def onSave(self, event):
nfHPM = 0 # number of frames in which head position is missing
nfHDM = 0 # number of frames in which head direction is missing
fp_ = self.fPath + '.csv'
fh = open(fp_, 'w')
fh.write('frame-index, hPosX, hPosY, mHPos, bPosX, bPosY, hDir, mHD\n')
for fi in range(1, self.frame_cnt + 1):
d_ = self.oData[fi]
if d_['hPos'] == ('None', 'None') or d_['hPos'] == ('D', 'D'):
nfHPM += 1 # head position is missing
if type(d_['hD']) != int: nfHDM += 1 # head direction is missing
line = '%i, %s, %s, %s, %s, %s, %s, %s\n' % (fi, str(
d_['hPos'][0]), str(d_['hPos'][1]), str(
d_['mHPos']), str(d_['bPos'][0]), str(
d_['bPos'][1]), str(d_['hD']), str(d_['mHD']))
fh.write(line)
fh.write(
'------------------------------------------------------------------\n'
)
fh.write('Number of frames in which head position is missing, %i\n' %
nfHPM)
fh.write('Number of frames in which head direction is missing, %i\n' %
nfHDM)
fh.close()
msg = 'Saved.\n'
chr_num = 50 # characters in one line
if len(fp_) > chr_num:
for i in range(len(fp_) / chr_num):
msg += '%s\n' % (fp_[chr_num * i:chr_num * (i + 1)])
msg += '%s\n' % (fp_[chr_num * (i + 1):])
show_msg(msg, size=(400, 200))
def onSave(self, event):
WD = 0 # walking distance
HM = 0 # head movements without walking (~ looking around)
nfH = 0 # number of frames when only head tag is detected
nfT = 0 # number of frames when only tail tag is detected
nfB = 0 # number of frames when only both tags are detected
nfN = 0 # number of frames when only no tags were detected
fp_ = self.fPath + '.csv'
fh = open(fp_, 'w')
fh.write('frame-index, hPosX, hPosY, tbPosX, tbPosY, WD, HM, h2ac_dist\n')
hsf = self.vFPS/2 # half second frames
for fi in range(1, self.frame_cnt+1):
h_ = self.oData[fi]['hPos']
t_ = self.oData[fi]['tbPos']
if type(h_[0]) == int and type(t_[0]) == int: nfB += 1
elif type(h_[0]) == int and type(t_[0]) != int: nfH += 1
elif type(h_[0]) != int and type(t_[0]) == int: nfT += 1
elif type(h_[0]) != int and type(t_[0]) != int: nfN += 1
wd_ = 0; hm_ = 0
if fi > (hsf) and fi % hsf == 0:
### every half second, calculate walking-distance and head-movement
ph_ = self.oData[fi-hsf]['hPos']
pt_ = self.oData[fi-hsf]['tbPos']
if type(h_[0])==int and type(h_[1])==int and type(ph_[0])==int and type(ph_[1])==int: # all the head position info available
hl = np.sqrt( (h_[0]-ph_[0])**2 + (h_[1]-ph_[1])**2 ) # line connecting two head tag positions
if hl > (self.tagSz/2): # if movement distance is too small, discard
if type(t_[0])==int and type(t_[1])==int and type(pt_[0])==int and type(pt_[1])==int: # all the tail position info available
hla = np.degrees(np.arctan2( (h_[1]-ph_[1]), (h_[0]-ph_[0]) )) # degree of line connecting two head tag positions
tla = np.degrees(np.arctan2( (t_[1]-pt_[1]), (t_[0]-pt_[0]) )) # degree of line connecting two tail tag positions
angle_diff = calc_angle_diff(hla, tla)
if angle_diff < 45: # 45 degrees difference is considered as more or less similar direction to account it as 'walking'
wd_ = hl # walking distance for one frame
WD += hl # total walking distance
if wd_ == 0:
# if walking didn't happen, hl is recorded as head movement
hm_ = hl
HM += hl
line = '%i, %s, %s, %s, %s, %i, %i, %s\n'%(fi, str(h_[0]), str(h_[1]), str(t_[0]), str(t_[1]), wd_, hm_, str(self.oData[fi]['h2ac_dist']))
fh.write(line)
fh.write('------------------------------------------------------------------\n')
fh.write('Total walking distance, %i\n'%WD)
fh.write('Total head movements without walking, %i\n'%HM)
fh.write('------------------------------------------------------------------\n')
fh.write('Number of frames when both tags are detected, %i\n'%nfB)
fh.write('Number of frames when only head tag is detected, %i\n'%nfH)
fh.write('Number of frames when only tail tag is detected, %i\n'%nfT)
fh.write('Number of frames when no tags are detected, %i\n'%nfN)
fh.close()
msg = 'Saved.\n'
chr_num = 50 # characters in one line
if len(fp_) > chr_num:
for i in range(len(fp_)/chr_num):
msg += '%s\n'%(fp_[chr_num*i:chr_num*(i+1)])
msg += '%s\n'%(fp_[chr_num*(i+1):])
show_msg(msg, size=(400,200))
def start_arduino(self):
if DEBUG: print('CATOSFrame.start_arduino()')
self.mods["arduino"] = Arduino(self, self.output_folder)
if self.mods["arduino"].aConn == None:
return # !!! remove for actual setup. This is for testing purpose.
