ --draw 0 --segments 1`
When using `--segments 1` also run:
`python split_and_merge_output.py --frameOutput ~/output --segmentDir ~/output/segments/`
Using split_and_merge_output, frames are split into segments so SMALL_FACES actually detects _really_ small faces. This requires enabling --segments on opencv-webcam-demo (so it detects/writes segment%06d files) Using split_and_merge_output, frames are split into segments so SMALL_FACES actually detects _really_ small faces. This requires enabling --segments on opencv-webcam-demo (so it detects/writes segment%06d files)
split_and_merge_output also remerges these segment%06.json files into a frame%06d.json file. split_and_merge_output also remerges these segment%06.json files into a frame%06d.json file.
When done, generate output:
`parse_output.py -o ~/output1 --json --window-size 1 > ~/sdk-samples/output/talk1.json`
`parse_output.py -o ~/output2 --json --window-size 1 > ~/sdk-samples/output/talk2.json`
`parse_output.py -o ~/output3 --json --window-size 1 > ~/sdk-samples/output/talk3.json`
and audio, which expects wav to start simmmultaneously with frame00001:
`python parse_output.py -o ~/pictures/1 --wav ~/pictures/1.wav --targetDir /home/crowd/sdk-samples/output/1 --window-size 1`
`python parse_output.py -o ~/pictures/2 --wav ~/pictures/2.wav --targetDir /home/crowd/sdk-samples/output/2 --window-size 1`
`python parse_output.py -o ~/pictures/3 --wav ~/pictures/3.wav --targetDir /home/crowd/sdk-samples/output/3 --window-size 1`
Then start server:
`cd ~/sdk-samples && php -S 0.0.0.0:8000`
Navigate to: `http://192.168.178.33:8000/graphs.php` to view images

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<html>
<head>
<title>Results of analysis: The Black Box Concern</title>
<script type="text/javascript" src="lodash.core.min.js"></script>
<script type="text/javascript" src="plotly-1.31.2.min.js"></script>
<script type="text/javascript">
var d1 = <?php echo require "output/talk1.json" ?>;
var d2 = <?php echo require "output/talk2.json" ?>;
var d3 = <?php echo require "output/talk3.json" ?>;
</script>
<style type="text/css">
body{
font-family: sans-serif;
width:calc(100% - 10em);
margin-left:10%;
margin-right:0;
}
#scroller{
width:100%;
overflow-x:auto;
}
#presentations{
width:300%;
}
#presentations .presentation{
width:33%;
float:left;
}
#presentations .presentation div.plot{
width:100%;
height:10em;
}
#checkboxes{
font-size: .8em;
width: 10em;
position:absolute;
left:0;
top:0;
}
label{
display:block;
}
#checkboxes span{
color: gray;
}
#checkboxes :checked + span{
color: black;
}
#imgwrap{
}
#imgwrap img{
width:90%;
}
h1{
margin: .1em 0;
text-transform:uppercase;
height:.9em;
}
</style>
</head>
<body>
<div id="checkboxes">
</div>
<div id="scroller">
<div id='presentations'>
<div class='presentation'>
<h1>Orit Halpern</h1>
<div class='stats' id='plot1-stats'></div>
<div class='plot' id="plot1-div"></div>
</div>
<div class='presentation'>
<h1>Penousal Machado</h1>
<div class='stats' id='plot2-stats'></div>
<div class='plot' id="plot2-div"></div>
</div>
<div class='presentation'>
<h1>Nicolas Maigret</h1>
<div class='stats' id='plot3-stats'></div>
<div class='plot' id="plot3-div"></div>
</div>
</div>
</div>
<div id='imgwrap'>
<img src="" id="hoverimg">
</div>
<script type='text/javascript'>
facialParameters = [
"smile",
"innerBrowRaise",
"browRaise",
"browFurrow",
"noseWrinkle",
"upperLipRaise",
"lipCornerDepressor",
"chinRaise",
"lipPucker",
"lipPress",
"lipSuck",
"mouthOpen",
