def main(testName, dataPath, imagePath='images/white_background.jpg'):
# Call loadData() and save results
pos, fixations, saccade = loadData(
dataPath) # Eventually this could use inputs to specify data
leftEyeFrame = fixations.loc[fixations['eye'] ==
'L'] # Filter only the rows for the left eye
durations = leftEyeFrame['duration'].values
xPositions = leftEyeFrame['x_pos'].values
yPositions = leftEyeFrame['y_pos'].values
fixDurations = leftEyeFrame['duration'].values
"""
fix - a dict with three keys: 'x', 'y', and 'dur' (each contain
a numpy array) for the x and y coordinates and duration of
each fixation
"""
fix = {'x': xPositions, 'y': yPositions, 'dur': fixDurations}
try:
fig = gazeplotter.draw_heatmap(
fix,
[GetSystemMetrics(0), GetSystemMetrics(1)],
imagefile=imagePath)
except ValueError as e:
fig = gazeplotter.draw_heatmap(
fix,
[GetSystemMetrics(1), GetSystemMetrics(0)],
imagefile=imagePath)
plt.show()
analyze(testName, pos, fixations, saccade)
def process_images(imglist, eventfile, ppname, imgdir, plotdir):
# check if the image directory exists
if not os.path.isdir(imgdir):
raise Exception("ERROR: no image directory found; path '%s' does not exist!" % imgdir)
# check if output directorie exist; if not, create it
if not os.path.isdir(plotdir):
os.mkdir(plotdir)
# EXPERIMENT SPECS
DISPSIZE = (1920,1080) # (px,px)
SCREENSIZE = (39.9,29.9) # (cm,cm)
SCREENDIST = 61.0 # cm
PXPERCM = numpy.mean([DISPSIZE[0]/SCREENSIZE[0],DISPSIZE[1]/SCREENSIZE[1]]) # px/cm
# read the file
smidata = read_smioutput(eventfile, None, ag_mode=SMIModes.LEFT_ONLY, stop=None, debug=False)
nokey = 0
processed = 0
# loop through trials
for trialnr in range(len(imglist)):
# load image name, saccades, and fixations
imgname = imglist[int(trialnr)]
try:
saccades = smidata[trialnr]['events']['Esac'] # [starttime, endtime, duration, startx, starty, endx, endy]
fixations = smidata[trialnr]['events']['Efix'] # [starttime, endtime, duration, endx, endy]
except KeyError:
print "No eyetracking data for trial %s (image: %s)" % (trialnr + 1, imgname)
nokey += 1
continue
except IndexError:
print "No eyetracking data for trial %s (image: %s)" % (trialnr + 1, imgname)
nokey += 1
continue
processed += 1
# paths
imagefile = os.path.join(imgdir, imgname)
# rawplotfile = os.path.join(plotdir, "raw_data_%s_%d" % (ppname,trialnr))
scatterfile = os.path.join(plotdir, "fixations_%s_%d" % (ppname,trialnr))
scanpathfile = os.path.join(plotdir, "scanpath_%s_%d" % (ppname,trialnr))
heatmapfile = os.path.join(plotdir, "heatmap_%s_%d" % (ppname,trialnr))
# raw data points
# draw_raw(smidata[trialnr]['x'], smidata[trialnr]['y'], DISPSIZE, imagefile=imagefile, savefilename=rawplotfile)
# fixations
draw_fixations(fixations, DISPSIZE, imagefile=imagefile, durationsize=True, durationcolour=False, alpha=0.5, savefilename=scatterfile)
# scanpath
draw_scanpath(fixations, saccades, DISPSIZE, imagefile=imagefile, alpha=0.5, savefilename=scanpathfile)
# heatmap
draw_heatmap(fixations, DISPSIZE, imagefile=imagefile, durationweight=True, alpha=0.75, savefilename=heatmapfile)
print "%s images processed. %s sections without eyetracker data." % (processed, nokey)
def generate_plots(IMGDIR, PLOTDIR, filename, fixations, saccades, data,
DISPSIZE, trialnr):
# cognitive load
if int(filename[4:5]) == 1:
cognitive_load = "LOW"
else:
cognitive_load = "HIGH"
#imgname = "screenshot.jpg"
#imagefile = os.path.join(IMGDIR,imgname)
# paths
rawplotfile = os.path.join(
PLOTDIR, "raw_data_%s_%s" % (filename[:3], cognitive_load))
