def createNewFDVT(self):
fn = QtGui.QFileDialog.getOpenFileName(self, "Select FDVT", '.',
'*.csv')
anno = A.Annotation()
anno.loadFromFile(fn[0])
# filterTuples = anno.extractAllFilterTuples()
annotationSelector = SD.AnnotationSelector()
annotationSelector.setAnnotationFile(fn[0])
OD.OverlayDialogWidgetBase.getUserInput(self, annotationSelector)
# annotationFilters = AS.AnnotationSelecter.getAnnotationSelection(self,
# anno)
annotationSelection = annotationSelector.getUserSelection()
annotationFilters = []
colors = []
for a, b, c in annotationSelection:
annotationFilters += [A.AnnotationFilter(None, [a], [b])]
colors += [c]
filteredAnno = anno.filterFrameListMultiple(annotationFilters,
exactMatch=False)
import tempfile
tmpDir = tempfile.mkdtemp()
fdvt = FDV.FrameDataVisualizationTreeBehaviour(tmpDir)
fdvt.importAnnotation(filteredAnno, annoFilters=annotationFilters)
self.addFDVT(fdvt, colors)
print annotationFilters
def setAnnotationFile(self, filename):
try:
self.anno = A.Annotation()
self.anno.loadFromFile(filename)
self.scanLabelFile()
except IOError:
self.anno = None
def loadAnnotation(self, lst):
from os.path import isfile
videoLength = lst[0]
self.loading = True
f = self.bhvrPath
if isfile(f):
cfg.log.debug("AnnotationLoader: f exists create empty Annotation")
out = Annotation.Annotation()
cfg.log.debug(
"AnnotationLoader: created Annotation. try to load..")
try:
out.loadFromFile(f)
cfg.log.info(
"AnnotationLoader: loaded Annotation {0} {1}".format(
self.bhvrPath, self))
except:
cfg.log.warning("load annotation of " + f +
" failed, reset annotaions")
if videoLength is None:
videoLength = self.retrieveVideoLength(self.bhvrPath)
out = Annotation.Annotation(
frameNo=videoLength) #, vialNames=self.vialNames)
else:
cfg.log.warning(
"AnnotationLoader: f does NOT exist create empty Annotation at {0}"
.format(self.bhvrPath))
if videoLength is None:
videoLength = self.retrieveVideoLength(self.videoPath)
out = Annotation.Annotation(
frameNo=videoLength) #, vialNames=self.vialNames)
cfg.log.info("new annotation with length {0}".format(videoLength))
if out is None:
cfg.log.warning("annotation is None. Should never, ever happen!")
self.annotation = out
# self.loadedAnnotation.emit([self, self.path])
cfg.log.debug("finished loading annotation {0}".format(self.bhvrPath))
self.loadedAnnotation.emit([self.key, self.annotation.getLength()])
self.loading = False
def extractFeatures(self):
"""
Iteration over video file to extract features
:return:
"""
if len(self.videoListRel) == 1:
progressSteps = VE.videoExplorer.retrieveVideoLength(
self.rel2absFile(self.videoListRel[0]))
else:
progressSteps = len(self.videoListRel)
self.setStatus("extracting features..", progressSteps)
for i, relVidFile in enumerate(self.videoListRel):
if os.path.exists(self.generateColorFeatureSavePath(relVidFile))\
and os.path.exists(self.generateDiffImgFeatureSavePath(relVidFile)):
# do not recompute features already computed
if len(self.videoListRel) > 1:
self.incrementStatus()
continue
colorFeat = []
diffImgFeat = []
vE = VE.videoExplorer()
vE.setVideoStream(self.rel2absFile(relVidFile), frameMode='RGB')
anno = A.Annotation()
anno.loadFromFile(
self.rel2absFile(self.convertVideoToAnnoFilename(relVidFile)))
annotationList = anno.filterFrameLists(self.annotationFilters)
prevFrame = None
for frame in vE:
colorFeat += [
self.extractColorFeatureFromFrame(frame, annotationList[i])
