event = sys.argv[1]
event.replace(".
file = "/var/www/html/out/" + sys.argv[1]
tstamp_prev = None
image_acc = None
m_image_acc = None
cap = cv2.VideoCapture(file)
cv2.namedWindow('pepe')
open("jpgs/" + event + ".txt")
while True:
_ , frame = cap.read()
if (_ is True):
print ("Count: ", count)
alpha, tstamp_prev = iproc.getAlpha(tstamp_prev)
if image_acc is None:
image_acc = np.empty(np.shape(frame))
image_diff = cv2.absdiff(image_acc.astype(frame.dtype), frame,)
hello = cv2.accumulateWeighted(frame, image_acc, alpha)
mframe = frame
mframe = cv2.cvtColor(mframe, cv2.COLOR_BGR2GRAY)
mframe = cv2.GaussianBlur(mframe, (21, 21), 0)
if m_image_acc is None:
m_image_acc = np.empty(np.shape(mframe))
m_image_diff = cv2.absdiff(m_image_acc.astype(mframe.dtype), mframe,)
hello = cv2.accumulateWeighted(mframe, m_image_acc, alpha)
sframe = cv2.convertScaleAbs(image_acc)
cv2.imshow('pepe', sframe)
def view(file, show = 0):
# before processing dump frames from this file for 24 hour time lapse
os.system("./dump-frames-tl.py " + file )
config_file = ""
try:
(file_date, cam_num) = file.split("-")
cam_num = cam_num.replace(".avi", "")
except:
cam_num = ""
if cam_num == "":
config = read_config(config_file)
else:
#cam_num = sys.argv[1]
config_file = "conf/config-" + cam_num + ".txt"
config = read_config(config_file)
#config = read_config(config_file)
frame_time_data = []
values = {}
dir_name = os.path.dirname(file)
file_name = file.replace(dir_name + "/", "")
summary_file_name = file_name.replace(".avi", "-summary.txt")
data_file_name = file_name.replace(".avi", ".txt")
screen_cap_file_name = file_name.replace(".avi", ".jpg")
object_file_name = file_name.replace(".avi", "-objects.jpg")
time_file_name = file_name.replace(".avi", "-time.txt")
capture_date = parse_file_date(file_name)
#last_cal_date = # Get last / closest calibration date
file_base_name = file_name.replace(".avi", "")
status = day_or_night(config, capture_date)
# read in time file if it exists
if os.path.isfile(dir_name + "/" + time_file_name):
frame_time_data = read_time_file(dir_name + "/" + time_file_name)
print ("FRAME TIME DATA LENGTH:", len(frame_time_data))
time.sleep(1)
else:
print ("no frame time data! " + dir_name + "/" + time_file_name )
for x in range(0, 225):
frame_time_data.append("|||")
fps_t = 0
for ftd in frame_time_data:
print ("FRAMEdata", ftd)
fps, tc, tt, tx = ftd.split("|")
if fps == "":
fps = 0
fps_t = int(float(fps_t)) + int(float(fps))
if len(frame_time_data) > 0:
avg_fps = fps_t / len(frame_time_data)
else :
avg_fps = 0
print ("Viewing file: " + file)
print ("Directory: " + dir_name)
print ("File Name: " + file_name)
print ("Summary File Name: " + summary_file_name)
print ("Data File Name: " + data_file_name)
print ("Screen Cap File Name: " + screen_cap_file_name)
print ("Object File Name: " + object_file_name)
print ("Capture Date: " + capture_date)
print ("FPS: " + str(avg_fps))
# make sure the file exists
if os.path.isfile(file) is False:
print("This file does not exist. Exiting.")
return(0)
else:
print ("The file is ok.")
#process video
tstamp_prev = None
image_acc = None
last_frame = None
nice_image_acc = None
final_image = None
cur_image = None
frame_count = 0
# open data log file
fp = open(dir_name + "/" + data_file_name, "w")
fp2 = open(dir_name + "/" + summary_file_name, "w")
fp.write("frame|contours|x|y|w|h|color|fps|adjusted_unixtime|unixtime|time_offset\n")
fp2.write("frame|contours|x|y|w|h|color|fps|adjusted_unixtime|unixtime|time_offset\n")
#if show == 1:
# cv2.namedWindow('pepe')
cap = cv2.VideoCapture(file)
time.sleep(2)
xs = []
ys = []
motion_frames = []
frames = []
colors = []
noise = 0
while True:
_ , frame = cap.read()
frame_count = frame_count + 1
frames.extend([frame])
if frame is None:
if frame_count <= 1:
print("Bad file.")
return(0)
else:
print("Processed ", frame_count, "frames.")
