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import os, sys
import numpy as np
import PIL
from PIL import Image
import io
from datetime import datetime, timedelta,date
import time
from matplotlib.dates import date2num, num2date
# import colour_demosaicing
import skvideo.io
import re
import pickle
import cv2
import progressbar as pb
# Create interface sr for reading seq files.
# sr = seqIo_reader( fName )
# Create interface sw for writing seq files.
# sw = seqIo_Writer( fName, header )
# Crop sub-sequence from seq file.
# seqIo_crop( fName, 'crop', tName, frames )
# Extract images from seq file to target directory or array.
# Is = seqIo_toImgs( fName, tDir=[],skip=1,f0=0,f1=np.inf,ext='' )
# Create seq file from an array or directory of images or from an AVI file. DONE
# seqIo_frImgs( fName, fName,header,aviName=[],Is=[],sDir=[],name='I',ndig=5,f0=0,f1=1e6 )
# Convert seq file by applying imgFun(I) to each frame I.
# seqIo( fName, 'convert', tName, imgFun, varargin )
# Replace header of seq file with provided info.
# seqIo( fName, 'newHeader', info )
# Create interface sr for reading dual seq files.
# sr = seqIo( fNames, 'readerDual', [cache] )
FRAME_FORMAT_RAW_GRAY = 100 #RAW
FRAME_FORMAT_RAW_COLOR = 200 #RAW
FRAME_FORMAT_JPEG_GRAY = 102 #JPG
FRAME_FORMAT_JPEG_COLOR = 201 #JPG
FRAME_FORMAT_MONOB = 101 #BRGB8
FRAME_FORMAT_MONOB_JPEG = 103 #JBRGB
FRAME_FORMAT_PNG_GRAY = 0x001 #PNG
FRAME_FORMAT_PNG_COLOR = 0x002 #PNG
#matlab equivalent fread
def fread(fid, nelements, dtype):
"""Equivalent to Matlab fread function"""
if dtype is np.str_:
dt = np.uint8 # WARNING: assuming 8-bit ASCII for np.str!
else:
dt = dtype
data_array = np.fromfile(fid, dt, nelements)
if data_array.size == 1:
data_array = data_array[0]
return data_array
def fwrite(fid,a,dtype=np.str_):
# assuming 8but ASCII for string
if dtype is np.str_:
dt = np.uint8 # WARNING: assuming 8-bit ASCII for np.str!
else:
dt = dtype
if isinstance(a,np.ndarray):
data_array = a.astype(dt)
else:
data_array = np.array(a).astype(dt)
data_array.tofile(fid)
def tsSync(video_path, srTop, srFront):
#tsSync
name = video_path.split('/')[-1]
srDepth=seqIo_reader(video_path + '/' + name + '_DepGr_Raw.seq')
#read timestamp of individual frames
tsTop = srTop.getTs()
tsFront = srFront.getTs()
tsDepth = srDepth.getTs()
#check the version of the videos
videoDateStr = re.search('[0-9]+_[0-9]+-[0-9]+-[0-9]+',name).group(0)
videoDateNum =date2num(datetime.strptime(videoDateStr ,'%Y%m%d_%H-%M-%S'))
videoRefNum = date2num(datetime.strptime('20150401_00-00-00','%Y%m%d_%H-%M-%S'))
seqV = 1 if videoDateNum < videoRefNum else 2
##correlate timestamps from one view to another
mapTs = {}
if seqV ==1:
for f in range(len(tsDepth)):
if tsDepth[f] - np.floor(tsDepth[f])>=.5: # Santiago's bug acquisistion software
tsDepth[f]-= 1
tsDepth-= 0.03 # substract the systematic timeshift
#load front and top view and convert from UTC to PST
hourShift = np.round((tsDepth[0]-tsTop[0])/3600.)*3600
timeShift = tsDepth[0] - tsTop[0] - .066
# print('tsDepth[0] - tsTop[0] = timeShift: %s sec'% str(timeShift - hourShift))
tsTop += timeShift
tsFront += timeShift
srTop.ts = tsTop
srFront.ts = tsFront
srDepth.ts = tsDepth
# Convert timestamps from left to right
mapTs['T2F'] = transformTs(tsTop, tsFront)
mapTs['F2T'] = transformTs(tsFront, tsTop)
mapTs['T2D'] = transformTs(tsTop, tsDepth)
mapTs['D2T'] = transformTs(tsDepth, tsTop)
mapTs['F2D'] = transformTs(tsFront, tsDepth)
mapTs['D2F'] = transformTs(tsDepth, tsFront)
else:
T = len(tsTop)
F = len(tsFront)
D = len(tsDepth)
mapTs['T2F'] = resizeTs(T,F)
mapTs['F2T'] = resizeTs(F,T)
mapTs['T2D'] = resizeTs(T,D)
mapTs['D2T'] = resizeTs(D,T)
mapTs['F2D'] = resizeTs(F,D)
mapTs['D2F'] = resizeTs(D,F)
#display the time in string format
# fTp=5
# fFr = mapTs['T2F'][fTp]
# fDp = mapTs['T2D'][fTp]
# tF = ts2str(tsFront[fFr])
# tT = ts2str(tsTop[fTp])
# tD = ts2str(tsDepth[fDp])
#
# print('mapping to tTop:')
# print('tTop = ' + str(fTp) + ' - ' + tT)
# print('tFront = ' + str(fFr) + ' - ' + tF)
# print('tDepth = ' + str(fDp) + ' - ' + tD)
# fDp = np.round(len(tsDepth)/1.5).astype(int)
# fTp = mapTs['D2T'][fDp]
# tT = ts2str(tsTop[fTp])
# tD = ts2str(tsDepth[fDp])
# print('mapping to tTop:')
# print('tTop = ' + str(fTp) + '. ' + tT)
# print('tDepth = ' + str(fDp) + '. ' + tD)
return mapTs,srTop,srFront