msg = "Arduino chip is not found.\nPlease connect it and retry."
show_msg(msg, self.panel)
self.onClose(None)
writeFile(self.log_file_path,
"%s, [CATOS], arduino mod init.\n" % (get_time_stamp()))
def onClose(self, event):
self.timer.Stop()
result = True
if self.session_start_time != -1: # session is running
result = show_msg(msg='Session is not stopped..\nUnsaved data will be lost. (Stop analysis or Cmd+S to save.)\nOkay to proceed to exit?', cancel_btn = True)
if result == True:
if self.cv_proc.video_rec != None: self.cv_proc.stop_video_rec()
wx.FutureCall(500, self.Destroy)
def start_arduino(self):
self.mods["arduino"] = Arduino(self, self.output_folder)
if self.mods["arduino"].aConn == None:
show_msg('Arduino chip is not found.\nPlease connect it and retry.', self.panel)
self.onClose(None)
writeFile(self.log_file_path, '%s, [CATOS], arduino mod init.\n'%(get_time_stamp()))
def onStartStopAnalyzeVideo(self, event):
'''Choose a video file and starts analysis'''
if self.session_start_time == -1: # not in analysis session. start a session
dlg = wx.DirDialog(self, "Choose directory for analysis", getcwd(),
wx.DD_DEFAULT_STYLE | wx.DD_DIR_MUST_EXIST)
if dlg.ShowModal() == wx.ID_CANCEL: return
self.fPath = dlg.GetPath()
self.frame_cnt = len(glob(path.join(self.fPath, 'f*.jpg')))
if self.frame_cnt == 0:
show_msg('No jpg frame images in the chosen directory.')
self.fPath = ''
return
if path.isfile(path.join(self.fPath, 'bg.jpg')) == False:
show_msg(
msg="'bg.jpg' file is not found in the chosen directory.",
cancel_btn=False)
return
self.cv_proc.bg = load_img(path.join(self.fPath, 'bg.jpg'),
flag='cv') # load background image
self.cv_proc.bg = self.onLoadImg(self.cv_proc.bg)
self.onChangeAnimalSp(None) # set default parameters of cv_proc
self.sTxt_fp.SetLabel('%s' % (path.basename(self.fPath)))
result_csv_file = self.fPath + '.csv'
if path.isfile(
result_csv_file) == False: # result CSV file doesn't exist
for i in range(1, self.frame_cnt + 1):
self.oData[i] = dict(
hPos=('None', 'None'),
mHPos=False,
bPos=('None', 'None'),
hD='None',
mHD=False
) # head position, head position was manually determined, base of head(around nect), head direction, head direction was manually determined
else: # result CSV file exists
f = open(result_csv_file, 'r')
lines = f.readlines()
f.close()
for i in range(1, self.frame_cnt + 1):
self.oData[i] = dict(hPos=('None', 'None'),
mHPos=False,
bPos=('None', 'None'),
hD='None',
mHD=False)
if i < len(lines):
items = [x.strip() for x in lines[i].split(',')]
idx_ = int(items[0])
if items[1] == 'None': hPos_val = ('None', 'None')
elif items[1] == 'D': hPos_val = ('D', 'D')
else: hPos_val = (int(items[1]), int(items[2]))
if items[3] == 'True': mHPos_val = True
else: mHPos_val = False
if items[4] == 'None': bPos_val = ('None', 'None')
elif items[4] == 'D': bPos_val = ('D', 'D')
else: bPos_val = (int(items[4]), int(items[5]))
if items[6] == 'None': hD_val = 'None'
elif items[6] == 'D': hD_val = 'D'
else: hD_val = int(items[6])
if items[7] == 'True': mHD_val = True
else: mHD_val = False
self.oData[idx_]['hPos'] = copy(hPos_val)
self.oData[idx_]['mHPos'] = copy(mHPos_val)
self.oData[idx_]['bPos'] = copy(bPos_val)
self.oData[idx_]['hD'] = copy(hD_val)
self.oData[idx_]['mHD'] = copy(mHD_val)
self.fi = 1
self.session_start_time = time()
self.btn_start.SetLabel('Stop analysis')
### start video recorder
self.video_path = self.fPath + '.avi'
fp = path.join(self.fPath, self.filenames % self.fi)
img = load_img(fp, flag='cv')
img = self.onLoadImg(img)
self.cv_proc.start_video_rec(self.video_path, img)
self.proc_img() # process 1st image
else: # in session. stop it.