# finish processing file and write output files
total_motion = len(motion_frames)
if total_motion < 3 :
#this a BS capture. abort
os.system("mv " + dir_name + "/" + file_base_name + "* " + "/var/www/html/out/dist/")
return(0)
half_motion = int(round(total_motion/2,0))
print ("key frame #1 : ", 1)
print ("key frame #2 : ", half_motion)
print ("key frame #3 : ", total_motion -1)
print ("Xs", xs)
print ("Ys", ys)
print ("MF", motion_frames)
avg_color = sum(colors) / float(len(colors))
print ("CL", colors)
print ("Avg Color: ", avg_color)
#print (motion_frames[1])
#print (motion_frames[half_motion])
#print (motion_frames[total_motion -1])
#print(frames[motion_frames[1]])
#print(frames[motion_frames[half_motion]])
#print(frames[motion_frames[total_motion - 1]])
object_file_image = (frames[motion_frames[1]] * .33) + (frames[motion_frames[half_motion]] * .33) + (frames[motion_frames[total_motion-2]] * .33)
x1 = xs[1]
y1 = xs[1]
x2 = xs[half_motion]
y2 = xs[half_motion]
x3 = xs[total_motion-2]
y3 = xs[total_motion-2]
xmax = max(xs)
ymax = max(ys)
xmin = min(xs)
ymin = min(ys)
skip = 0
if xmax - xmin == 0 and ymax - ymin == 0:
skip = 1
straight_line = compute_straight_line(x1,y1,x2,y2,x3,y3)
if (straight_line < 1 and straight_line > 0) or avg_color > 190:
meteor_yn = "Y"
else:
meteor_yn = "N"
if status == 'night':
meteor_yn = "Y"
else:
meteor_yn = "N"
#meteor_yn = "Y"
if skip == 1:
meteor_yn = "N"
print ("Skipping not enough x,y movement!", xmax, xmin, ymax, ymin)
if noise >= 5:
meteor_yn = "N"
print ("Skipping to much noise!", noise)
if avg_fps < 20:
meteor_yn = "N"
print ("Skipping calibration file!", avg_fps)
print ("Status:", status)
print ("Straight Line:", straight_line)
print ("Likely Meteor:", meteor_yn)
obj_outfile = dir_name + "/" + object_file_name
sc_outfile = dir_name + "/" + screen_cap_file_name
cv2.imwrite(obj_outfile, object_file_image)
cv2.imwrite(sc_outfile, object_file_image)
#write summary & data files
fp.close()
fp2.close()
# prep event or capture for upload to AMS
values['datetime'] = capture_date
values['motion_frames'] = total_motion
values['cons_motion'] = total_motion
values['color'] = avg_color
values['straight_line'] = straight_line
values['meteor_yn'] = meteor_yn
values['bp_frames'] = total_motion
if meteor_yn == 'Y':
try:
values['best_caldate'] = config['best_caldate']
except:
config['best_caldate'] = '0000-00-00 00:00:00';
values['best_caldate'] = config['best_caldate']
try:
log_fireball_event(config, file, dir_name + "/" + summary_file_name, dir_name + "/" + object_file_name, values)
except:
print ("failed to upload event file.")
return(0)
#move files to maybe dir
print ("Move to maybe dir!")
os.system("mv " + dir_name + "/" + file_base_name + "* " + "/var/www/html/out/maybe/")
else:
log_motion_capture(config, dir_name + "/" + object_file_name, values)
try:
log_motion_capture(config, dir_name + "/" + object_file_name, values)
except:
print ("failed to upload capture file.")
return(0)
print ("Move to false dir!")
if (skip == 1 or noise >= 5) and status == 'night':
os.system("mv " + dir_name + "/" + file_base_name + "* " + "/var/www/html/out/dist/")
elif avg_fps < 20:
os.system("mv " + dir_name + "/" + file_base_name + "* " + "/var/www/html/out/calvid/")
else:
os.system("mv " + dir_name + "/" + file_base_name + "* " + "/var/www/html/out/false/")
return(1)
nice_frame = frame
alpha, tstamp_prev = iproc.getAlpha(tstamp_prev)
frame = cv2.resize(frame, (0,0), fx=0.5, fy=0.5)
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray_frame = frame
frame = cv2.GaussianBlur(frame, (21, 21), 0)
if last_frame is None:
last_frame = nice_frame