scatterfile = os.path.join(
PLOTDIR, "fixations_%s_%s" % (filename[:3], cognitive_load))
scanpathfile = os.path.join(
PLOTDIR, "scanpath_%s_%s" % (filename[:3], cognitive_load))
heatmapfile = os.path.join(
PLOTDIR, "heatmap_%s_%s" % (filename[:3], cognitive_load))
# raw data points
draw_raw(data[trialnr]['x'],
data[trialnr]['y'],
DISPSIZE,
imagefile=None,
savefilename=rawplotfile)
# fixations
draw_fixations(fixations,
DISPSIZE,
imagefile=None,
durationsize=True,
durationcolour=False,
alpha=0.5,
savefilename=scatterfile)
# scanpath
draw_scanpath(fixations,
saccades,
DISPSIZE,
imagefile=None,
alpha=0.5,
savefilename=scanpathfile)
# heatmap
draw_heatmap(fixations,
DISPSIZE,
imagefile=None,
durationweight=True,
alpha=0.5,
savefilename=heatmapfile)
# plot fixations
fig = gazeplotter.draw_fixations(
fixations,
DISPSIZE,
imagefile=os.path.join(IMGDIR, "%s%s" % (imgname, ext)),
durationsize=True,
durationcolour=False,
alpha=0.5,
savefilename=os.path.join(
OUTDIR, "fixations_%s_%s.png" % (trackertype, imgname)))
pyplot.close(fig)
# create heatplot
fig = gazeplotter.draw_heatmap(
fixations,
DISPSIZE,
imagefile=os.path.join(IMGDIR, "%s%s" % (imgname, ext)),
durationweight=True,
alpha=0.5,
savefilename=os.path.join(
OUTDIR, "heatmap_%s_%s.png" % (trackertype, imgname)))
pyplot.close(fig)
# PRECISION AND ACCURACY AVERAGES
# empty dicts
alldata = {}
for ppname in PPS:
# read data file
datafile = open(
os.path.join(IOUTDIR, ppname, trackertype, "ROI_analysis.txt"),
'r')
data = datafile.readlines()
datafile.close()
heatmapfile = os.path.join(pplotdir,
"heatmap_%s_%d" % (ppname, trialnr))
##raw data points
#draw_raw(edfdata[trialnr]['x'], edfdata[trialnr]['y'],edfdata[trialnr]['size'], DISPSIZE, imagefile=imagefile, savefilename=rawplotfile)
#fixations
draw_fixations(fixations,
DISPSIZE,
imagefile=imagefile,
durationsize=True,
durationcolour=True,
alpha=0.5,
savefilename=scatterfile)
##scanpath
draw_scanpath(fixations,
saccades,
DISPSIZE,
imagefile=imagefile,
alpha=0.5,
savefilename=scanpathfile)
# heatmap
draw_heatmap(fixations,
DISPSIZE,
imagefile=imagefile,
durationweight=True,
alpha=0.5,
savefilename=heatmapfile)
# PLOT DATA
for i in range(len(imagedata)):
# image name
imgname = os.path.splitext(os.path.basename(IMAGES[i]))[0]
# pickle fixation data
fixfile = open(os.path.join(outputdir, "fixations_%s.dat" % imgname), 'w')
pickle.dump(imagedata[i]['events']['Efix'], fixfile)
fixfile.close()
# plot raw data
fig = gazeplotter.draw_raw(imagedata[i]['x'], imagedata[i]['y'], DISPSIZE, imagefile=IMAGES[i], savefilename=os.path.join(outputdir, "image_%s_raw.png" % imgname))
pyplot.close(fig)
# plot fixations
fig = gazeplotter.draw_fixations(imagedata[i]['events']['Efix'], DISPSIZE, imagefile=IMAGES[i], durationsize=True, durationcolour=False, alpha=0.5, savefilename=os.path.join(outputdir, "image_%s_fixations.png" % imgname))
pyplot.close(fig)
# draw heatmap
fig = gazeplotter.draw_heatmap(imagedata[i]['events']['Efix'], DISPSIZE, imagefile=IMAGES[i], durationweight=True, alpha=0.5, savefilename=os.path.join(outputdir, "image_%s_heatmap.png" % imgname))
pyplot.close(fig)
# ROI ANALYSIS
if "01F_HA_O" in IMAGES[i]:
# empty dicts
Nfix = {}
fixdur = {}
dwelltime = {}
# go through all ROI names
for ROIname in ROILIST:
# starting values
Nfix[ROIname] = 0
fixdur[ROIname] = 0
dwelltime[ROIname] = 0
# go through all fixations
# loop through all images
for imgname in IMAGES:
# get rid of image path and extension
imgname, ext = os.path.splitext(os.path.basename(imgname))
