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)
def save_all_scanpath(self, bar):
"""
Saves all scanpaths, due to the number of positions, it applies clustering methods to have a better and more viewable image
:return: None
"""
rgb_im = self.image.convert('RGB')
rgb_im.save('converted_image.jpg')
dir = self.image_dir + "scanpath_images/"
if not os.path.exists(dir):
os.makedirs(dir)
for u_id in self.user_positions:
out = dir + u_id + "_scanpath.png"
pos = self.user_positions[u_id]
tmp = cluster_points(pos)
draw_scanpath(tmp, (self.rescaled_width, self.rescaled_height), imagefile='converted_image.jpg', savefilename=out)
bar.next()
gc.collect()
os.remove('converted_image.jpg')
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)
# 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 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)