"smirk",
"eyeClosure",
"eyeWiden",
"cheekRaise",
"lidTighten",
"dimpler",
"lipStretch",
"jawDrop",
]
defaultFacialParameters = [
"smile",
"innerBrowRaise",
"browRaise",
"browFurrow",
"noseWrinkle",
//~ "upperLipRaise",
//~ "lipCornerDepressor",
"chinRaise",
// "lipPucker",
//~ "lipPress",
//~ "lipSuck",
//~ "mouthOpen",
//"smirk",
// "attention",
//~ "eyeClosure",
//~ "eyeWiden",
"cheekRaise", //
"lidTighten",
//~ "dimpler", //
//~ "lipStretch",
//~ "jawDrop", //
];
function getCheckedParams(){
params = [];
for(var i in facialParameters){
let param = facialParameters[i];
if(document.getElementById("check_"+param).checked){
params.push(param);
}
}
return params;
}
var checkboxWrapperEl = document.getElementById("checkboxes");
for(var i in facialParameters){
let param = facialParameters[i];
var labelEl = document.createElement('label');
var checkboxEl = document.createElement('input');
var spanEl = document.createElement('span');
checkboxEl.type = "checkbox";
checkboxEl.checked = defaultFacialParameters.indexOf(param) > -1;
checkboxEl.id = "check_"+param;
checkboxEl.addEventListener('change',function(a){drawGraphs();});
labelEl.appendChild(checkboxEl);
spanEl.innerHTML = param;
labelEl.appendChild(spanEl);
checkboxWrapperEl.appendChild(labelEl);
}
var imgEl = document.getElementById("hoverimg");
var plot1Div = document.getElementById('plot1-div');
var plot2Div = document.getElementById('plot2-div');
var plot3Div = document.getElementById('plot3-div');
function drawGraphs(){
params = getCheckedParams();
drawGraph("talk1", plot1Div, d1, params);
drawGraph("talk2", plot2Div, d2, params);
drawGraph("talk3", plot3Div, d3, params);
}
function drawGraph(id, targetEl, d, params) {
var data = [
/* {
name: "Mean",
x: d['windows'].map(function(w){return w['start'];}),
y: d['windows'].map(function(w){return _.mean(_.filter(w['params'], function(v, param){return params.indexOf(param) > -1}));}),
//~ error_y: {
//~ type: 'data',
//~ array: d['windows'].map(function(w){return w['stddev'];}),
//~ visible: true
//~ },
type: 'scatter',
line: {
//~ color: 'rgb(55, 128, 191)',
width: 5
}
}*/
];
var avgV = {};
for(var i in params){
param = params[i];
paramValues = d['windows'].map(function(w){return w['params'][param];});
data.push({
name: param,
x: d['windows'].map(function(w){return w['start'];}),
y: paramValues,
type: 'scatter',
});
avgV[param] = _.mean(paramValues);
}
var devFunction = function(w){
let dev = 0;
for(var i in params){
let param = params[i];
dev += Math.pow(avgV[param] - w['params'][param], 2);
}
return Math.sqrt(dev);
};
data.push({
name: "Deviation",
x: d['windows'].map(function(w){return w['start'];}),
y: d['windows'].map(devFunction),
//~ error_y: {
//~ type: 'data',
//~ array: d['windows'].map(function(w){return w['stddev'];}),
//~ visible: true,
//~ color: '#f00'
//~ },
type: 'scatter',
line: {
color: '#800080',
width: 5
}
});
valFun = function(w){return w['params']['smile'] - (w['params']["innerBrowRaise"]+ w['params']["browFurrow"]+ w['params']["noseWrinkle"]+ w['params']["upperLipRaise"]+ w['params']["lipCornerDepressor"]+ w['params']["chinRaise"]+ w['params']["lipPress"]+ w['params']["lipSuck"])/8;};
var posWindow = _.maxBy(d['windows'], valFun);
var negWindow = _.minBy(d['windows'], valFun);
var devWindow = _.maxBy(d['windows'], devFunction);
var avgWindow = _.minBy(d['windows'], devFunction);
var diffWindow = _.maxBy(d['windows'], function(w){return w['stddev'];});
var concensusWindow = _.minBy(d['windows'], function(w){return w['stddev'];});