if image_acc is None:
image_acc = np.empty(np.shape(frame))
image_diff = cv2.absdiff(image_acc.astype(frame.dtype), frame,)
hello = cv2.accumulateWeighted(frame, image_acc, alpha)
_, threshold = cv2.threshold(image_diff, 30, 255, cv2.THRESH_BINARY)
thresh= cv2.dilate(threshold, None , iterations=2)
(_, cnts, xx) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
data = str(frame_count) + "|"
color = 0
contours = len(cnts)
x,y,w,h = 0,0,0,0
if contours > 3:
noise = noise + 1
if contours > 0:
x,y,w,h = cv2.boundingRect(cnts[0])
mx = x + w
my = y + h
cx = int(x + (w/2))
cy = int(y + (h/2))
color = gray_frame[cy,cx]
xs.extend([x])
ys.extend([y])
colors.extend([color])
motion_frames.extend([frame_count])
line_data = str(frame_count) + "|" + str(contours) + "|" + str(x) + "|" + str(y) + "|" + str(w) + "|" + str(h) + "|" + str(color) + "|" + frame_time_data[frame_count-1] + "\n"
fp.write(line_data)
fp2.write(line_data)
print (frame_count, contours, x,y,w,h,color)
def show_loop(pipe_child):
config = read_config()
print(config['cam_ip'])
device_lat = config['device_lat']
device_lng = config['device_lng']
device_operator = config['last_name'] + config['first_name']
device_id = config['device_id']
image_acc = None
nice_image_acc = None
tstamp_prev = None
count = 0
#time_start = datetime.datetime.now()
time_start = time.time()
frame = pipe_child.recv()
frames = deque(maxlen=200)
frame_times = deque(maxlen=200)
frame_data = deque(maxlen=200)
motion_on = 0
motion_off = 0
cnts = []
lc = 1
calibrate_now = 0
calibrate_start = 0
#sense_up = 0
while True:
frame = pipe_child.recv()
frame_time = time.time()
frames.appendleft(frame)
frame_times.appendleft(frame_time)
#frame_info = str(motion_on) + "|" + str(motion_off) + "|" + str(len(cnts)) + "|"
#frame_data.appendleft(frame_info)
#if (count == 0):
#calibrate on start (only if dark)
#sys command to sense up
# calibrate_start = 1
#if calibrate_start >= 0:
# calibrate_start = calibrate_start + 1
if (lc % 11 == 0 and count == 5):
dec_sec = datetime.datetime.fromtimestamp(
int(frame_time)).strftime("%f")
dec_sec_f = dec_sec[:2]
cframe = frame
format_time = datetime.datetime.fromtimestamp(
int(frame_time)).strftime("%Y-%m-%d %H:%M:%S.")
cv2.putText(
cframe, "AMSMeteors.org / " + device_operator + " " +
format_time + dec_sec_f + " UTC " + device_id + " " +
device_lat + " " + device_lng, (10, frame.shape[0] - 10),
cv2.FONT_HERSHEY_SIMPLEX, .4, (255, 255, 255), 1)
cv2.imwrite("/var/www/html/out/latest.jpg", cframe)
if count % 100 == 0:
time_diff = frame_time - time_start
#time_diff_seconds = time_diff.total_seconds()
fps = count / time_diff
print("FPS: " + str(fps))
#ff.write("FPS: " + str(fps) + "\n")
count = 1
lc = lc + 1
print("LC:" + str(lc))
time_start = frame_time
if count % 3 == 0:
#if sense_up > 1:
# print ("Sense Up: ", sense_up)
#if sense_up >= 100 and sense_up < 103:
# print ("Take calibration...")
# dec_sec = datetime.datetime.fromtimestamp(int(frame_time)).strftime("%f")
# dec_sec_f = dec_sec[:2]
# cframe = frame
# format_time = datetime.datetime.fromtimestamp(int(frame_time)).strftime("%Y-%m-%d %H:%M:%S.")
# cv2.putText(cframe, "AMSMeteors.org / " + device_operator + " " + format_time + dec_sec_f + " UTC " + device_id + " " + device_lat + " " + device_lng,
# (10, frame.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, .4, (255, 255, 255), 1)
# format_time = datetime.datetime.fromtimestamp(int(frame_time)).strftime("%Y%m%d%H%M%S")
# cal_file = "/var/www/html/out/cal" + format_time + ".jpg"
# cv2.imwrite(cal_file, cframe)
# motion_on = 0
# motion_off = 0
#if sense_up == 106:
#os.system("/var/www/html/write-serial.py sense_down")
