def play_sound(self, snd_key):
'''
if snd_key == 'button1' : stream = self.stream[1] #self.stream[1] # usb-output
elif snd_key == 'button2': stream = self.stream[3] #self.stream[3] switched the position between button2 & 3
elif snd_key == 'button3': stream = self.stream[2] #self.stream[2] # usb-output
elif snd_key == 'foil':
stream_idx = randint(1, 3)
stream = self.stream[stream_idx] # randomly choose a stream if it's a foil sound
else: stream = self.stream[0] # built-in output stream
if self.flag_4th_speaker_test == True:
stream = self.stream[0]
self.flag_4th_speaker_test = False
'''
stream = self.stream[0]
if self.flag_SWS_test == True:
snd_key += '_SWS'
self.flag_SWS_test = False
elif flag_NVS_test == True:
snd_key += '_NVS'
self.flag_NVS_test = False
audio_output_data = self.wf[snd_key].readframes(self.chunk)
while audio_output_data != '':
stream.write(audio_output_data)
audio_output_data = self.wf[snd_key].readframes(self.chunk)
self.wf[snd_key].rewind()
if snd_key == 'foil':
writeFile(LOG, '%s, Played the <%s> sound through a stream #%i'%(get_time_stamp(), snd_key, stream_idx))
else:
writeFile(LOG, '%s, Played the <%s> sound'%(get_time_stamp(), snd_key))
def data_recording(self, fps):
if self.flag_recording_started == False: # This is the beginning of storing the video_data
curr_time_stamp = get_time_stamp()
if self.recording_timestamp != curr_time_stamp:
self.recording_timestamp = copy(curr_time_stamp)
self.recording_frame_cnt = 0
if FLAG_DEBUG: print "Video-recording starts @ %s"%self.recording_timestamp
self.start_new_tmp_img_dir()
self.start_new_MR()
writeFile(LOG, '%s, Start a video-recording from CAM#%i'%(self.recording_timestamp, self.cID))
self.record_past_buffer_imgs()
self.buffer_images = [] # clear the buffer images
self.save_tmp_image()
if fps != -1: self.rec_fps.append(fps)
self.flag_recording_started = True
else: # The recording already started
if self.recording_frame_cnt < self.maximum_frame_cnt:
self.save_tmp_image()
if fps != -1: self.rec_fps.append(fps)
#if fps != -1: self.rec_fps = (self.rec_fps + fps)/2
else:
if FLAG_DEBUG: print "Video-recording finishes @ %s due to exceeding the maximum frame-rate."%get_time_stamp()
writeFile(LOG, '%s, Finish the video-recording from %i\nThe average FPS during the recording was, %i'%(get_time_stamp(), self.cID, int(np.median(self.rec_fps))))
self.init_movie_params()
self.data_recording(fps)
def quiet_now(self, fps):
if self.flag_recording_started: # if it's not recording, there's no need to check the quiet state
curr_time = time()
if self.has_been_quiet_since == -1: self.has_been_quiet_since = time()
else:
if curr_time - self.has_been_quiet_since > self.maximum_q_duration:
# quiet moment is longer than maximum-quiet-duration
if FLAG_DEBUG: print "Video-recording finishes @ %s"%get_time_stamp()
writeFile(LOG, '%s, Finish the video-recording from CAM#%i\nThe average FPS during the recording was, %i'%(get_time_stamp(), self.cID, int(np.median(self.rec_fps))))
return "save_the_movie"
else:
self.data_recording(fps)
return None
def run(self, fps):
global PLACE_TO_CHECK_MOVEMENTS
if self.flag_take_first_bg_image == True: # First bg-image has to be taken at the beginning
self.take_bg_img()
self.flag_take_first_bg_image = False
self.color_image = cv.QueryFrame(self.cap_cam)
#########################################################################################
# Pre-processing
#########################################################################################
cv.Resize(self.color_image, self.color_image_resize)
cv.CvtColor(self.color_image_resize, self.grey_image, cv.CV_RGB2GRAY)
cv.Smooth(self.grey_image, self.grey_image, cv.CV_GAUSSIAN, 7, 0)
cv.Dilate(self.grey_image, self.grey_image, None, 2)
cv.Erode(self.grey_image, self.grey_image, None, 2)
#########################################################################################
# Checking movements
#########################################################################################
if self.first_run:
self.first_run = False
cv.ConvertScale(self.grey_image, self.grey_avg, 1.0, 0.0)
else:
cv.RunningAvg(self.grey_image, self.grey_avg, 0.3, None)
cv.ConvertScale(self.grey_avg, self.temp_grey, 1.0, 0.0) # Convert the scale of the moving average. (for Motion-detection)
cv.AbsDiff(self.grey_image, self.temp_grey, self.diff_grey) # Minus the current frame from the moving average. (for Motion-detection)
cv.Canny(self.diff_grey, self.diff_grey, 10, 15) # Find Edges for Motion-detection
m_min_pt1, m_max_pt2, m_center_pt_list = self.get_points(self.diff_grey) # get some useful points from the movement's contours
#########################################################################################