def transformTs(ts1, ts2):
# map ts1 to ts2 where ts2 is the reference
rankTs = np.zeros((len(ts1),4))
for f in range(len(ts1)):
tsDiff = ts2-ts1[f]
tsRank = np.sort(abs(tsDiff))
ind = np.argsort(abs(tsDiff))
rankTs[f,:] = [ind[0]+1,ind[1]+1,tsRank[0],tsRank[1]]
mapTs = np.round(smooth(rankTs[:,0],7)).astype(int)
mapTs = np.round(smooth(mapTs,7)).astype(int)
return mapTs
def smooth(a, WSZ):
out0 = np.convolve(a, np.ones(WSZ, dtype=int), 'valid') / WSZ
r = np.arange(1, WSZ - 1, 2)
start = np.cumsum(a[:WSZ - 1])[::2] / r
stop = (np.cumsum(a[:-WSZ:-1])[::2] / r)[::-1]
return np.concatenate((start, out0, stop))
def resizeTs(t1, t2):
if t1>t2:
mapTs = np.hstack((np.array(range(t2))+1,np.ones((t1-t2),int)*t2))
else:
mapTs = np.array(range(t1))+1
return mapTs
def ts2str(ts):
t = ts / 86400. + date.toordinal(date(1971, 1, 2))
# datetime.fromtimestamp(t)
str_time = (datetime.fromordinal(int(t)) + timedelta(days=t % 1) - timedelta(days=366)).strftime(
"%Y-%m-%d %H:%M:%S") + '.%03d' % np.round((ts - np.floor(ts)) * 1000)
return str_time
def parse_ann(f_ann):
header = 'Caltech Behavior Annotator - Annotation File'
conf = 'Configuration file:'
fid = open(f_ann)
ann = fid.read().splitlines()
fid.close()
NFrames = []
# check the header
assert ann[0].rstrip() == header
assert ann[1].rstrip() == ''
assert ann[2].rstrip() == conf
# parse action list
l = 3
names = [None] * 1000
keys = [None] * 1000
types = []
bnds = []
k = -1
# get config keys and names
while True:
ann[l] = ann[l].rstrip()
if not isinstance(ann[l], str) or not ann[l]:
l += 1
break
values = ann[l].split()
k += 1
names[k] = values[0]
keys[k] = values[1]
l += 1
names = names[:k + 1]
keys = keys[:k + 1]
# read in each stream in turn until end of file
bnds0 = [None] * 10000
types0 = [None] * 10000
actions0 = [None] * 10000
nStrm1 = 0
while True:
ann[l] = ann[l].rstrip()
nStrm1 += 1
t = ann[l].split(":")
l += 1
ann[l] = ann[l].rstrip()
assert int(t[0][1]) == nStrm1
assert ann[l] == '-----------------------------'
l += 1
bnds1 = np.ones((10000, 2), dtype=int)
types1 = np.ones(10000, dtype=int) * -1
actions1 = [None] * 10000
k = 0
# start the annotations
while True:
ann[l] = ann[l].rstrip()
t = ann[l]
if not isinstance(t, str) or not t:
l += 1
break
t = ann[l].split()
type = [i for i in range(len(names)) if t[2] == names[i]]
type = type[0]
if type == None:
print('undefined behavior' + t[2])
if bnds1[k - 1, 1] != int(t[0]) - 1 and k > 0:
print('%d ~= %d' % (bnds1[k, 1], int(t[0]) - 1))
bnds1[k, :] = [int(t[0]), int(t[1])]
types1[k] = type
actions1[k] = names[type]
k += 1
l += 1
if l == len(ann):
break
if nStrm1 == 1:
nFrames = bnds1[k - 1, 1]
assert nFrames == bnds1[k - 1, 1]
bnds0[nStrm1 - 1] = bnds1[:k]
types0[nStrm1 - 1] = types1[:k]
actions0[nStrm1 - 1] = actions1[:k]
if l == len(ann):
break
while not ann[l]:
l += 1
bnds = bnds0[:nStrm1]
types = types0[:nStrm1]
actions = actions0[:nStrm1]
idx = 0
if len(actions[0]) < len(actions[1]):
idx = 1
type_frame = []
action_frame = []
len_bnd = []
for i in range(len(bnds[idx])):
numf = bnds[idx][i, 1] - bnds[idx][i, 0] + 1
len_bnd.append(numf)
action_frame.extend([actions[idx][i]] * numf)
type_frame.extend([types[idx][i]] * numf)
ann_dict = {
'keys': keys,
'behs': names,
'nstrm': nStrm1,
'nFrames': nFrames,
'behs_se': bnds,
'behs_dur': len_bnd,
'behs_bout': actions,
'behs_frame': action_frame
}
return ann_dict
def parse_ann_dual(f_ann):
header = 'Caltech Behavior Annotator - Annotation File'
conf = 'Configuration file:'
fid = open(f_ann)
ann = fid.read().splitlines()
fid.close()
NFrames = []
# check the header
assert ann[0].rstrip() == header
assert ann[1].rstrip() == ''
assert ann[2].rstrip() == conf
# parse action list
l = 3
names = [None] * 1000
keys = [None] * 1000
types = []
bnds = []
k = -1
# get config keys and names
while True:
ann[l] = ann[l].rstrip()
if not isinstance(ann[l], str) or not ann[l]:
l += 1
break
values = ann[l].split()
k += 1
names[k] = values[0]
keys[k] = values[1]
l += 1
names = names[:k + 1]
keys = keys[:k + 1]
# read in each stream in turn until end of file
bnds0 = [None] * 10000
types0 = [None] * 10000
actions0 = [None] * 10000
nStrm1 = 0
while True:
ann[l] = ann[l].rstrip()
nStrm1 += 1
t = ann[l].split(":")
l += 1
ann[l] = ann[l].rstrip()
assert int(t[0][1]) == nStrm1
assert ann[l] == '-----------------------------'
l += 1
bnds1 = np.ones((10000, 2), dtype=int)
types1 = np.ones(10000, dtype=int) * -1
actions1 = [None] * 10000
k = 0
# start the annotations
while True:
ann[l] = ann[l].rstrip()
t = ann[l]
if not isinstance(t, str) or not t:
l += 1
break
t = ann[l].split()
type = [i for i in range(len(names)) if t[2] == names[i]]
type = type[0]
if type == None:
print('undefined behavior' + t[2])
if bnds1[k - 1, 1] != int(t[0]) - 1 and k > 0:
print('%d ~= %d' % (bnds1[k, 1], int(t[0]) - 1))
bnds1[k, :] = [int(t[0]), int(t[1])]
types1[k] = type
actions1[k] = names[type]
k += 1
l += 1
if l == len(ann):
break
if nStrm1 == 1:
nFrames = bnds1[k - 1, 1]
assert nFrames == bnds1[k - 1, 1]
bnds0[nStrm1 - 1] = bnds1[:k]
types0[nStrm1 - 1] = types1[:k]
actions0[nStrm1 - 1] = actions1[:k]
if l == len(ann):
break
while not ann[l]:
l += 1
bnds = bnds0[:nStrm1]
types = types0[:nStrm1]
actions = actions0[:nStrm1]
idx = 0
if len(actions[0]) < len(actions[1]):
idx = 1
type_frame = []
action_frame = []
len_bnd = []
for i in range(len(bnds[idx])):
numf = bnds[idx][i, 1] - bnds[idx][i, 0] + 1
len_bnd.append(numf)
action_frame.extend([actions[idx][i]] * numf)
type_frame.extend([types[idx][i]] * numf)
type_frame2 = []
action_frame2 = []
len_bnd2 = []
idx=1 if idx==0 else 0
for i in range(len(bnds[idx])):
numf = bnds[idx][i, 1] - bnds[idx][i, 0] + 1
len_bnd2.append(numf)
action_frame2.extend([actions[idx][i]] * numf)
type_frame2.extend([types[idx][i]] * numf)
ann_dict = {
'keys': keys,
'behs': names,
'nstrm': nStrm1,
'nFrames': nFrames,
'behs_se': bnds,
'behs_dur': len_bnd,
'behs_bout': actions,
'behs_frame': action_frame if 'interaction' not in action_frame else action_frame2,
'behs_frame2': action_frame2 if 'interaction' in action_frame2 else action_frame
}
return ann_dict
def syncTopFront(f,num_frames,num_framesf):
return int(round(f / (num_framesf - 1) * (num_frames - 1))) if num_framesf > num_frames else int(round(f / (num_frames - 1) * (num_framesf - 1)))
class seqIo_reader():
def __init__(self,fname,info=[],buildTable=True):
self.filename = fname
try:
self.file=open(fname,'rb')
except EnvironmentError as e:
print(os.strerror(e.errno))
self.header={}
self.seek_table=None
self.frames_read=-1
self.timestamp_length = 10
if info==[]:
self.readHeader()
else:
info.numFrames=0
if buildTable:
print("buildTable was True, so calling buildSeekTable()")
self.buildSeekTable(False)
def readHeader(self):
#make sure we do this at the beginning of the file
assert self.frames_read == -1, "Can only read header from beginning of file"
self.file.seek(0,0)
# pdb.set_trace()
# Read 1024 bytes (len of header)
tmp = fread(self.file,1024,np.uint8)
#check that the header is not all 0's
n=len(tmp)
if n<1024:raise ValueError('no header')
if all(tmp==0): raise ValueError('fully empty header')
self.file.seek(0,0)
#first 4 bytes stor 0XFEED next 24 store 'Norpix seq '
magic_number = fread(self.file,1,np.uint32)
name = fread(self.file,10,np.uint16)
name = ''.join(map(chr,name))
if not '{0:X}'.format(magic_number)=='FEED' or not name=='Norpix seq':raise ValueError('invalid header')
self.file.seek(4,1)
#next 8 bytes for version and header size (1024) then 512 for desc
version = int(fread(self.file,1,np.int32))
hsize =int(fread(self.file,1,np.uint32))
assert(hsize)==1024 ,"incorrect header size"
# d = self.file.read(512)
descr=fread(self.file,256,np.uint16)
# descr = ''.join(map(chr,descr))
# descr = ''.join(map(unichr,descr)).replace('\x00',' ')
descr = ''.join([chr(x) for x in descr]).replace('\x00',' ')