var annotations = [
//~ {
//~ x: posWindow['start'],
//~ y: posWindow['params']['smile'],
//~ xref: 'x',
//~ yref: 'y',
//~ text: 'Most positive moment',
//~ font: {color: 'gray'},
//~ showarrow: true,
//~ arrowhead: 7,
//~ ax: 0,
//~ ay: -40
//~ },
//~ {
//~ x: negWindow['start'],
//~ y: _.max([negWindow['params']["innerBrowRaise"], negWindow['params']["browFurrow"], negWindow['params']["noseWrinkle"], negWindow['params']["upperLipRaise"], negWindow['params']["lipCornerDepressor"], negWindow['params']["chinRaise"], negWindow['params']["lipPress"], negWindow['params']["lipSuck"]]),
//~ xref: 'x',
//~ yref: 'y',
//~ text: 'Most negative moment',
//~ font: {color: 'gray'},
//~ showarrow: true,
//~ arrowhead: 7,
//~ ax: 0,
//~ ay: -40
//~ },
{
x: devWindow['start'],
y: devFunction(devWindow),
xref: 'x',
yref: 'y',
text: 'Most deviant moment',
font: {color: 'gray'},
showarrow: true,
arrowhead: 7,
ax: 0,
ay: -40
},
{
x: avgWindow['start'],
y: devFunction(avgWindow),
xref: 'x',
yref: 'y',
text: 'Most average moment',
font: {color: 'gray'},
showarrow: true,
arrowhead: 7,
ax: 0,
ay: -40
},
{
x: avgWindow['start'],
y: devFunction(avgWindow),
xref: 'x',
yref: 'y',
text: 'Most average moment',
font: {color: 'gray'},
showarrow: true,
arrowhead: 7,
ax: 0,
ay: -40
},
{
x: diffWindow['start'],
y: devFunction(diffWindow),
xref: 'x',
yref: 'y',
text: 'Least concensus',
font: {color: 'gray'},
showarrow: true,
arrowhead: 7,
ax: 0,
ay: -40
},
{
x: concensusWindow['start'],
y: devFunction(concensusWindow),
xref: 'x',
yref: 'y',
text: 'Most concensus',
font: {color: 'gray'},
showarrow: true,
arrowhead: 7,
ax: 0,
ay: -40
}
]
var layout = {
//~ dragmode: 'zoom',
annotations: annotations,
//~ boxmode: 'group',
margin: {
r: 10,
t: 10,
b: 18,
l: 20
},
showlegend: false,
xaxis: {
autorange: true,
//~ domain: [0, 1],
//~ range: ['2017-01-03 12:00', '2017-02-15 12:00'],
//~ rangeslider: {range: ['2017-01-03 12:00', '2017-02-15 12:00']},
//~ title: 'Date',
type: 'date'
},
yaxis: {
autorange: true,
domain: [0, 1],
//~ range: [114.609999778, 137.410004222],
type: 'linear'
}
};
Plotly.newPlot(targetEl.id, data, layout,{displayModeBar: false});
//~ targetEl.on('plotly_click', function(data){
//~ console.log(data);
//~ var pts = '';
//~ for(var i=0; i < data.points.length; i++){
//~ pts = 'x = '+data.points[i].x +'\ny = '+
//~ data.points[i].y.toPrecision(4) + '\n\n';
//~ }
//~ alert('Closest point clicked:\n\n'+pts);
//~ });
targetEl.on('plotly_hover', function (data){
var points = data.points[0],
pointNum = points.pointNumber;
console.log(pointNum, d['windows'][pointNum]['startFrame'], data);
imgEl.src = "/images.php?i="+d['windows'][pointNum]['startFrame']+"&params="+params.join() + "&nr=" + d['outputNr'] ;
var audio = new Audio('output/'+d['outputNr']+'/'+d['windows'][pointNum]['startFrame']+'.wav');
audio.play();
//~ Plotly.Fx.hover('plot-div',[
//~ { curveNumber:0, pointNumber:pointNum },
//~ { curveNumber:1, pointNumber:pointNum },
//~ { curveNumber:2, pointNumber:pointNum },
//~ ]);
});
//~ plotDiv.on('plotly_hover', function (eventdata){
//~ console.log(data);
//~ });
}
drawGraphs();
</script>
</body>
</html>

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<?php
$basedir = "/home/crowd/pictures/";
$framename = basename($_GET['i']);
$outputnr = (int) $_GET['nr'];
$params = explode(',',$_GET['params']);
$availableParams = array("smile",
"innerBrowRaise",
"browRaise",
"browFurrow",
"noseWrinkle",
"upperLipRaise",