# Get rid of changing blobs from the recognized blobs to figure out which blob is 'STILL'
#########################################################################################
if time() - self.last_blob_chk_time > self.still_blob_chk_interval:
removal_idx = []
for i in range(len(self.recognized_blobs)):
recognized_time = self.recognized_blobs[i][1]
bound_rect = self.recognized_blobs[i][2]
cv.Zero(self.mask_img)
curr_img_in_blob_location = cv.CloneImage(self.mask_img)
diff_img = cv.CloneImage(self.mask_img)
cv.Rectangle(self.mask_img, (bound_rect[0],bound_rect[1]), (bound_rect[0]+bound_rect[2],bound_rect[1]+bound_rect[3]), 255, cv.CV_FILLED)
cv.Copy(self.grey_image, curr_img_in_blob_location, self.mask_img)
cv.AbsDiff(self.recognized_blobs[i][0], curr_img_in_blob_location, diff_img)
cv.Threshold(diff_img, diff_img, 30, 255, cv.CV_THRESH_BINARY)
mat_diff_img = cv.GetMat(diff_img)
moments = cv.Moments(mat_diff_img)
overall_changed_area = cv.GetCentralMoment(moments, 0, 0)
if overall_changed_area < 2000:
pass
'''
x = bound_rect[0]*2
y = bound_rect[1]*2
w = bound_rect[2]*2
h = bound_rect[3]*2
cv.Rectangle(self.color_image, (x,y), (x+w,y+h), (255,0,0), 2)
'''
else:
removal_idx.append(i)
if time() - recognized_time > self.max_still_blob_dur: # this blob is recognized over certain time
### get little bigger image around the blob, then update the background - image
cv.Rectangle(self.mask_img, (bound_rect[0]-20,bound_rect[1]-20), (bound_rect[0]+bound_rect[2]+20,bound_rect[1]+bound_rect[3]+20), 255, cv.CV_FILLED)
cv.Zero(curr_img_in_blob_location)
new_bg_img = cv.CloneImage(curr_img_in_blob_location)
cv.Copy(self.grey_image, curr_img_in_blob_location, self.mask_img) # get the changed image part
cv.Not(self.mask_img, self.mask_img) # invert the mask image
cv.Copy(self.grey_bg_img, new_bg_img, self.mask_img) # get the unchanged bg-image
cv.Add(curr_img_in_blob_location, new_bg_img, self.grey_bg_img) # combine the above two into the bg-img
timestamp = get_time_stamp()
writeFile(LOG, '%s, Background was updated on Cam #%i'%(timestamp, self.cID))
'''
### Save the changed bg-img
capture_file_name = "_changed_bg_img_cID%.2i_%s.jpg"%(self.cID, timestamp)
capture_file_path = os.path.join(self.cwd, self.output_folder, capture_file_name)
cv.SaveImage(capture_file_path, self.grey_bg_img)
'''
if i not in removal_idx:
removal_idx.append(i) # this blob info will be removed
for i in range(len(removal_idx)): self.recognized_blobs.pop(removal_idx[i]-i)
self.last_blob_chk_time = time()
#########################################################################################
# Foreground blob checking
#########################################################################################
foreground, fg_mask_img, fg_size = self.bg_subtraction(self.grey_image) # background subtraction
f_min_pt1, f_max_pt2, f_center_pt_list = self.get_points(foreground) # get some useful points from the foregournd contours
### checking foreground blobs and register it
number_of_fBlobs = 0
grouped_points_for_fBlobs = []
if len(f_center_pt_list) > 0:
number_of_fBlobs, grouped_points_for_fBlobs = self.clustering(f_center_pt_list) # clustrering foreground-blobs
if number_of_fBlobs < 2:
if f_min_pt1 != [] and f_max_pt2 != []:
number_of_fBlobs = 1
x = f_min_pt1[0] + (f_max_pt2[0]-f_min_pt1[0])/2
y = f_min_pt1[1] + (f_max_pt2[1]-f_min_pt1[1])/2
grouped_points_for_fBlobs = [[[x, y]]]
if len(self.recognized_blobs) < self.max_blob_number:
bound_rect = (f_min_pt1[0], f_min_pt1[1], f_max_pt2[0]-f_min_pt1[0], f_max_pt2[1]-f_min_pt1[1])
self.chk_and_register_fBlob(bound_rect)
else:
for grouped_points in grouped_points_for_fBlobs:
if len(self.recognized_blobs) < self.max_blob_number:
bound_rect = cv.BoundingRect(grouped_points)
self.chk_and_register_fBlob(bound_rect)
#########################################################################################
# Movement Recording
#########################################################################################
if len(m_center_pt_list) > 0: # there was a rect indicating the movements
whole_bounding_rect = (m_min_pt1[0], m_min_pt1[1], m_max_pt2[0]-m_min_pt1[0], m_max_pt2[1]-m_min_pt1[1])
if self.min_th_for_movement < whole_bounding_rect[2] + whole_bounding_rect[3] < self.max_th_for_movement:
# bounding rect for all the movement points is within the thresholds
self.has_been_quiet_since = -1 # it's not quiet
self.data_recording(fps) # data-recording
### Record movement detail with certain interval
if time() > self.last_time_behavior_recorded + self.MR_interval:
### Find out where the white blob is
whitish_area = -1
white_x = -1
white_y = -1
'''