# descr = descr.encode('utf-8')
#read more info
tmp = fread(self.file,9,np.uint32)
assert tmp[7]==0, "incorrect origin"
fps = fread(self.file,1,np.float64)
codec = 'imageFormat' + '%03d'%tmp[5]
desc_format = fread(self.file,1,np.uint32)
padding = fread(self.file,428,np.uint8)
padding = ''.join(map(chr,padding))
#store info
self.header={'magicNumber':magic_number,
'name':name,
'seqVersion': version,
'headerSize':hsize,
'descr': descr,
'width':int(tmp[0]),
'height':int(tmp[1]),
'imageBitDepth':int(tmp[2]),
'imageBitDepthReal':int(tmp[3]),
'imageSizeBytes':int(tmp[4]),
'imageFormat':int(tmp[5]),
'numFrames':int(tmp[6]),
'origin':int(tmp[7]),
'trueImageSize':int(tmp[8]),
'fps':fps,
'codec':codec,
'descFormat':desc_format,
'padding':padding,
'nHiddenFinalFrames':0
}
assert(self.header['imageBitDepthReal']==8)
# seek to end fo header
self.file.seek(432,1)
self.frames_read += 1
self.imageFormat = self.header['imageFormat']
if self.imageFormat in (100,200): self.ext = 'raw'
elif self.imageFormat in (102,201): self.ext = 'jpg'
elif self.imageFormat in(0x001,0x002): self.ext = 'png'
elif self.imageFormat == 101: self.ext = 'brgb8'
elif self.imageFormat == 103: self.ext = 'jbrgb'
else: raise ValueError('uknown format')
self.compressed = True if self.ext in ['jpg','jbrgb','png','brgb8'] else False
self.bit_depth = self.header['imageBitDepth']
# My code uses a timestamp_length of 10 bytes, old uses 8. Check if not 10
if self.bit_depth / 8 * (self.header['height'] * self.header['width']) + self.timestamp_length \
!= self.header['trueImageSize']:
# If not 10, adjust to actual (likely 8) and print message
self.timestamp_length = int(self.header['trueImageSize'] \
- (self.bit_depth / 8 * (self.header['height'] * self.header['width'])))
def buildSeekTable(self,memoize=False):
"""Build a seek table containing the offset and frame size for every frame in the video."""
print("in seqIo_reader.buildSeekTable()")
pickle_name = self.filename.strip(".seq") + ".seek"
if memoize:
if os.path.isfile(pickle_name):
self.seek_table = pickle.load(open(pickle_name, 'rb'))
return
# assert self.header['numFrames']>0
n=self.header['numFrames']
if n==0:n=1e7
seek_table = np.zeros((n)).astype(np.int64)
seek_table[0]=1024
extra = 8 # extra bytes after image data , 8 for ts then 0 or 8 empty
self.file.seek(1024,0)
#compressed case
if self.compressed:
i=1
while (True):
try:
# size = fread(self.file,1,np.uint32)
# offset = seek_table[i-1] + size +extra
# seek_table[i]=offset
# # seek_table[i-1,1]=size
# self.file.seek(size-4+extra,1)
size = fread(self.file, 1, np.uint32)
offset = seek_table[i - 1] + size + extra
# self.file.seek(size-4+extra,1)
self.file.seek(offset, 0)
if i == 1:
if fread(self.file, 1, np.uint32) != 0:
self.file.seek(-4, 1)
else:
extra += 8;
offset += 8
self.file.seek(offset, 0)
seek_table[i] = offset
# seek_table[i-1,1]=size
i+=1
except Exception as e:
break
#most likely EOF
else:
#uncompressed case
assert (self.header['numFrames']>0)
frames = range(0, self.header["numFrames"])
offsets = [x * self.header["trueImageSize"] + 1024 for x in frames]
for i,offset in enumerate(offsets):
seek_table[i]=offset
# seek_table[i,1]=self.header["imageSize"]
if n==1e7:
n = np.minimum(n,i)
self.seek_table=seek_table[:n]
self.header['numFrames']=n
else:
self.seek_table=seek_table
if memoize:
pickle.dump(seek_table,open(pickle_name,'wb'))
#compute frame rate from timestamps as stored fps may be incorrect
# if n==1: return
self.getTs()
# ds = self.ts[1:100]-self.ts[:99]
# ds = ds[abs(ds-np.median(ds))<.005]
# if bool(np.prod(ds)): self.header['fps']=1/np.mean(ds)
def getTs(self, n=None):
if n==None: n=self.header['numFrames']
if self.compressed and self.seek_table is None:
self.buildSeekTable()
ts = np.zeros((n))
for i in range(n):
if not self.compressed: #uncompressed
self.file.seek(1024 + i*self.header['trueImageSize']+self.header['imageSizeBytes'],0)
else: #compressed
self.file.seek(self.seek_table[i],0)
self.file.seek(fread(self.file,1,np.uint32)-4,1)
# print(i)
ts[i]=fread(self.file,1,np.uint32)+fread(self.file,1,np.uint16)/1000.