# print ("Sense down.")
# r = requests.get("http://" + config['cam_ip'] + "/webs/btnSettingEx?flag=1000¶mchannel=0¶mcmd=1058¶mctrl=50¶mstep=0¶mreserved=0&")
#if sense_up > 200:
# calibrate_now = 0
# motion_on = 0
# motion_on = 0
# sense_up = 0
alpha, tstamp_prev = iproc.getAlpha(tstamp_prev)
frame = cv2.resize(frame, (0, 0), fx=0.8, fy=0.8)
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
frame = cv2.GaussianBlur(frame, (21, 21), 0)
if image_acc is None:
image_acc = np.empty(np.shape(frame))
image_diff = cv2.absdiff(
image_acc.astype(frame.dtype),
frame,
)
hello = cv2.accumulateWeighted(frame, image_acc, alpha)
_, threshold = cv2.threshold(image_diff, 30, 255,
cv2.THRESH_BINARY)
thresh = cv2.dilate(threshold, None, iterations=2)
(_, cnts, xx) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
if len(cnts) == 0:
motion_off = motion_off + 1
elif len(cnts) > 2 and lc > 3:
print("dropped frame", len(cnts))
motion_off = motion_off + 1
dropped = frames.pop()
#frames.appendleft(last_frame)
elif lc > 2:
motion_on = motion_on + 1
motion_off = 0
if motion_off > 5 and motion_on < 3:
motion_on = 0
#if calibrate_now == 1:
# sense_up = sense_up + 1
#if motion_off == 3 and motion_on >= 3:
#r = requests.get("http://" + config['cam_ip'] + "/webs/btnSettingEx?flag=1000¶mchannel=0¶mcmd=1058¶mctrl=25¶mstep=0¶mreserved=0&")
if motion_off > 20 and motion_on >= 3 and calibrate_now == 0:
#ff.write("RECORD BUFFER NOW!\n")
motion_off = 0
motion_on = 0
i = 1000
format_time = datetime.datetime.fromtimestamp(
int(frame_time)).strftime("%Y%m%d%H%M%S")
outfile = "{}/{}.avi".format("/var/www/html/out", format_time)
outfile_text = "{}/{}.txt".format("/var/www/html/out",
format_time)
if record == 1:
df = open(outfile_text, 'w', 1)
dql = len(frame_times) - 1
time_diff = frame_times[1] - frame_times[dql]
fps = 200 / time_diff
print("FPS: ", fps)
writer = cv2.VideoWriter(
outfile, cv2.VideoWriter_fourcc(*'MJPG'), fps,
(frames[0].shape[1], frames[0].shape[0]), True)
while frames:
img = frames.pop()
ft = frame_times.pop()
format_time = datetime.datetime.fromtimestamp(
int(ft)).strftime("%Y-%m-%d %H:%M:%S.")
dec_sec = datetime.datetime.fromtimestamp(
int(frame_time)).strftime("%f")
format_time = format_time + dec_sec
#img_data = frame_data.pop()
#fts = ft.strftime("%Y%m%d %H:%M:%S.%f|")
df.write(format_time + "\n")
#cv2.putText(img, img_time.strftime("AMSMeteors.org / " + device_operator + " %Y%m%d %H:%M:%S." + dec_sec_f + " UTC " + device_id + ": " + device_lat + " " + device_lng),
#(10, img.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, .5, (255, 255, 255), 1)
#cv2.imwrite("out/" + str(i) + ".jpg", img)
writer.write(img)
i = i + 1
writer.release()
df.close()
#r = requests.get("http://" + config['cam_ip'] + "/webs/btnSettingEx?flag=1000¶mchannel=0¶mcmd=1058¶mctrl=50¶mstep=0¶mreserved=0&")
#calibrate_now = 1
#sense_up = sense_up + 1
if motion_on > 0:
#ff.write("motion_on " + str(motion_on) + "\n")
print("motion_on " + str(motion_on) + "\n")
#cv2.imshow('pepe', frame)
#last_frame = frame
count = count + 1
def cam_loop(pipe_parent):
#cv2.namedWindow("pepe")
lc = 0
tstamp_prev = None
motion_on = 0
motion_off = 0
config = read_config()
print(config['cam_ip'])
cap = cv2.VideoCapture("rtsp://" + config['cam_ip'] +
"/av0_1&user=admin&password=admin")
cv2.setUseOptimized(True)
image_acc = None
time.sleep(5)
frames = deque(maxlen=200)
frame_times = deque(maxlen=200)
time_start = datetime.datetime.now()
count = 0
while True:
_, frame = cap.read()
if _ is True:
frame_time = datetime.datetime.now()
frames.appendleft(frame)
frame_times.appendleft(frame_time)
#pipe_parent.send(frame)
if count % 300 == 0:
time_diff = frame_time - time_start
fps = count / time_diff.total_seconds()
print("FPS: " + str(fps))
count = 1
lc = lc + 1
print("LC:" + str(lc))
time_start = frame_time
if count % 3 == 0:
#alpha = .25
alpha, tstamp_prev = iproc.getAlpha(tstamp_prev)
frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
frame = cv2.GaussianBlur(frame, (21, 21), 0)
if image_acc is None:
image_acc = np.empty(np.shape(frame))
image_diff = cv2.absdiff(
image_acc.astype(frame.dtype),
frame,
)
hello = cv2.accumulateWeighted(frame, image_acc, alpha)
_, threshold = cv2.threshold(image_diff, 30, 255,
cv2.THRESH_BINARY)
thresh = cv2.dilate(threshold, None, iterations=2)
(_, cnts, xx) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
#cv2.imshow("pepe", frame)
#cv2.imshow("pepe", image_diff)
#cv2.waitKey(5)
if len(cnts) == 0:
motion_off = motion_off + 1
print(len(cnts), motion_on, motion_off)
elif len(cnts) < 30:
print(len(cnts), motion_on, motion_off)
motion_on = motion_on + 1
motion_off = 0
#cv2.imshow("pepe", cv2.convertScaleAbs(image_diff))
else:
print("CNTS:", len(cnts))
if motion_off > 5 and motion_on < 5:
motion_on = 0
if lc < 3:
motion_on = 0
if motion_off > 10 and motion_on >= 5:
r = requests.get(
"http://" + config['cam_ip'] +
"/webs/btnSettingEx?flag=1000¶mchannel=0¶mcmd=1058¶mctrl=25¶mstep=0¶mreserved=0&"
)
if motion_off > 30 and motion_on >= 5:
r = requests.get(
"http://" + config['cam_ip'] +
"/webs/btnSettingEx?flag=1000¶mchannel=0¶mcmd=1058¶mctrl=50¶mstep=0¶mreserved=0&"
)
print("RECORD BUFFER NOW!\n")
motion_on = 0
format_time = frame_time.strftime("%Y%m%d%H%M%S")
outfile = "{}/{}.avi".format("/var/www/html/out", format_time)
outfile_text = "{}/{}.txt".format("/var/www/html/out",
format_time)
df = open(outfile_text, 'w', 1)
dql = len(frame_times) - 1
time_diff = frame_times[1] - frame_times[dql]
fps = 200 / time_diff.total_seconds()
print("FPS: ", fps)
writer = cv2.VideoWriter(
outfile, cv2.VideoWriter_fourcc(*'MJPG'), fps,
(frames[0].shape[1], frames[0].shape[0]), True)
while frames:
img = frames.pop()
ft = frame_times.pop()
format_time = ft.strftime("%Y-%m-%d %H:%M:%S.")