]
if prevFrame:
diffImgFeat += [
self.extractDiffImgFeatureFromFrames(
prevFrame, frame, annotationList[i])
]
else:
diffImgFeat += [np.zeros((16, ), dtype=np.int32)]
if len(self.videoListRel) == 1:
self.incrementStatus()
np.save(self.generateColorFeatureSavePath(relVidFile),
np.asarray(colorFeat))
np.save(self.generateDiffImgFeatureSavePath(relVidFile),
np.asarray(diffImgFeat))
if len(self.videoListRel) > 1:
self.incrementStatus()
def __init__(self):
super(Test, self).__init__()
self.annoSelector = AnnotationSelecter(self)
self.setCentralWidget(self.annoSelector)
self.show()
import pyTools.videoProc.annotation as A
a = A.Annotation()
a.loadFromFile('/media/peter/Seagate Backup Plus Drive1/peter_testCopy/WP609L_small.bhvr')
self.annoSelector.setAnnotation(a)
def createAnnotationArrays(self, annoFileList):
maxClass = len(self.annotationFilters)
annotationArrays = dict()
for annoFile in sorted(annoFileList):
if os.path.exists(self.rel2absFile(annoFile)):
anno = A.Annotation()
anno.loadFromFile(self.rel2absFile(annoFile))
for i, annoFilter in enumerate(self.annotationFilters):
filtAnno = anno.filterFrameListBool(annoFilter)
if i == 0:
annotationArrays[annoFile] = np.zeros(
(filtAnno.shape[0], maxClass), dtype=np.bool)
annotationArrays[annoFile][:, i] = filtAnno
return annotationArrays
def classify(self):
"""
Applies the classifier on all data
:return:
"""
print("classifying!")
if len(self.videoListRel) == 1:
progressSteps = VE.videoExplorer.retrieveVideoLength(
self.rel2absFile(self.videoListRel[0]), 100000)
# self.fdvt = FDV.FrameDataVisualizationTreeBehaviour()
# self.fdvt.meta['singleFileMode'] = True
else:
progressSteps = len(self.videoListRel)
# self.fdvt = FDV.FrameDataVisualizationTreeBehaviour()
# self.fdvt.meta['singleFileMode'] = False
self.setStatus("classifying...", progressSteps)
filters = []
# filt = A.AnnotationFilter(annotators=["simpleFlyShowCase"],
# behaviours=['negative'],
# vials=self.annotationFilters[0].vials)
# self.fdvt.addNewClass(filt)
# filters += [filt]
clfy_res = []
for af in self.annotationFilters:
filt = A.AnnotationFilter(annotators=["SimpleHistogramPlugin"],
behaviours=af.behaviours,
vials=af.vials)
# self.fdvt.addNewClass(filt)
filters += [filt]
clfy_res += [{'frames': [], 'meta': {}}]
for i, videoPathRel in enumerate(self.videoListRel):
feat = np.load(self.generateFeatureSavePath(videoPathRel))
dv = [] # deltaVector
for k in range(0, feat.shape[0], 100):
f = feat[k:k + 100]
prediction = self.classifier.predict(f)
for j, p in enumerate(prediction):
# p-1 because tehre is no negative class!!!
# dv += [self.fdvt.getDeltaValue(videoPathRel, k + j,
# filters[int(p-1)])]
# UPDATE ANNOTATIONS
clfy_res[p]['frames'] += [k + j]
clfy_res[p]['meta'][k + j] = {
"confidence": 1,
"boundingBox": [None, None, None, None]
}
if len(self.videoListRel) == 1:
self.incrementStatus(100)
# SAVE RESULT IN ANNOTATIONS
resAnno = A.Annotation(frameNo=feat.shape[0])
for i, af in enumerate(self.annotationFilters):
annotator = af.annotators[0]
label = af.behaviours[0]
if clfy_res[i]['frames']:
resAnno.addAnnotation(vial=None,
frames=clfy_res[i]['frames'],
annotator='SimpleHistogramPlugin',
behaviour=label,
metadata=clfy_res[i]['meta'])
# self.fdvt.insertDeltaVector(dv)
resAnno.saveToFile(
self.generateFeatureSavePath(videoPathRel) + 'hist.csv')
if len(self.videoListRel) > 1:
self.incrementStatus()