self.ts=ts
return self.ts
def getFrame(self,index,decode=True):
#get frame image (I) and timestamp (ts) at which frame was recorded
nch = self.header['imageBitDepth']/8
if self.ext in ['raw','brgb8']: #read in an uncompressed image( assume imageBitDepthReal==8)
shape = (self.header['height'], self.header['width'])
self.file.seek(1024 + index*self.header['trueImageSize'],0)
I = fread(self.file,self.header['imageSizeBytes'],np.uint8)
if decode:
if nch==1:
I=np.reshape(I,shape)
else:
I=np.reshape(I,(shape,nch))
if nch==3:
t=I[:,:,2]; I[:,:,2]=I[:,:,0]; I[:,:,1]=t
if self.ext=='brgb8':
I= cv2.demosaicing(I, code=cv2.COLOR_BAYER_BG2BGR)
# I= colour_demosaicing.demosaicing_CFA_Bayer_bilinear(I,'BGGR')
elif self.ext in ['jpg','jbrgb']:
self.file.seek(self.seek_table[index],0)
nBytes = fread(self.file,1,np.uint32)
data = fread(self.file,nBytes-4,np.uint8)
if decode:
I = PIL.Image.open(io.BytesIO(data))
if self.ext == 'jbrgb':
I= cv2.demosaicing(I, code=cv2.COLOR_BAYER_BG2BGR)
# I=colour_demosaicing.demosaicing_CFA_Bayer_bilinear(I,'BGGR')
else:
I = data
elif self.ext=='png':
self.file.seek(self.seek_table[index],0)
nBytes = fread(self.file,1,np.uint32)
I= fread(self.file,nBytes-4,np.uint8)
if decode:
I= np.array(I).transpose(range(I.shape,-1,-1))
else: assert(False)
ts = fread(self.file,1,np.uint32)+fread(self.file,1,np.uint16)/1000.
return np.array(I), ts
# Close the file
def close(self):
self.file.close()
class seqIo_writer():
def __init__(self,filename,old_header):
self.file = open(filename,'wb')
self.file.seek(0,0)
self.header=old_header
#create space for header
fwrite(self.file,np.zeros(1024).astype(int),np.uint8)
assert(set(['width','height','fps','codec']).issubset(self.header.keys()))
codec = self.header['codec']
if codec in ['monoraw', 'imageFormat100']: self.frmt = 100;self.nch = 1;self.ext = 'raw'
elif codec in ['raw', 'imageFormat200']: self.frmt = 200;self.nch = 3;self.ext = 'raw'
elif codec in ['monojpg', 'imageFormat102']: self.frmt = 102;self.nch = 1;self.ext = 'jpg'
elif codec in ['jpg', 'imageFormat201']: self.frmt = 201;self.nch = 3;self.ext = 'jpg'
elif codec in ['monopng', 'imageFormat001']: self.frmt = 0x001;self.nch = 1;self.ext = 'png'
elif codec in ['png', 'imageFormat002']: self.frmt = 0x002;self.nch = 3;self.ext = 'png'
else: raise ValueError('unknown format')
self.header['imageFormat']=self.frmt
self.header['imageBitDepth']=8*self.nch
self.header['imageBitDepthReal']=8
nBytes = self.header['width']*self.header['height']*self.nch
self.header['imageSizeBytes']=nBytes
self.header['numFrames']=0
self.header['trueImageSize']=nBytes + 6 +512-np.mod(nBytes+6,512)
# Close the file
def close(self):
self.writeHeader()
self.file.close()
def writeHeader(self):
self.file.seek(0,0)
# first write 4 bytes to store 0XFEED, next 24 store 'Nrpix seq '
fwrite(self.file,int('FEED',16),np.uint32)
name = np.array(['Norpix seq ']).view(np.uint8)
fwrite(self.file,name, np.uint16)
# next 8 bytes for version (3) and header size (1024) then 512 for descr
fwrite(self.file,[3,1024],np.int32)
if not 'descr' in self.header.keys() or len(np.array([self.header['descr']]).view(np.uint8))>256: d = np.array(['No Description']).view(np.uint8)
else: d= np.array([self.header['descr']]).view(np.uint8)
d = np.concatenate((d[:np.minimum(256,len(d))],np.zeros(256-len(d)).astype(np.uint8)))
fwrite(self.file,d,np.uint16)
#write remaining info
vals= [self.header['width'],self.header['height'],self.header['imageBitDepth'],self.header['imageBitDepthReal'],
self.header['imageSizeBytes'],self.header['imageFormat'],self.header['numFrames'],0,self.header['trueImageSize']]
fwrite(self.file,vals,np.uint32)
#store frame rate nad pad with 0s
fwrite(self.file,self.header['fps'],np.float64)
fwrite(self.file,np.zeros(432),np.uint8)
def addFrame(self,I,ts=0,encode=1):
nCh = self.header['imageBitDepth']/8
ext = self.ext
c = self.header['numFrames']+1
if encode:
siz = [self.header['height'],self.header['width'],nCh]