# empty lists
fixations = []
# loop through all participants
for ppname in PPS:
fixfile = open(os.path.join(IOUTDIR, ppname, trackertype, "fixations_%s.dat" % imgname), 'r')
fixations.extend(pickle.load(fixfile))
fixfile.close()
# plot fixations
fig = gazeplotter.draw_fixations(fixations, DISPSIZE, imagefile=os.path.join(IMGDIR, "%s%s" % (imgname,ext)), durationsize=True, durationcolour=False, alpha=0.5, savefilename=os.path.join(OUTDIR, "fixations_%s_%s.png" % (trackertype,imgname)))
pyplot.close(fig)
# create heatplot
fig = gazeplotter.draw_heatmap(fixations, DISPSIZE, imagefile=os.path.join(IMGDIR, "%s%s" % (imgname,ext)), durationweight=True, alpha=0.5, savefilename=os.path.join(OUTDIR, "heatmap_%s_%s.png" % (trackertype,imgname)))
pyplot.close(fig)
# PRECISION AND ACCURACY AVERAGES
# empty dicts
alldata = {}
for ppname in PPS:
# read data file
datafile = open(os.path.join(IOUTDIR, ppname, trackertype, "ROI_analysis.txt"), 'r')
data = datafile.readlines()
datafile.close()
# parse data
for i in range(len(data)):
data[i] = data[i].replace('\n','').replace('\r','').replace('"','').replace("'","").split('\t')
header = data.pop(0)
# loop through all fields in the header
if '.jpg' in msg[1]:
imgname = os.path.splitext(msg[1])[0]
imgfile = os.path.join(IMGDIR, msg[1])
# get the fixations
fixations = gazedata[trialnr]['events']['Efix']
print "outdir:", outdir # plot the samples
gazeplotter.draw_raw(gazedata[trialnr]['x'],
gazedata[trialnr]['y'],
RESOLUTION,
imagefile=imgfile,
savefilename=os.path.join(outdir,
'%s_samples.png' % imgname))
# plot the fixations
gazeplotter.draw_fixations(fixations,
RESOLUTION,
imagefile=imgfile,
durationsize=True,
durationcolour=False,
alpha=0.5,
savefilename=os.path.join(
outdir, '%s_fixations.png' % imgname))
# plot a heatmap
gazeplotter.draw_heatmap(fixations,
RESOLUTION,
imagefile=imgfile,
durationweight=True,
alpha=0.5,
savefilename=os.path.join(
outdir, '%s_heatmap.png' % imgname))
# PLOTS
print("plotting gaze data")
# loop through trials
for trialnr in range(len(data)):
# load image name, saccades, and fixations
imgname = data[trialnr][header.index("image")]
saccades = edfdata[trialnr]['events']['Esac'] # [starttime, endtime, duration, startx, starty, endx, endy]
fixations = edfdata[trialnr]['events']['Efix'] # [starttime, endtime, duration, endx, endy]
# paths
imagefile = os.path.join(IMGDIR,imgname)
rawplotfile = os.path.join(pplotdir, "raw_data_%s_%d" % (ppname,trialnr))
scatterfile = os.path.join(pplotdir, "fixations_%s_%d" % (ppname,trialnr))
scanpathfile = os.path.join(pplotdir, "scanpath_%s_%d" % (ppname,trialnr))
heatmapfile = os.path.join(pplotdir, "heatmap_%s_%d" % (ppname,trialnr))
# raw data points
draw_raw(edfdata[trialnr]['x'], edfdata[trialnr]['y'], DISPSIZE, imagefile=imagefile, savefilename=rawplotfile)
# fixations
draw_fixations(fixations, DISPSIZE, imagefile=imagefile, durationsize=True, durationcolour=False, alpha=0.5, savefilename=scatterfile)
# scanpath
draw_scanpath(fixations, saccades, DISPSIZE, imagefile=imagefile, alpha=0.5, savefilename=scanpathfile)
# heatmap
draw_heatmap(fixations, DISPSIZE, imagefile=imagefile, durationweight=True, alpha=0.5, savefilename=heatmapfile)
def heatMap(startTime, endTime, totalTime):
#(in seconds) (later converted to millis)
#start time of video segment
#end time of video segment
#total time of video
#saveLocation: location where output heatmap is to be saved
#fixationFilePath: location of fixation csv
#videoLocation: location of video