"lipCornerDepressor",
"chinRaise",
"lipPucker",
"lipPress",
"lipSuck",
"mouthOpen",
"smirk",
"eyeClosure",
"eyeWiden",
"cheekRaise",
"lidTighten",
"dimpler",
"lipStretch",
"jawDrop"
);
foreach($params as $param) {
if(!in_array($param, $availableParams)) {
throw new Exception("Invalid param" . $param);
}
}
$framefile = $basedir ."/".$outputnr ."/".$framename.".jpg";
$framejson = $basedir ."/".$outputnr ."/".$framename.".json";
$im = imagecreatefromjpeg($framefile);
$json = json_decode(file_get_contents($framejson), true);
$colorFg = imagecolorallocate($im, 255,255,255);
$avg = [];
foreach($params as $param) {
$values = array_map(function($f) use($param){return $f[$param];}, $json['faces']);
$avg[$param] = array_sum($values) / count($values);
}
foreach($json['faces'] as &$face) {
$face['diff'] = 0;
foreach($params as $param) {
$face['diff'] += abs($avg[$param] - $face[$param]);
}
$face['diff'] = sqrt($face['diff']);
}
usort($json['faces'], function ($f1, $f2) {
if ($f1['diff'] == $f2['diff']) return 0;
return $f1['diff'] > $f2['diff'] ? -1 : 1;
});
$targetIm = imagecreatetruecolor(1920, 1080);
$white = imagecolorallocate($targetIm, 255, 255, 255);
imagefill($targetIm, 0, 0, $white);
$i = 0;
$faceDim = 120;
$faceMargin = 20;
$itemsPerRow = (int) 1080 / ($faceDim + $faceMargin);
$maxDiff = sqrt(count($params) * 100);
foreach($json['faces'] as $face) {
$posX = $i % $itemsPerRow;
$posY = (int) ($i / $itemsPerRow);
$destX = $posX * ($faceDim + $faceMargin);
$destY = $posY * ($faceDim + $faceMargin);
imagecopyresampled ( $targetIm , $im , $destX , $destY , (int) $face['rect']['x'] , (int) $face['rect']['y'] , $faceDim , $faceDim , (int) $face['rect']['w'], (int) $face['rect']['h']);
$score = ($face['diff'] / $maxDiff) * 255; // score on 0-100 -> 255 scale for color:
$colorBg = imagecolorallocate($im, (int) $score, (int) 255 - $score, 0);
imagettftext($targetIm, 12, 0, $destX, $destY + $faceDim + $faceMargin/1.2, $colorBg, "/usr/share/fonts/truetype/dejavu/DejaVuSansMono.ttf", round($face['diff'],2));
$i++;
}
$im = $targetIm;
/*
foreach($json['faces'] as $face) {
// Draw a rectangle in color representing score on params
imagecolorallocate($im, 200,200,200);
$total = 0;
foreach($params as $param) {
$total += $face[$param];
}
$score = ($total / count($params)) * 2.55; // score on 0-100 -> 255 scale for color:
$colorBg = imagecolorallocate($im, (int) 255 - $score, (int) $score, 0);
//~ var_dump($face['rect']);
//~ imagefilledrectangle($im, $face['rect']['x'], $face['rect']['y'], $face['rect']['x']+$face['rect']['width'], $face['rect']['y']+$face['rect']['height'], $colorBg);
$face['rect']['x2'] = round($face['rect']['x'] + $face['rect']['w']);
$face['rect']['y2'] = round($face['rect']['y'] + $face['rect']['h']);
$face['rect']['x'] = round($face['rect']['x']);
$face['rect']['y'] = round($face['rect']['y']);
imagefilledrectangle($im, $face['rect']['x'], $face['rect']['y'], $face['rect']['x2'], $face['rect']['y2'], $colorBg);
}
$im = imagescale($im, 1920, 1080);
*/
header("Content-Type: image/jpeg");
// Save the image
imagejpeg($im, NULL, 80);
//~ imagedestroy($im);

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View file

@ -5,11 +5,13 @@ import json
import time import time
import glob import glob
import numpy as np import numpy as np
import datetime
import Tkinter import Tkinter
import moviepy.editor as mpy
import sys
import wave
FPS = 1
facialParameters = [ facialParameters = [
"smile", "smile",
@ -35,16 +37,44 @@ facialParameters = [