dec_sec = ft.strftime("%f")
format_time = format_time + dec_sec
df.write(format_time + "\n")
writer.write(img)
#i = i + 1
writer.release()
df.close()
count = count + 1
def cam_loop(pipe_parent):
#cv2.namedWindow("pepe")
lc = 0
tstamp_prev = None
motion_on = 0
motion_off = 0
config = read_config()
print (config['cam_ip'])
cap = cv2.VideoCapture("rtsp://" + config['cam_ip'] + "/av0_1&user=admin&password=admin")
#cv2.setUseOptimized(True)
image_acc = None
time.sleep(5)
frames = deque(maxlen=200)
frame_times = deque(maxlen=200)
time_start = datetime.datetime.now()
count = 0
while True:
_ , frame = cap.read()
#if _ is True:
# frame_time = datetime.datetime.now()
# frames.appendleft(frame)
# frame_times.appendleft(frame_time)
# #pipe_parent.send(frame)
if True:
#alpha = .25
alpha, tstamp_prev = iproc.getAlpha(tstamp_prev)
#frame = cv2.resize(frame, (0,0), fx=0.25, fy=0.25)
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
frame = cv2.GaussianBlur(frame, (21, 21), 0)
if image_acc is None:
image_acc = np.empty(np.shape(frame))
image_diff = cv2.absdiff(image_acc.astype(frame.dtype), frame,)
hello = cv2.accumulateWeighted(frame, image_acc, alpha)
_,threshold = cv2.threshold(image_diff, 30, 255, cv2.THRESH_BINARY)
thresh= cv2.dilate(threshold, None , iterations=2)
(_, cnts, xx) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
if len(cnts) == 0:
motion_off = motion_off + 1
elif len(cnts) < 30 :
motion_on = motion_on + 1
motion_off = 0
print (len(cnts), motion_on)
if motion_off > 3 and motion_on < 3:
motion_on = 0
if count < 100:
motion_on = 0
#if motion_off > 10 and motion_on >=5:
# r = requests.get("http://" + config['cam_ip'] + "/webs/btnSettingEx?flag=1000¶mchannel=0¶mcmd=1058¶mctrl=25¶mstep=0¶mreserved=0&")
if motion_off > 10 and motion_on >= 3:
# r = requests.get("http://" + config['cam_ip'] + "/webs/btnSettingEx?flag=1000¶mchannel=0¶mcmd=1058¶mctrl=50¶mstep=0¶mreserved=0&")
print("RECORD BUFFER NOW!\n")
os.system("touch /home/pi/fireball_camera/write_buffer");
time.sleep(2)
os.system("rm /home/pi/fireball_camera/write_buffer");
motion_on = 0
#motion_off = 0
count = 0
count = count + 1
def show_loop(pipe_child, shared_dict):
#cv2.namedWindow("pepe")
#config = read_config()
print(config['cam_ip'])
device_lat = config['device_lat']
device_lng = config['device_lng']
device_operator = config['first_name'] + " " + config['last_name']
device_id = config['device_id']
image_acc = None
nice_image_acc = None
tstamp_prev = None
count = 0
#time_start = datetime.datetime.now()
time_start = time.time()
frame = pipe_child.recv()
frames = deque(maxlen=200)
frame_times = deque(maxlen=200)
#frame_data = deque(maxlen=200)
motion_on = 0
motion_off = 0
cnts = []
lc = 1
calibrate_now = 0
calibrate_start = 0
#sense_up = 0
while True:
frame = pipe_child.recv()
alpha, tstamp_prev = iproc.getAlpha(tstamp_prev)
#lock.acquire()
#print ("SHOW LOOP:", count)
#frame = cv2.resize(frame, (0,0), fx=0.8, fy=0.8)
#frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
frame = cv2.GaussianBlur(frame, (21, 21), 0)
if image_acc is None:
image_acc = np.empty(np.shape(frame))
image_diff = cv2.absdiff(
image_acc.astype(frame.dtype),
frame,
)
hello = cv2.accumulateWeighted(frame, image_acc, alpha)
_, threshold = cv2.threshold(image_diff, 30, 255, cv2.THRESH_BINARY)
thresh = cv2.dilate(threshold, None, iterations=2)
(_, cnts, xx) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
#print(len(cnts), motion_on, motion_off)
#print(cnts)
if len(cnts) > 1:
shared_dict['noise'] = shared_dict['noise'] + 1
if len(cnts) == 0:
shared_dict['motion_off'] = shared_dict['motion_off'] + 1
#middle_pixel = 0
#avg_color = 0
else:
# if the total cnts are over 1 then cat to the log!
dist_time = datetime.datetime.now()
log_entry = str(cam_num) + "|" + str(
len(cnts)) + "|" + str(dist_time)
cmd = "/bin/echo \"" + log_entry + "\" >> /tmp/distortion.log"
os.system(cmd)
#area = cv2.contourArea(cnts[0])
#perim = cv2.arcLength(cnts[0], True)
#print ("Perim:", perim)
#x,y,w,h = cv2.boundingRect(cnts[0])
#x2 = x+w
#y2 = y+h
#mx = int(x + (w/2))
#my = int(y + (h/2))
#print ("XY:", x,x2,y,y2)
#middle_pixel = frame[my,mx]
#middle_sum = np.sum(middle_pixel)
#crop_frame = frame[y:y2,x:x2]
#avg_color_per_row = np.average(crop_frame, axis=0)
#avg_color = np.average(avg_color_per_row, axis=0)
#shared_dict['xywh'] = (x,y,w,h)
#shared_dict['area'] = area
#shared_dict['perim'] = perim
#shared_dict['middel_pixel'] = middle_pixel
#shared_dict['avg_color'] = avg_color
shared_dict['motion_on'] = shared_dict['motion_on'] + 1
shared_dict['motion_off'] = 0
shared_dict['cnts'] = len(cnts)
print("MMO:", shared_dict['cnts'], shared_dict['motion_on'],
shared_dict['motion_off'])
if shared_dict['motion_off'] > 5 and shared_dict['motion_on'] < 3:
shared_dict['motion_on'] = 0
#cv2.imshow('pepe', image_diff)
#cv2.waitKey(5)
count = count + 1
def stack_calibration_video(outfile):
frames = deque(maxlen=200)
count = 0
show = None
#cv2.namedWindow('pepe')
file_exists = Path(outfile)
if (file_exists.is_file()):
print("File found.")
else:
print("File not found.", outfile)
exit()
cap = cv2.VideoCapture(outfile)
time.sleep(2)
count = 0
tstamp_prev = None
image_acc = None
dst = None
dst_x = None
while count < 89:
_, frame = cap.read()
if frame is None:
print("Frame is none.")
continue
frames.appendleft(frame)
alpha, tstamp_prev = iproc.getAlpha(tstamp_prev)
if count == 80:
sframe = frame
#alpha = .23
alpha = .5
nice_frame = frame
#frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
#frame = cv2.GaussianBlur(frame, (21, 21), 0)
if show is None:
show = np.empty(np.shape(frame))
if image_acc is None:
image_acc = np.empty(np.shape(frame))
if dst is None:
dst = np.empty(np.shape(frame))
image_diff = cv2.absdiff(
image_acc.astype(frame.dtype),
frame,
)
hello = cv2.accumulateWeighted(frame, image_acc, alpha)
abs_frame = cv2.convertScaleAbs(frame)
abs_image_acc = cv2.convertScaleAbs(image_acc)
if dst is None:
dst = abs_image_acc
else:
dst = cv2.convertScaleAbs(dst)
dst = cv2.addWeighted(abs_frame, alpha, dst, alpha, 0)
#nice_avg = cv2.convertScaleAbs(image_dst)
#cv2.imshow('pepe', dst)
#cv2.waitKey(1)
count = count + 1
image_acc = np.empty(np.shape(frame))
framex = frames[45]
framey = frames[88]
image_diff = cv2.absdiff(
framex.astype(framey.dtype),
framey,
)
#cv2.imshow("pepe",image_diff)
#cv2.waitKey(0)
for i in range(1, 5):
k = i * 5 + 30
frame = frames[i + 25]
#cv2.imshow('pepe', frame)
#cv2.waitKey(0)
image_diff = cv2.absdiff(
image_acc.astype(frame.dtype),
frame,
)
#cv2.imshow('pepe', image_diff)
#cv2.waitKey(0)
hello = cv2.accumulateWeighted(frame, image_acc, alpha)
abs_frame = cv2.convertScaleAbs(frame)
abs_image_acc = cv2.convertScaleAbs(image_acc)
if dst_x is None:
dst_x = abs_image_acc
else:
dst_x = cv2.convertScaleAbs(dst_x)
#cv2.imshow('pepe', dst_x)
#cv2.waitKey(0)
print("Writing out files.")