### Temporarily disabled. Not very useful at the moment.
if len(f_center_pt_list) > 0:
### make the color image with the area left(= detected blob) after background subtraction
cv.Zero(self.color_image_for_masking)
cv.Copy(self.color_image_resize, self.color_image_for_masking, fg_mask_img)
### save the masked color image for analysis purpose (Temporary)
#capture_file_path = os.path.join(self.cwd, self.output_folder, '_tmp', '%s.jpg'%get_time_stamp())
#cv.SaveImage(capture_file_path, self.color_image_for_masking)
### extract whitish color
cv.CvtColor(self.color_image_for_masking, self.color_image_for_masking, cv.CV_BGR2HSV)
cv.InRangeS(self.color_image_for_masking, self.HSV_min, self.HSV_max, self.grey_image)
### calculate its(whitish blob) size and position
mat_result_whitish_blob = cv.GetMat(self.grey_image)
moments = cv.Moments(mat_result_whitish_blob)
whitish_area = cv.GetCentralMoment(moments,0,0)
white_x = -1
white_y = -1
if whitish_area > 1000:
white_x = int(cv.GetSpatialMoment(moments, 1, 0)/whitish_area)
white_y = int(cv.GetSpatialMoment(moments, 0, 1)/whitish_area)
'''
### make the movement-record
movement_rect = (m_min_pt1[0], m_min_pt1[1], m_max_pt2[0]-m_min_pt1[0], m_max_pt2[1]-m_min_pt1[1])
if len(f_min_pt1) != 0:
foreground_rect = (f_min_pt1[0], f_min_pt1[1], f_max_pt2[0]-f_min_pt1[0], f_max_pt2[1]-f_min_pt1[1])
fg_x = foreground_rect[0]+foreground_rect[2]/2
fg_y = foreground_rect[1]+foreground_rect[3]/2
else:
foreground_rect = '(-1/ -1/ -1/ -1)'
fg_x = fg_y = -1
writeFile(self.behavior_rec_path, "%s, %i/%i, %s, %i/%i, %i, %i, %i, %i/%i, %s, %s\n"%(
str(movement_rect).replace(",","/"),
movement_rect[0]+movement_rect[2]/2, movement_rect[1]+movement_rect[3]/2,
str(foreground_rect).replace(",","/"),
fg_x, fg_y, number_of_fBlobs, int(fg_size),
int(whitish_area), white_x, white_y,
str(grouped_points_for_fBlobs).replace(",", "/"), get_time_stamp()))
self.last_time_behavior_recorded = time()
### Checking on order from main_module
if len(PLACE_TO_CHECK_MOVEMENTS) > 0:
if PLACE_TO_CHECK_MOVEMENTS == 'feeder':
if self.x_range_for_feeder_movements[0] < fg_x < self.x_range_for_feeder_movements[1]:
if self.y_range_for_feeder_movements[0] < fg_y < self.y_range_for_feeder_movements[1]:
self.vi_conn.send("motion_at_feeder")
PLACE_TO_CHECK_MOVEMENTS = ""
else:
self.flag_save_movie = self.quiet_now(fps)
else:
self.flag_save_movie = self.quiet_now(fps)
if self.flag_recording_started == False: self.save_buffer_img() # if it's not recording, save the buffer image
def send(self, msg=''):
self.aConn.write(msg) # send a message to Arduino
sleep(0.2)
self.aConn.flushOutput() # flush the serial connection
self.log_file_path = update_log_file_path(self.output_folder, self.log_file_path)
if os.path.isfile(self.log_file_path): writeFile(self.log_file_path, "%s, Message - '%s' was sent to Arduino"%(get_time_stamp(), msg))