result = show_msg(msg='Save data?', cancel_btn=True)
if result == True: self.onSave(None)
if self.is_running == True: self.onSpace(None)
self.session_start_time = -1
self.sTxt_s_time.SetLabel('0:00:00')
self.btn_start.SetLabel('Analyze video (folder)')
self.sTxt_fp.SetLabel('')
self.loaded_img.SetBitmap(wx.NullBitmap)
self.fPath = ''
self.frame_cnt = 0
self.fi = 0
self.oData = {}
self.cv_proc.stop_video_rec()
def onStartStopAnalyzeVideo(self, event):
'''Choose a video file and starts analysis'''
if self.session_start_time == -1: # not in analysis session. start a session
dlg = wx.DirDialog(self, "Choose directory for analysis", getcwd(), wx.DD_DEFAULT_STYLE|wx.DD_DIR_MUST_EXIST)
if dlg.ShowModal() == wx.ID_CANCEL: return
self.fPath = dlg.GetPath()
self.sString = self.fPath[-8:]
self.frame_cnt = len(glob(path.join(self.fPath, '*.jpg')))
if self.frame_cnt == 0:
show_msg('No jpg frame images in the chosen directory.')
self.fPath = ''
return
fNames = self.fPath.split('/')
self.sTxt_fp.SetLabel( '%s / %s / %s / %s'%(fNames[-4],fNames[-3],fNames[-2],fNames[-1]) )
result_csv_file = self.fPath + '.csv'
if path.isfile(result_csv_file) == False: # result CSV file doesn't exist
for i in range(1, self.frame_cnt+1):
self.oData[i] = dict( hPos = (None,None), tbPos = (None,None), h2ac_dist = None )
# hPos: head tag position,
# tbPos: tail-base tag position,
# h2ac_dist: distance from the head tag to the arena center
else: # result CSV file exists
f = open(result_csv_file, 'r')
lines = f.readlines()
f.close()
for i in range(1, self.frame_cnt+1):
self.oData[i] = dict( hPos = (None,None), tbPos = (None,None), h2ac_dist = None )
if i < len(lines):
items = [ x.strip() for x in lines[i].split(',') ]
idx_ = int(items[0])
if items[1] == 'None': hPos_val = (None, None)
elif items[1] == 'D': hPos_val = ('D', 'D')
else: hPos_val = ( int(items[1]), int(items[2]) )
if items[3] == 'None': tbPos_val = (None, None)
elif items[3] == 'D': tbPos_val = ('D', 'D')
else: tbPos_val = ( int(items[3]), int(items[4]) )
if items[7] == 'None': h2ac_dist_val = None
else: h2ac_dist_val = int(items[7])
self.oData[idx_]['hPos'] = copy(hPos_val)
self.oData[idx_]['tbPos'] = copy(tbPos_val)
self.oData[idx_]['h2ac_dist'] = copy(h2ac_dist_val)
self.fi = 1
self.session_start_time = time()
self.btn_start.SetLabel('Stop analysis')
### start video recorder
self.video_path = self.fPath + '.avi'
fp = path.join(self.fPath, 'f%06i.jpg'%self.fi)
img = load_img(fp, flag='cv')
self.cv_proc.start_video_rec( self.video_path, img )
self.proc_img() # process 1st image
else: # in session. stop it.
result = show_msg(msg='Save data?', cancel_btn = True)
if result == True: self.onSave(None)
if self.is_running == True: self.onSpace(None)
self.session_start_time = -1
self.sTxt_s_time.SetLabel('0:00:00')
self.btn_start.SetLabel('Analyze video (folder)')
self.sTxt_fp.SetLabel('')
self.loaded_img.SetBitmap(wx.NullBitmap)
self.fPath = ''
self.sString = ''
self.frame_cnt = 0
self.fi = 0
self.oData = {}
self.cv_proc.stop_video_rec()