"jawDrop", "jawDrop",
] ]
defaultFacialParameters = [
"smile",
"innerBrowRaise",
"browRaise",
"browFurrow",
"noseWrinkle",
"upperLipRaise",
"lipCornerDepressor",
"chinRaise",
#~ "lipPucker",
"lipPress",
"lipSuck",
"mouthOpen",
#~ "smirk",
#~ "attention",
"eyeClosure",
"eyeWiden",
"cheekRaise", #
"lidTighten",
"dimpler", #
"lipStretch",
"jawDrop", #
]
parser = argparse.ArgumentParser(description='Parses opencv-webcam-demo json output files and collects statistics') parser = argparse.ArgumentParser(description='Parses opencv-webcam-demo json output files and collects statistics')
parser.add_argument('--frameOutput', '-o', required=True, help='directory to look for frames & json') parser.add_argument('--frameOutput', '-o', required=True, help='directory to look for frames & json')
parser.add_argument('--targetDir', help='Directory in which files are stored')
parser.add_argument('--status', action='store_true', help='Keep status of last frame') parser.add_argument('--status', action='store_true', help='Keep status of last frame')
parser.add_argument('--stats', action='store_true', help='Show statistics for all frames')
parser.add_argument('--cutAllFaces', action='store_true', help='Cut out all faces from all frames') parser.add_argument('--cutAllFaces', action='store_true', help='Cut out all faces from all frames')
parser.add_argument('--sum', action='store_true', help='Get total scores over all time') parser.add_argument('--sum', action='store_true', help='Get total scores over all time')
parser.add_argument('--unique', action='store_true', help='Get most unique window') parser.add_argument('--unique', action='store_true', help='Get most unique window')
parser.add_argument('--avg', action='store_true', help='Get most average window') parser.add_argument('--avg', action='store_true', help='Get most average window')
parser.add_argument('--json', action='store_true', help='Get output as JSON for graphs (graphs.php)')
parser.add_argument('--wav', '-w', required=False, default=False, help='split wave file into windows')
parser.add_argument('--disonant', action='store_true', help='Get most disonant faces over time') parser.add_argument('--disonant', action='store_true', help='Get most disonant faces over time')
parser.add_argument('--window-size', '-s', type=int, default=10, help='The nr of frames to group in one sliding window for analysis') parser.add_argument('--window-size', '-s', type=int, default=10, help='The nr of frames to group in one sliding window for analysis')
parser.add_argument("--params", "-p", type=str, nargs='+', default=facialParameters, choices=facialParameters, help="The parameters used to calculate the statistics") parser.add_argument("--params", "--metrics", "-p", type=str, nargs='+', default=defaultFacialParameters, choices=facialParameters, help="The parameters used to calculate the statistics")
args = parser.parse_args() args = parser.parse_args()
@ -81,7 +111,13 @@ class Frame:
self.faces = None # init with getFaces self.faces = None # init with getFaces
def getTime(self): def getTime(self):
return os.path.getmtime(self.imgPath) """
@return datetime
"""
with Image.open(self.imgPath) as i:
#~ print(i._getexif()[36867])
return datetime.datetime.strptime(i._getexif()[36867], "%Y:%m:%d %H:%M:%S")
#~ return datetime.datetime.fromtimestamp(os.path.getmtime(self.imgPath))
def getJson(self): def getJson(self):
#~ try: #~ try:
@ -91,7 +127,7 @@ class Frame:
#~ # no json file yet? #~ # no json file yet?
