def processFrameOf(self, camera):
if not camera.isUp():
#self.log("WARN", "Video stream for Camera: " + camera._id + " not available")
return False
maxt = 10
frame = None
for i in range(1, maxt + 1):
#self.log("INFO", "Trying to accesss frame {}/{}".format(i, maxt))
try:
ret, f = camera.read()
if ret:
frame = f
except:
yyyyy = 1
if frame is None:
#self.log("WARN", "Couldn't access a valid frame")
return False
if camera._id in self.preprocessings:
self.log("INFO", "Pre-Processing frame of camera: " + camera._id)
st = time.time()
lineCoords = [(5, frame.shape[0] - 30 * (i + 1)) for i in range(3)]
pp = self.preprocessings[camera._id]
if 'brightness' in pp:
bv = pp['brightness']
frame = Preprocessing.adjustBrightness(frame, bv)
Preprocessing.putText(frame, "Brightness: " + str(bv),
lineCoords[0])
if 'sharpness' in pp:
sv = pp['sharpness']
frame = Preprocessing.sharpenImage(frame, k=sv)
Preprocessing.putText(frame, "Sharpness: " + str(sv),
lineCoords[1])
if 'denoise' in pp:
dv = pp['denoise']
if dv > 0:
frame = Preprocessing.denoiseImage(frame, strength=dv)
Preprocessing.putText(frame, "denoise: " + str(dv),
lineCoords[2])
et = time.time()
self.log("TIME", "Action took {:2.6f}s".format((et - st)))
#person detection
#plt.imshow(frame)
self.log("INFO", "Detecting People in the frame")
bboxes, conf = self.pd.detect(frame, drawOnFrame=False)
#overlapping bounding boxes
self.log("INFO", "Applying nms")
bboxes = non_max_suppression(np.array(bboxes),
probs=None,
overlapThresh=0.65)
#tracking
if len(bboxes) > 0:
tbboxes, tids = camera.tk.track(frame,
bboxes,
conf,
drawOnFrame=False)
if len(tbboxes) > 0:
self.log("INFO", "Tracking people {}".format(len(tids)))
for i in range(len(tbboxes)):
tbbox = np.array(tbboxes[i], np.int32)
tid = tids[i]
#increasing fps by selective recognition
if camera.track.hasPerson(tid):
if camera.track.people[tid].isSuspect():
if time.time() - camera.track.people[
tid].whenRecognized < self.recognizeThresh:
continue
person = frame[tbbox[1]:tbbox[3], tbbox[0]:tbbox[2]]
#cv2.imshow("person: ", person)
faces = fdr.extractFaces(person, drawOnFrame=False)
if len(faces) <= 0:
continue
face = faces[0]
fe = fdr.getEmbedding(face[0])
#check if he/she is a suspect
suspectDetected = False
for k, suspect in self.suspects.items():
#{"face":face, "em":em, "path":path}
for pic in suspect.pictures:
em = pic['em']
if fdr.is_match(em, fe):
camera.track.suspectDetected(
tid, suspect, time.time(), frame,
self.SERVER_ID, camera._id)
suspectDetected = True
break
if suspectDetected:
break
#update track
camera.track.updatePositions(tbboxes, tids)
camera.track.clearForgotten()
#display bboxes and everything
camera.track.draw(frame)
#udpate the processedFrame
#cv2.imshow("Frame", frame)
t = time.localtime()
text = "Server: " + time.strftime("%H:%M:%S", t)
cv2.putText(frame, text, (10, 60), cv2.FONT_HERSHEY_COMPLEX, 0.5,
(0, 255, 255), 1)
with self.lock:
camera.processedFrame = frame
camera.processedFrameTime = time.time()
self.xo = 1
return True
def processFrameOf(self, camera):
if not camera.isUp():
#self.log("WARN", "Video stream for Camera: " + camera._id + " not available")
camera.connect()
return False
maxt = 10
frame = None
for i in range(1, maxt + 1):
#self.log("INFO", "Trying to accesss frame {}/{}".format(i, maxt))
try:
ret, f = camera.read()
if ret:
frame = f
except:
yyyyy = 1
if frame is None:
#self.log("WARN", "Couldn't access a valid frame")
camera.reconnect()
return False
if camera._id in self.preprocessings:
self.log("INFO", "Pre-Processing frame of camera: " + camera._id)
st = time.time()
lineCoords = [(5, frame.shape[0] - 30 * (i + 1)) for i in range(3)]
pp = self.preprocessings[camera._id]
if 'brightness' in pp:
bv = pp['brightness']
frame = Preprocessing.adjustBrightness(frame, bv)
Preprocessing.putText(frame, "Brightness: " + str(bv),
lineCoords[0])
if 'sharpness' in pp:
sv = pp['sharpness']
frame = Preprocessing.sharpenImage(frame, k=sv)
Preprocessing.putText(frame, "Sharpness: " + str(sv),
lineCoords[1])
if 'denoise' in pp:
dv = pp['denoise']
if dv > 0:
frame = Preprocessing.denoiseImage(frame, strength=dv)
Preprocessing.putText(frame, "denoise: " + str(dv),
lineCoords[2])
et = time.time()
self.log("TIME", "Action took {:2.6f}s".format((et - st)))
#processing
cameraId = camera._id
t = 0
st = time.time()
bboxes, conf = self.pd.detect(frame, drawOnFrame=False)
et = time.time()
t += (et - st)
if len(bboxes) == 0:
return False
#print("detection time taken: {:2.4f}s".format(et-st))
st = time.time()
bboxes, ids, cents = camera.tk.track(frame,
bboxes,
conf,
returnCentroids=True,
drawOnFrame=False)
et = time.time()
t += (et - st)
if len(bboxes) == 0:
return False
#print("tracking time taken: {:2.4f}s".format(et-st) )
st = time.time()
facesWithIds = fdr.extractFacesAndAssignToPeople(frame,
bboxes,
ids,
cents,
drawOnFrame=False)
et = time.time()
t += (et - st)
#print("extracting faces time taken: {:2.4f}s".format(et-st) )
#drawing normal boxes around detected people
for i in range(len(bboxes)):
_bbox = bboxes[i]
_id = ids[i]
_cent = cents[i]
st = (int(_bbox[0]), int(_bbox[1]))
end = (int(_bbox[2]), int(_bbox[3]))
clr = (0, 255, 0)
cv2.rectangle(frame, st, end, clr, 2)
label = "ID:{}".format(_id)
self.textOnFrame(frame,
label,
fc=(0, 0, 0),
bc=(0, 255, 0),
org=(int(_cent[0]), int(_cent[1])))
for fd in facesWithIds:
_c = fd[1]
st = (_c[0], _c[1])
end = (_c[2], _c[3])
cv2.rectangle(frame, st, end, (255, 0, 0), 2)
self.inventory.update()
for suspect in self.inventory.suspects:
#recognition
if suspect.shouldRecognize():
recognized = -1
for embd in suspect.embds:
for index, facedata in enumerate(facesWithIds):
if fdr.is_match(facedata[3], embd):
recognized = index
break
if recognized >= 0:
faceWithId = facesWithIds.pop(recognized)
personId = cameraId + "_" + str(faceWithId[2])
try:
_trackIdIndex = ids.index(faceWithId[2])
if not _trackIdIndex > -1:
continue
except:
continue
_bbox = bboxes[_trackIdIndex]
self.markSuspectOnFrame(frame, suspect, _bbox)
suspect.recognized(personId, frame, self.SERVER_ID,
cameraId)
break
if recognized == -1:
if suspect.last_time_recognized != None:
if time.time() - suspect.last_time_recognized > 20:
suspect.personId = None
#displaying the person red on frame
if suspect.personId != None:
_trackId = int(suspect.personId.split("_")[1])
try:
_trackIdIndex = ids.index(_trackId)
if not _trackIdIndex > -1:
continue
except:
continue
_bbox = bboxes[_trackIdIndex]
self.markSuspectOnFrame(frame, suspect, _bbox)
print("processing one frame: {:2.4f}s".format(t))
t = time.localtime()
text = "Server: " + time.strftime("%H:%M:%S", t)
cv2.putText(frame, text, (10, 60), cv2.FONT_HERSHEY_COMPLEX, 0.5,
(0, 255, 255), 1)
with self.lock:
camera.processedFrame = frame
camera.processedFrameTime = time.time()
self.xo = 1
return True