jpg_file = outfile.replace(".avi", ".jpg")
print(jpg_file)
print(dst)
cv2.imwrite(jpg_file, dst)
jpg_file_x = outfile.replace(".avi", "-x.jpg")
cv2.imwrite(jpg_file_x, dst_x)
jpg_file = jpg_file.replace(".jpg", "-single.jpg")
sframe = cv2.convertScaleAbs(sframe)
cv2.imwrite(jpg_file, sframe)
print("Done")
def view(file, show=0):
nostars = 0
skip = 0
avg_color = 0
max_cons_motion = 0
straight_line = -1
final_image = None
start_time = int(time.time())
el = file.split("/")
act_file = el[-1]
dir = file.replace(act_file, "")
acc_file = act_file.replace(".mp4", "-acc.jpg")
star_file = act_file.replace(".mp4", "-stars.jpg")
acc_file = dir + "stars/" + acc_file
star_file = dir + "stars/" + star_file
# before processing dump frames from this file for 24 hour time lapse
#os.system("./dump-frames-tl.py " + file )
config_file = ""
try:
(file_date, cam_num) = file.split("-")
cam_num = cam_num.replace(".avi", "")
except:
cam_num = ""
if cam_num == "":
config = read_config(config_file)
else:
#cam_num = sys.argv[1]
config_file = "conf/config-" + cam_num + ".txt"
config = read_config(config_file)
#config = read_config(config_file)
frame_time_data = []
values = {}
dir_name = os.path.dirname(file) + "/"
file_name = file.replace(dir_name, "")
summary_file_name = file_name.replace(".mp4", "-summary.txt")
data_file_name = file_name.replace(".mp4", ".txt")
screen_cap_file_name = file_name.replace(".mp4", ".jpg")
object_file_name = file_name.replace(".mp4", "-objects.jpg")
time_file_name = file_name.replace(".mp4", "-time.txt")
capture_date = parse_file_date(file_name)
#last_cal_date = # Get last / closest calibration date
file_base_name = file_name.replace(".mp4", "")
print(capture_date)
status = day_or_night(config, capture_date)
if status == "day":
print("Skip this daytime file.")
move_file(dir_name + file_name, "day")
return ()
# read in time file if it exists
#if os.path.isfile(dir_name + "/" + time_file_name):
# frame_time_data = read_time_file(dir_name + "/" + time_file_name)
# print ("FRAME TIME DATA LENGTH:", len(frame_time_data))
# time.sleep(1)
#else:
# print ("no frame time data! " + dir_name + "/" + time_file_name )
# for x in range(0, 225):
# frame_time_data.append("|||")
#fps_t = 0
#for ftd in frame_time_data:
# print ("FRAMEdata", ftd)
# fps, tc, tt, tx = ftd.split("|")
# if fps == "":
# fps = 0
# fps_t = int(float(fps_t)) + int(float(fps))
#if len(frame_time_data) > 0:
# avg_fps = fps_t / len(frame_time_data)
#else :
# avg_fps = 0
avg_fps = 25
print("Viewing file: " + file)
print("Directory: " + dir_name)
print("File Name: " + file_name)
print("Summary File Name: " + summary_file_name)
print("Data File Name: " + data_file_name)
print("Screen Cap File Name: " + screen_cap_file_name)
print("Object File Name: " + object_file_name)
print("Capture Date: " + capture_date)
#print ("FPS: " + str(avg_fps))
# make sure the file exists
if os.path.isfile(file) is False:
print("This file does not exist. Exiting.")
return (0)
else:
print("The file is ok.")
#process video
tstamp_prev = None
image_acc = None
last_frame = None
last_gray_frame = None
nt_acc = None
nice_image_acc = None
final_image = None
cur_image = None
frame_count = 0
# open data log file
#fp = open(dir_name + "/" + data_file_name, "w")
#fp2 = open(dir_name + "/" + summary_file_name, "w")
#fp.write("frame|contours|x|y|w|h|color|fps|adjusted_unixtime|unixtime|time_offset\n")
#fp2.write("frame|contours|x|y|w|h|color|fps|adjusted_unixtime|unixtime|time_offset\n")
show = 1
if show == 1:
cv2.namedWindow('pepe')
#cap = skvideo.io.VideoCapture(file)
cap = cv2.VideoCapture(file)
time.sleep(2)
xs = []
ys = []
motion_frames = []
frames = []
colors = []
show_sw = 0
noise = 0
prev_motion = 0
cons_motion = 0
motion_events = []
while True:
_, frame = cap.read()
if frame is not None:
frame[680:720, 0:620] = [0, 0, 0]
frame_count = frame_count + 1
#frames.extend([frame])
if frame is None or nostars > 5:
if frame_count <= 1:
print("Bad file.")