#~ return None #~ return None
def getImg(self, markFaces = True): def getImg(self, markFaces = False):
img = Image.open(self.imgPath) img = Image.open(self.imgPath)
if not markFaces: if not markFaces:
return img return img
@ -132,6 +168,13 @@ class Frame:
vAvg = np.mean(vectors, axis=0) vAvg = np.mean(vectors, axis=0)
return vAvg return vAvg
def getStdDev(self, params):
"""
Get standard deviation of the faces within the frame for given params
"""
vectors = [f.getCharacteristicVector(params) for f in self.getFaces()]
return np.std(vectors)
def updateAnomalyScores(self, params): def updateAnomalyScores(self, params):
vAvg = self.getAverageV(params) vAvg = self.getAverageV(params)
for face in self.getFaces(): for face in self.getFaces():
@ -152,6 +195,14 @@ class Window:
self.deviation = None self.deviation = None
self.standardDeviation = None self.standardDeviation = None
def getStartTime(self):
"""get time of first frame in window. Returns datetime"""
return self.frames[0].getTime()
def getEndTime(self):
"""get time of last frame in window. Returns datetime"""
return self.frames[-1].getTime()
def getFaces(self): def getFaces(self):
faces = [] faces = []
for frame in self.frames: for frame in self.frames:
@ -178,12 +229,14 @@ class Window:
frames = sorted(frames.items(), key=lambda f: f[0]) frames = sorted(frames.items(), key=lambda f: f[0])
frames = [f[1] for f in frames] frames = [f[1] for f in frames]
windows = [] windows = []
windowCount = len(frames) - windowSize + 1 windowCount = len(frames) / windowSize
#~ windowCount = len(frames) - windowSize + 1
if windowCount < 1: if windowCount < 1:
raise Exception("Not enough frames ({}) for a window of size {}".format(len(frames), windowSize)) raise Exception("Not enough frames ({}) for a window of size {}".format(len(frames), windowSize))
for offset in range(0, windowCount): for offset in range(0, windowCount):
frameSubset = frames[offset:offset+windowSize] frameSubset = frames[offset*windowSize:(offset+1)*windowSize]
#~ frameSubset = frames[offset:offset+windowSize]
windows.append(Window(frameSubset)) windows.append(Window(frameSubset))
return windows return windows
@ -212,6 +265,11 @@ class WindowCollection:
return sorted(self.windows, key=lambda w: np.linalg.norm(w.getAverageV(params)-vAvg)) return sorted(self.windows, key=lambda w: np.linalg.norm(w.getAverageV(params)-vAvg))
def getDeviationForWindow(self, window, params):
vectors = self.getWindowVectors(params)
vAvg = np.mean(vectors, axis=0)
return np.linalg.norm(w.getAverageV(params)-vAvg)
def getUniqueWindows(self, params, nr=5): def getUniqueWindows(self, params, nr=5):
windows = self.getWindowsByDeviation(params) windows = self.getWindowsByDeviation(params)
return windows[0: nr] return windows[0: nr]
@ -260,7 +318,7 @@ def validateJsonTimes():
thisTime = frame.getJson()['t'] thisTime = frame.getJson()['t']
#print(frameNr, thisTime) #print(frameNr, thisTime)
if not (lastTime is None) and lastTime > thisTime: if not (lastTime is None) and lastTime > thisTime:
print "ERRROR!! Time error at %s. Restarted scanner there?" % frameNr sys.stderr.write("ERRROR!! Time error at %s. Restarted scanner there?\n" % frameNr)
lastTime = thisTime lastTime = thisTime
def sumEmotions(): def sumEmotions():
@ -335,7 +393,17 @@ def monitorStatus(frameDir, params):
# don't check too often # don't check too often
time.sleep(.5) time.sleep(.5)