assert(I.shape[0]==siz[0] and I.shape[1]==siz[1])
if len(I.shape)==3:
assert(I.shape[2]==siz[2] or I.shape[2]==self.nch)
if ext=='raw':
#write uncompressed image and assume imageBitDepthReal==8
if not encode : assert(I.size==self.header['imageSizeBytes'])
else:
if nCh==3: t=I[:,:,2]; I[:,:,2]=I[:,:,0];I[:,:,0]=t
if nCh==1: I=I.transpose()
else: I = np.transpose( np.expand_dims(I, axis=2), (2, 1, 0) )
# I= I.flat.view(np.uint8)
I= I.flat
fwrite(self.file,I,np.uint8)
pad = self.header['trueImageSize']-self.header['imageSizeBytes']-6
if ext =='jpg':
if encode:
#write red from to temporary jpg
cv2.imwrite('tmp.jpg',I, [int(cv2.IMWRITE_JPEG_QUALITY ),80])
# j=Image.fromarray(I.astype(np.uint8))
# j.save('tmp.jpg')
# I=Image.open('tmp.jpg')
fid = open('tmp.jpg','r')
I = fid.read()
fid.close()
b=bytearray(I)
assert (b[0] == 255 and b[1] == 216 and b[-2] == 255 and b[-1] == 217); # JPG
os.remove('tmp.jpg')
I = np.array(list(b)).astype(np.uint8)
nbytes = len(I)+4
fwrite(self.file,nbytes,np.uint32)
# self.file.write(I)
fwrite(self.file,I,np.uint8)
pad = 10
if ts==0: ts = (c-1)/self.header['fps']
s = int(np.floor(ts))
ms = int(np.round(np.mod(ts,1)*1000))
fwrite(self.file,s,np.int32)
fwrite(self.file,ms,np.uint16)
self.header['numFrames']=c
if pad>0:
pad = np.zeros(pad).astype(np.uint8)
fwrite(self.file,pad,np.uint8)
def seqIo_crop(fname, tname, frames):
"""
Crop sub-sequence from seq file.
Frame indices are 0 indexed. frames need not be consecutive and can
contain duplicates. An index of -1 indicates a blank (all 0) frame. If
contiguous subset of frames is cropped timestamps are preserved.
USAGE
seqIo( fName, 'crop', tName, frames )
INPUTS
fName - seq file name
tName - cropped seq file name
frames - frame indices (0 indexed)
"""
if not isinstance(frames, np.ndarray): frames=np.array(frames)
sr = seqIo_reader(fname)
sw = seqIo_writer(tname,sr.header)
pad,_= sr.getFrame(0)
pad = np.zeros(pad.size).astype(np.uint8)
kp = frames>=0 & frames<sr.header['numFrames']
if not np.all(kp): frames = frames[kp]
print('%i out of bounds frames'% np.sum(~kp))
ordered = np.all(frames[1:]==frames[:-1]+1)
n= frames.size
k=0
for f in frames:
if f<0:
sw.addFrame(pad)
continue
I,ts = sr.getFrame(f)
k+=1
if ordered:
sw.addFrame(I,ts)
else:
sw.addFrame(I)
sr.close()
sw.close
def seqIo_toImgs(fName, tDir=[], skip=1, f0=0, f1=np.inf, ext=''):
"""
Extract images from seq file to target directory or array.
USAGE
Is = seqIo( fName, 'toImgs', [tDir], [skip], [f0], [f1], [ext] )
INPUTS
fName - seq file name
tDir - [] target directory (if empty extract images to array)
skip - [1] skip between written frames
f0 - [0] first frame to write
f1 - [numFrames-1] last frame to write
ext - [] optionally save as given type (slow, reconverts)
OUTPUTS
Is - if isempty(tDir) outputs image array (else Is=[])
"""
sr = seqIo_reader(fName)
f1 = np.minimum(f1,sr.header['numFrames']-1)
frames = range(f0,f1,skip)
n=len(frames)
k=0
#output images to array
if tDir==[]:
I,_=sr.getFrame(0)
d = I.shape
assert(len(d)==2 or len(d)==3)
try:
Is = np.zeros((I.shape+(n,))).astype(I.dtype)
except:
sr.close()
raise
for k in range(n):
I,ts = sr.getFrame(k)
if len(d)==2:
Is[:,:,k]=I
else:
Is[:,:,:,k]=I
print('saved %d' % k)
sr.close()
# output image directory
if not os.path.exists(tDir):os.makedirs(tDir)
if tDir.split('/')[-1]!='/':tDir+'/'
Is = np.array([])
for frame in frames:
f = tDir + 'I%05.' % (frame)
I, ts = sr.getFrame(frame)
if ext!='':
cv2.imwrite(f+ext,I)
else:
cv2.imwrite(f+sr.ext)
k+=1
print('saved %d' % frame)
sr.close()
return Is
def seqIo_frImgs(fName, header=[], aviName=[], Is=[], sDir=[], name='I', ndig=5, f0=0, f1=1e6):
"""
Create seq file from an array or directory of images or from an AVI file.
For info, if converting from array, only codec (e.g., 'jpg') and fps must
be specified while width and height and determined automatically. If
converting from AVI, fps is also determined automatically.