#imageWidth and IimageHeight: dimension of a frame in a video
saveLocation = '/Users/jeffhe/Desktop/commitments/urap/resources/heatmap_processing/0308_1528_manual_03/heatmat.png'
fixationFilePath = "/Users/jeffhe/Desktop/commitments/urap/resources/heatmap_processing/0308_1528_manual_03/fixations.csv"
gazeFilePath = "/Users/jeffhe/Desktop/commitments/urap/resources/heatmap_processing/0308_1528_manual_03/gaze_positions.csv"
videoLocation = "/Users/jeffhe/Desktop/commitments/urap/resources/heatmap_processing/0308_1528_manual_03/worldwithoutgaze.mp4"
imageWidth = 1280
imageHeight = 720
def changeStartTimeMillis():
with open(gazeFilePath) as f:
reader = csv.reader(f)
reader = list(reader)
startTimeSeconds = float(reader[1][0])
return startTimeSeconds
startTimeMillis = changeStartTimeMillis() * 1000
vidcap = cv2.VideoCapture(videoLocation)
frames = []
success, image = vidcap.read()
frames += [image]
while success:
success, image = vidcap.read()
frames += [image]
startFrame = (startTime / totalTime) * len(frames)
endFrame = (endTime / totalTime) * len(frames)
image = frames[int((startFrame + endFrame) / 2)]
startTime = startTime * 1000
endTime = endTime * 1000
with open(fixationFilePath) as f:
reader = csv.reader(f)
line_num = 0
Efix = []
for row in reader:
if (line_num != 0):
start = float(row[1]) * 1000 - startTimeMillis
Efix += [[
start, start + float(row[2]),
float(row[2]),
int(float(row[5]) * imageWidth),
imageHeight - int(float(row[6]) * imageHeight)
]]
line_num += 1
i = 0
while (i < len(Efix)):
start = Efix[i][0]
end = Efix[i][1]
print(startTime, end)
if (startTime > end):
Efix.remove(Efix[i])
continue
if (endTime < start):
Efix.remove(Efix[i])
continue
i += 1
draw_heatmap(Efix, (imageWidth, imageHeight),
image,
savefilename=saveLocation)
print(Efix)
def read_files(reduced, csvonly):
# Loop through all files
for ppname in PPS:
print("loading gaze data")
# path
fp = os.path.join(DATADIR, '%s.tsv' % ppname)
# check if the path exist
if not os.path.isfile(fp):
raise Exception(
"No eye data file file found for participant '%s'" % (ppname))
# read the file
tobiidata = read_tobii(fp, reduced, missing=0.0, debug=True)
#save_csv(tobiidata)
pplotdir = os.path.join(PLOTDIR, ppname[:3])
if not csvonly:
print("plotting gaze data")
# Loop through trials
for trialnr in range(len(tobiidata)):
# Load image name, saccades, and fixations
imgname = "screenshot.jpg"
imagefile = os.path.join(IMGDIR, imgname)
print(imagefile)
# [starttime, endtime, duration, startx, starty, endx, endy]
saccades = tobiidata[trialnr]['events']['Esac']
# [starttime, endtime, duration, endx, endy]
fixations = tobiidata[trialnr]['events']['Efix']
# cognitive load
if int(ppname[4:5]) == 1:
cognitive_load = "LOW"
else:
cognitive_load = "HIGH"
if reduced:
suffix = "_reduced"
else:
suffix = ""
# Save the fixation and saccades in csv format for MATLAB
save_csv(fixations, saccades, ppname, suffix)
if not csvonly:
# paths
rawplotfile = os.path.join(
pplotdir,
"raw_data_%s_%s%s" % (ppname[:3], cognitive_load, suffix))
scatterfile = os.path.join(
pplotdir,
"fixations_%s_%s%s" % (ppname[:3], cognitive_load, suffix))
scanpathfile = os.path.join(
pplotdir,
"scanpath_%s_%s%s" % (ppname[:3], cognitive_load, suffix))
heatmapfile = os.path.join(
pplotdir,
"heatmap_%s_%s%s" % (ppname[:3], cognitive_load, suffix))
# raw data points
draw_raw(tobiidata[trialnr]['x'],
tobiidata[trialnr]['y'],
DISPSIZE,
imagefile=None,
savefilename=rawplotfile)
# fixations
draw_fixations(fixations,