def playWindowStopmotion(window): def printStats(frameDir, params):
frames = loadFrames(frameDir)
vAvg = np.mean([f.getAverageV(params) for i,f in frames.items()], axis=0)
for nr, frame in frames.items():
max_index, max_value = max(enumerate(frame.getAverageV(params)), key=lambda a: a[1])
distance = np.linalg.norm(vAvg - frame.getAverageV(params))
print("{:06d}: {: >4} faces (d: {: 6.2f}, internal s {: 6.2f}, max: {})".format(frame.nr, len(frame.getFaces()),distance, frame.getStdDev(params), params[max_index]))
print("{} frames".format(len(frames)))
def playWindowStopmotion(window, params):
""" """
Play a set of sliding window frames as stop motion video Play a set of sliding window frames as stop motion video
""" """
@ -346,7 +414,7 @@ def playWindowStopmotion(window):
old_label_image = None old_label_image = None
for frame in window.frames: for frame in window.frames:
image = frame.getImg() image = frame.getImg(markFaces=True)
basewidth = 1000 basewidth = 1000
wpercent = (basewidth / float(image.size[0])) wpercent = (basewidth / float(image.size[0]))
hsize = int((float(image.size[1]) * float(wpercent))) hsize = int((float(image.size[1]) * float(wpercent)))
@ -358,6 +426,112 @@ def playWindowStopmotion(window):
root.update() root.update()
time.sleep(1) time.sleep(1)
def createWindowVideo(window, params, targetDir):
global FPS
basewidth = 1920
i=0
images = []
for frame in window.frames:
image = frame.getImg(markFaces=True)
wpercent = (basewidth / float(image.size[0]))
hsize = int((float(image.size[1]) * float(wpercent)))
image = image.resize((basewidth, hsize), Image.ANTIALIAS)
imgName = os.path.join("/tmp/","renderframe{:06d}.jpg".format(i))
print("(VIDEO) Create frame: {}".format(imgName))
image.save(imgName)
images.append(imgName)
i+=1
clip = mpy.ImageSequenceClip(images, fps=FPS)
#~ audio = mpy.AudioFileClip(filename="")
#~ audio.set_start(...)
#~ audio.set_duration(len(images)/FPS)
#~ clip = clip.set_audio(audio)
targetName = "video_" + "-".join(params) + ".mp4"
print("(VIDEO) Write video: {}".format(targetName))
clip.write_videofile(os.path.join(targetDir,targetName), fps=FPS)
def getGraphData(frames, params, window_size, outputNr):
"""
Get data to generate graph with
"""
collection = WindowCollection(window_size, frames)
windows = collection.windows
jsonOutput = {'windows':[], 'outputNr': outputNr}
for window in windows:
w = {
'start': window.getStartTime().strftime('%Y-%m-%d %H:%M:%S'),
'end': window.getEndTime().strftime('%Y-%m-%d %H:%M:%S'),
'startFrame': window.frames[0].name,
'params': {},
'param_values': {},
}
pVs = []
for param in params:
paramV = window.getAverageV([param])
value = paramV[0]
pVs.append(value)
w['params'][param] = value
#~ values = []
#~ for frame in window.frames:
#~ for face in frame.getFaces():
#~ values.append(face.data[param])
#~ w['param_values'][param] = values
w['avg'] = np.mean(pVs)
w['stddev'] = window.getStdDev(params)
jsonOutput['windows'].append(w)
jsonOutput['range'] = [
jsonOutput['windows'][0]['start'],
jsonOutput['windows'][-1]['end'],
]
return jsonOutput
def splitAudio(frames, window_size, srcWav, targetDir):
"""
Get audio cllips
"""
global FPS
if not os.path.exists(srcWav):
raise Exception("Wav does not exist")
if not os.path.exists(targetDir):
raise Exception("Target dir does not exist")
collection = WindowCollection(window_size, frames)
origAudio = wave.open(srcWav,'r')
frameRate = origAudio.getframerate()