USAGE
seqIo( fName, 'frImgs', info, varargin )
INPUTS
fName - seq file name
info - defines codec, etc, see seqIo>writer
varargin - additional params (struct or name/value pairs)
.aviName - [] if specified create seq from avi file
.Is - [] if specified create seq from image array
.sDir - [] source directory
.skip - [1] skip between frames
.name - ['I'] base name of images
.nDigits - [5] number of digits for filename index
.f0 - [0] first frame to read
.f1 - [10^6] last frame to read
"""
if aviName!=[]: #avi movie exists
vc = cv2.VideoCapture(aviName)
if vc.isOpened(): rval = True
else:
rval = False
print('video not readable')
return
fps = vc.get(cv2.cv.CV_CAP_PROP_FPS)
NUM_FRAMES = int(vc.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT))
print(NUM_FRAMES)
IM_TOP_H = vc.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT)
IM_TOP_W = vc.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH)
header['width']=IM_TOP_W
header['height']=IM_TOP_H
header['fps']=fps
sw = seqIo_writer(fName,header)
print('creating seq from AVI')
# initialize timer
timer = pb.ProgressBar(widgets=['Converting ', pb.Percentage(), ' -- ',
pb.FormatLabel('Frame %(value)d'), '/',
pb.FormatLabel('%(max)d'), ' [', pb.Timer(), '] ',
pb.Bar(), ' (', pb.ETA(), ') '], maxval=NUM_FRAMES)
for f in range(NUM_FRAMES):
rval, im = vc.read()
if rval:
im= im.astype(np.uint8)
sw.addFrame(im)
timer.update(f)
sw.close()
timer.finish()
elif Is==[]:
assert(os.path.isdir(sDir))
sw = seqIo_writer(fName,header)
frmstr = '%s/%s%%0%ii.%s' % (sDir,name,ndig,header.ext)
for frame in range(f0,f1):
f = frmstr % frame
if not os.path.isfile(f):break
fid = open(f, 'r')
if fid<0: sw.close(); assert(False)
I = fid.read()
fid.close()
b = bytearray(I)
assert (b[0] == 255 and b[1] == 216 and b[-2] == 255 and b[-1] == 217); # JPG
I = np.array(list(b)).astype(np.uint8)
sw.addFrame(I,0,0)
sw.close()
if frame==f0: print('No images found')
else:
nd = len(Is.shape)
if nd==2: nd=3
assert(nd<=4)
nFrm = Is.shape[nd-1]
header['height']=Is.shape[0]
header['width']=Is.shape[1]
sw =seqIo_writer(fName,header)
if nd==3:
for f in range(nFrm): sw.addFrame(Is[:,:,f])
if nd==4:
for f in range(nFrm): sw.addFrame(Is[:,:,:,f])
sw.close()
def seqIo_convert(fName, tName, imgFun, info=[], skip=1, f0=0, f1=np.inf):
"""
Convert seq file by applying imgFun(I) to each frame I.
USAGE
seqIo( fName, 'convert', tName, imgFun, varargin )
INPUTS
fName - seq file name
tName - converted seq file name
imgFun - function to apply to each image
varargin - additional params (struct or name/value pairs)
.info - [] info for target seq file
.skip - [1] skip between frames
.f0 - [0] first frame to read
.f1 - [inf] last frame to read
"""
assert(fName!=tName)
sr = seqIo_reader(fName)
if info==[]: info=sr.header
n=sr.header['numFrames']
f1=np.minimum(f1,n-1)
I,ts=sr.getFrame(0)
I=imgFun(I)
info['width']=I.shape[1]
info['height']=I.shape[0]
sw =seqIo_writer(tName,info)
print('converting seq')
for frame in range(f0,f1,skip):
I, ts = sr.getFrame(frame)
I = imgFun(I)
if skip==1:
sw.addFrame(I,ts)
else:
sw.addFrameI
sw.close()
sr.close()
def seqIo_newHeader(fName, info):
"""
Replace header of seq file with provided info.
Can be used if the file fName has a corrupt header. Automatically tries
to compute number of frames in fName. No guarantees that it will work.
USAGE
seqIo( fName, 'newHeader', info )
INPUTS
fName - seq file name
info - info for target seq file
"""
d, n = os.path.split(fName)
if d==[]:d='./'
tName=fName[:-4] + '_new' + time.strftime("%d_%m_%Y") + fName[-4:]
sr = seqIo_reader(fName)
sw = seqIo_writer(tName,info)
n=sr.header['numFrames']
for f in range(n):
I,ts=sr.getFrame(f)
sw.addFrame(I,ts)
sr.close()
sw.close()
class seqIo_dualReader():
"""
seqIo_dualReader
Create interface sr for reading dual seq files.
Wrapper for two seq files of the same image dims and roughly the same
frame counts that are treated as a single reader object. getframe()
returns the concatentation of the two frames. For videos of different
frame counts, the first video serves as the "dominant" video and the
frame count of the second video is adjusted accordingly. Same general
usage as in reader, but the only supported operations are: close(),
getframe(), getinfo(), and seek().