DISPSIZE,
imagefile=None,
durationsize=True,
durationcolour=False,
alpha=0.5,
savefilename=scatterfile)
# scanpath
draw_scanpath(fixations,
saccades,
DISPSIZE,
imagefile=None,
alpha=0.5,
savefilename=scanpathfile)
# heatmap
draw_heatmap(fixations,
DISPSIZE,
imagefile=None,
durationweight=True,
alpha=0.5,
savefilename=heatmapfile)
def heatMap(startTime, endTime, totalTime):
#(in seconds)
#start time of video segment you want to extract
#end time of video segment you want to extract
#total time of video
#saveLocation: location where output heatmap is to be saved
#gazeFilePath: location of gaze csv
#videoLocation: location of video
#imageWidth and IimageHeight: dimension of a frame in a video
saveLocation = '/Users/jeffhe/Desktop/commitments/urap/resources/heatmap_processing/0308_1630_text_02/heatmap.png'
gazeFilePath = "/Users/jeffhe/Desktop/commitments/urap/resources/heatmap_processing/0308_1630_text_02/gaze_positions.csv"
videoLocation = "/Users/jeffhe/Desktop/commitments/urap/resources/heatmap_processing/0308_1630_text_02/world.mp4"
imageWidth = 1280
imageHeight = 720
def StartTimeSeconds():
with open(gazeFilePath) as f:
reader = csv.reader(f)
reader = list(reader)
startTimeSeconds = float(reader[1][0])
return startTimeSeconds
startTimeSeconds = StartTimeSeconds() + startTime
endTimeSeconds = StartTimeSeconds() + endTime
vidcap = cv2.VideoCapture(videoLocation)
frames = []
success, image = vidcap.read()
frames += [image]
while success:
success, image = vidcap.read()
frames += [image]
startFrame = (startTime / totalTime) * len(frames)
endFrame = (endTime / totalTime) * len(frames)
image = frames[int((startFrame + endFrame) / 2)]
with open(gazeFilePath) as f:
reader = csv.reader(f)
line_num = 0
norm_pos_x = []
norm_pos_y = []
timeStamps = []
for row in reader:
if (line_num != 0):
if not (float(row[2]) < 0.5 or float(row[3]) > 1
or float(row[3]) < 0 or float(row[4]) > 1
or float(row[4]) < 0):
if (float(row[0]) > startTimeSeconds
and float(row[0]) < endTimeSeconds):
norm_pos_x += [int(float(row[3]) * 1280)]
norm_pos_y += [imageHeight - int(float(row[4]) * 720)]
timeStamps += [float(row[0])]
line_num += 1
count = 0
while (count < len(timeStamps)):
timeStamps[count] *= 1000
count += 1
Sfix, Efix = fixation_detection(norm_pos_x, norm_pos_y, timeStamps)
draw_heatmap(Efix, (imageWidth, imageHeight),
image,
savefilename=saveLocation)
#the above function call isn't necessary in Shaantam's case. The fixation data is stored in Efix
#in the form of [[start time, end time, duration, x-coordinates, y-coordinates][][]...]
#here, the y-coordinate is calculated from top (meaning that top pixel is 0, bottom pixel is 720)
return Efix
print i + 4
print gazedata[i]['events']['msg']
# imgname = gazedata[i]['events']['msg'][71][1].split()[-1]
imgname = imgs[i + 4]
imgname = imgname.split('.')[0] + '.jpg'
imgfile = os.path.join(IMGDIR, imgname)
print imgname, imgfile
# get the fixations
fixations = gazedata[i]['events']['Efix']
# get the saccades
saccades = gazedata[i]['events']['Esac']
# plot a heatmap
gazeplotter.draw_heatmap(fixations,
RESOLUTION,
imagefile=imgfile,
alpha=0.5,
invert_x=True,
invert_y=False,
savefilename=os.path.join(
outdir, '%s_fix.png' % imgname))
gazeplotter.draw_fixations(fixations,
RESOLUTION,
imagefile=imgfile,
alpha=0.5,
invert_x=True,
invert_y=False,
savefilename=os.path.join(
outdir, '%s_heatmap.png' % imgname))
# gazeplotter.draw_scanpath(fixations, saccades, RESOLUTION, imagefile=imgfile,
# alpha=0.5, invert_x=True, invert_y=False,