nChannels = origAudio.getnchannels()
sampWidth = origAudio.getsampwidth()
windows = collection.windows
for i, window in enumerate(windows):
print("Window {}, {}".format(i, window.frames[0].name))
start = i * window_size * FPS
end = i+1 * window_size * FPS
origAudio.setpos(start*frameRate)
print(origAudio.tell())
chunkData = origAudio.readframes(int((end-start)*frameRate))
print(origAudio.tell())
targetFile = os.path.join(targetDir, window.frames[0].name + '.wav')
print("\t{}".format(targetFile))
chunkAudio = wave.open(targetFile,'w')
chunkAudio.setnchannels(nChannels)
chunkAudio.setsampwidth(sampWidth)
chunkAudio.setframerate(frameRate)
chunkAudio.writeframes(chunkData)
chunkAudio.close()
#~ def createGraphPage(windows, params, targetFilename):
#~ jsonOutput = {'windows':[]}
#~ for window in windows:
#~ window
validateJsonTimes() validateJsonTimes()
if args.sum: if args.sum:
@ -378,13 +552,29 @@ if args.unique:
collection = WindowCollection(args.window_size, frames) collection = WindowCollection(args.window_size, frames)
windows = collection.getUniqueWindows(args.params) windows = collection.getUniqueWindows(args.params)
#~ print(windows) #~ print(windows)
playWindowStopmotion(windows[0]) if args.targetDir:
createWindowVideo(windows[0], args.params, args.targetDir)
else:
playWindowStopmotion(windows[0], args.params)
if args.avg: if args.avg:
collection = WindowCollection(args.window_size, frames) collection = WindowCollection(args.window_size, frames)
windows = collection.getMostAvgWindows(args.params) windows = collection.getMostAvgWindows(args.params)
#~ print(windows) #~ print(windows)
playWindowStopmotion(windows[0]) if args.targetDir:
createWindowVideo(windows[0], args.params, args.targetDir)
else:
playWindowStopmotion(windows[0], args.params)
if args.status: if args.status:
monitorStatus(args.frameOutput, args.params) monitorStatus(args.frameOutput, args.params)
if args.stats:
printStats(args.frameOutput, args.params)
if args.json:
nr = int(args.frameOutput[-1])
print json.dumps(getGraphData(frames, args.params, args.window_size, nr))
if args.wav:
print splitAudio(frames, args.window_size, args.wav, args.targetDir)

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@ -61,9 +61,11 @@ while True:
faces = [] faces = []
times = [] times = []
segmentImages = []
for i, segment in enumerate(segments): for i, segment in enumerate(segments):
segmentNr = nextOutNr - segmentCount + i + 1 # nextOutNr: 4 => 1,2,3,4 segmentNr = nextOutNr - segmentCount + i + 1 # nextOutNr: 4 => 1,2,3,4
segmentImages.append(os.path.join(args.segmentDir, "segment%06d.jpg" % segmentNr))
with open( os.path.join(args.segmentDir, "segment%06d.json" % segmentNr) ) as fp: with open( os.path.join(args.segmentDir, "segment%06d.json" % segmentNr) ) as fp:
j = json.load(fp) j = json.load(fp)
@ -84,6 +86,10 @@ while True:
with open(jsonOutFilename, 'w') as fp: with open(jsonOutFilename, 'w') as fp:
json.dump(data, fp) json.dump(data, fp)
print("(MERGE) Wrote: {}".format(jsonOutFilename)) print("(MERGE) Wrote: {}".format(jsonOutFilename))
print("(MERGE) Cleanup segments for frame {}".format(frameOutNr))
for imgName in segmentImages:
print("(MERGE) \t Unlink {}".format(imgName))
os.unlink(imgName)
nextOutNr += segmentCount nextOutNr += segmentCount
nextJson = os.path.join(args.segmentDir, "segment%06d.json" % nextOutNr) nextJson = os.path.join(args.segmentDir, "segment%06d.json" % nextOutNr)