USAGE
sr = seqIo( fNames, 'readerDual', [cache] )
INPUTS
fNames - two seq file names
cache - [0] size of cache (see seqIo>reader)
OUTPUTS
sr - interface for reading seq file
"""
def __init__(self,file1,file2):
self.s1 = seqIo_reader(file1)
self.s2 = seqIo_reader(file2)
self.info = self.s1.header
#set the display to be vertically align
self.info['height']=self.s1.header['height']+self.s2.header['height']
self.info['width']=np.maximum(self.s1.header['width'],self.s2.header['width'])
if self.s1.header['numFrames']!=self.s2.header['numFrames']:
print('Two videos files have different number of frames')
print('1st video has %d frames' % self.s1.header['numFrames'])
print('2nd video has %d frames' % self.s2.header['numFrames'])
print('first video %s is used as annotation refeence' % file1)
def getFrame(self):
I1,ts = self.s1.getFrame(0)
I2,_ = self.s2.getFrame(0)
w1 = I1.shape[1]
w2 = I2.shape[1]
if w1!=w2:
m=np.argmax(w1,w2)
if m==0:
wl = int(np.floor((w1-w2)/2.))
wr = w1-w2-wl
nd = len(I2.shape)
if nd==2:
padl = np.zeros((I2.shape[0],wl)).astype(np.uint8)
padr = np.zeros((I2.shape[0],wr)).astype(np.uint8)
else:
padl = np.zeros((I2.shape[0],wl,I2.shape[2])).astype(np.uint8)
padr = np.zeros((I2.shape[0],wr,I2.shape[2])).astype(np.uint8)
I2 = np.concatenate((padl,I2,padr),axis=1)
else:
wl = int(np.floor((w2 - w1) / 2.))
wr = w2 - w1 - wl
nd = len(I2.shape)
if nd == 2:
padl = np.zeros((I1.shape[0], wl)).astype(np.uint8)
padr = np.zeros((I1.shape[0], wr)).astype(np.uint8)
else:
padl = np.zeros((I1.shape[0], wl, I1.shape[2])).astype(np.uint8)
padr = np.zeros((I1.shape[0], wr, I1.shape[2])).astype(np.uint8)
I1 = np.concatenate((padl, I1, padr), axis=1)
I = np.hstack((I1,I2))
return I,ts
class seqIo_extractor():
"""
Create new seq files from top and fron view and syncronize them is not
path_vid: video path
vid_top: seq top video path and name
vid_front: seq front video path and name
s: start frame
e: end frame
"""
def __init__(self,path_vid,vid_top,vid_front,s,e):
sr_top = seqIo_reader(path_vid+vid_top)
sr_front = seqIo_reader(path_vid+vid_front)
num_frames=sr_top.header['numFrames']
num_framesf=sr_front.header['numFrames']
name =os.path.dirname(video_top).split('/')[-1]
if not os.path.exists(pathvid + name + '_%06d_%06d' % (s, e)):
os.makedirs(pathvid + name + '_%06d_%06d' % (s, e))
newdir = pathvid + name + '_%06d_%06d' % (s, e)
video_out_top = newdir + '/' + name + '_%06d_%06d_Top_J85.seq' % (s, e)
video_out_front = newdir + '/' + name + '_%06d_%06d_Front_J85.seq' % (s, e)
sw_top = seqIo_writer(video_out_top, sr_top.header)
sw_front = seqIo_writer(video_out_front, sr_front.header)
for f in range(s - 1, e):
if num_framesf > num_frames:
I_top, ts = sr_top.getFrame(f2(f))
I_front, ts2 = sr_front.getFrame(f)
else:
I_top, ts = sr_top.getFrame(f)
I_front, ts2 = sr_front.getFrame(f2(f))
sw_top.addFrame(I_top, ts)
sw_front.addFrame(I_front, ts2)
print(f)
sw_top.close()
sw_front.close()
def f2(f):
return int(round(f / (num_framesf - 1) * (num_frames - 1))) if num_framesf > num_frames else int(round(f / (num_frames - 1) * (num_framesf - 1)))
def seqIo_toVid(fName, ext='avi'):
"""
seqIo_toVid
Create seq file to another common used format as avi or mp4.
USAGE
seqIo( fName, ext )
INPUTS
fName - seq file name
ext - video extension to convert to
"""
assert fName[-3:]=='seq', 'Not a seq file'
sr = seqIo_reader(fName)
N = sr.header['numFrames']
h = sr.header['height']
w = sr.header['width']
fps = sr.header['fps']
out = fName[:-3]+ext
sw = skvideo.io.FFmpegWriter(out)
# sw = cv2.VideoWriter(out, -1, fps, (w, h))
timer = pb.ProgressBar(widgets=['Converting ', pb.Percentage(), ' -- ',
pb.FormatLabel('Frame %(value)d'), '/',
pb.FormatLabel('%(max)d'), ' [', pb.Timer(), '] ',
pb.Bar(), ' (', pb.ETA(), ') '], maxval=N)
for f in range(N):
I, ts = sr.getFrame(f)
#sw.writeFrame(Image.fromarray(I))
sw.write(I)
timer.update(f)
timer.finish()
# cv2.destroyAllWindows()
# sw.release()
sw.close()
sr.close()
print(out + ' converted')
# minimum header
# header = {'width': IM_TOP_W,
# 'height': IM_TOP_H,
# 'fps': fps,
# 'codec': 'imageFormat102'}
# filename= '/media/cristina/MARS_data/mice_project/teresa/Mouse156_20161017_17-22-09/Mouse156_20161017_17-22-09_Top_J85.seq'
# filename_out = filename[:-4] + '_new.seq'
# reader = seqIo_reader(filename)
# reader.header
# Initialize a SEQ writer
# writer = seqIo_writer(filename_out,reader.header)
# I,ts = reader.getFrame(0)
# writer.addFrame(I,ts)
# for f in range(8):
# I,ts = reader.getFrame(f)
# print(writer.file.tell())
# writer.addFrame(I,ts)
# writer.close()
# reader.close()
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