return (0)
else:
end_time = int(time.time())
elapsed = end_time - start_time
print("Processed ", frame_count, "frames. in ", elapsed,
"seconds")
# finish processing file and write output files
total_motion = len(motion_frames)
if total_motion > 3:
half_motion = int(round(total_motion / 2, 0))
print("key frame #1 : ", 1)
print("key frame #2 : ", half_motion)
print("key frame #3 : ", total_motion - 1)
print("Xs", xs)
print("Ys", ys)
print("MF", motion_frames)
avg_color = sum(colors) / float(len(colors))
print("CL", colors)
print("Avg Color: ", avg_color)
#object_file_image = (frames[motion_frames[1]] * .33) + (frames[motion_frames[half_motion]] * .33) + (frames[motion_frames[total_motion-2]] * .33)
x1 = xs[1]
y1 = xs[1]
x2 = xs[half_motion]
y2 = xs[half_motion]
x3 = xs[total_motion - 2]
y3 = xs[total_motion - 2]
xmax = max(xs)
ymax = max(ys)
xmin = min(xs)
ymin = min(ys)
skip = 0
if xmax - xmin == 0 and ymax - ymin == 0:
skip = 1
straight_line = compute_straight_line(
x1, y1, x2, y2, x3, y3)
if len(motion_events) > 3:
max_cons_motion = max(motion_events)
if (straight_line < 1
and straight_line >= 0) or avg_color > 190:
meteor_yn = "Y"
else:
meteor_yn = "N"
if status == 'night':
meteor_yn = "Y"
else:
meteor_yn = "N"
if total_motion <= 3:
meteor_yn = "N"
#meteor_yn = "Y"
if skip == 1:
meteor_yn = "N"
print("Skipping not enough x,y movement!", xmax, xmin,
ymax, ymin)
if noise >= 5:
meteor_yn = "N"
print("Skipping to much noise!", noise)
if avg_fps < 20:
meteor_yn = "N"
print("Skipping calibration file!", avg_fps)
# write out the stacked image_acc and the stacked star file
# nt_acc
print("Writing:", acc_file)
print("Writing:", star_file)
#image_acc_cl = cv2.cvtColor(image_acc, cv2.COLOR_GRAY2BGR)
#en_image_acc = Image.fromarray(cv2.convertScaleAbs(image_acc))
enhancer = ImageEnhance.Brightness(final_image)
enhanced_image = enhancer.enhance(1)
np_enhanced_image = np.asarray(enhanced_image)
#cv2.imwrite(acc_file, np_enhanced_image)
print("Total Stars: ", total_stars)
if total_stars == 0:
star_file = star_file.replace("/stars/", "/clouds/")
acc_file = acc_file.replace("/stars/", "/clouds/")
cv2.imwrite(acc_file, np_enhanced_image)
if total_stars > 0:
cv2.imwrite(star_file, star_image)
#cv2.imshow('pepe', star_image)
#cv2.waitKey(100)
print("Status:", status)
print("Total Motion:", total_motion)
print("Cons Motion:", cons_motion)
print("Straight Line:", straight_line)
print("Likely Meteor:", meteor_yn)
#obj_outfile = dir_name + "/" + object_file_name
#sc_outfile = dir_name + "/" + screen_cap_file_name
#cv2.imwrite(obj_outfile, object_file_image)
#cv2.imwrite(sc_outfile, object_file_image)
#write summary & data files
#fp.close()
#fp2.close()
# prep event or capture for upload to AMS
values['datetime'] = capture_date
values['motion_frames'] = total_motion
values['cons_motion'] = max_cons_motion
values['color'] = avg_color
values['straight_line'] = straight_line
values['meteor_yn'] = meteor_yn
values['bp_frames'] = total_motion
print("ending here...")
exit()
if meteor_yn == 'Y':
try:
values['best_caldate'] = config['best_caldate']
except:
config['best_caldate'] = '0000-00-00 00:00:00'
values['best_caldate'] = config['best_caldate']
#try:
#log_fireball_event(config, file, dir_name + "/" + summary_file_name, dir_name + "/" + object_file_name, values)
#except:
# print ("failed to upload event file.")
# return(0)
#move files to maybe dir
print("Move to maybe dir!")
#os.system("mv " + dir_name + "/" + file_base_name + "* " + "/var/www/html/out/maybe/")
move_file(dir_name + file_name, "maybe")
else:
#log_motion_capture(config, dir_name + "/" + object_file_name, values)
#try:
#log_motion_capture(config, dir_name + "/" + object_file_name, values)
#except:
# print ("failed to upload capture file.")
# return(0)
#print ("Move to false dir!")
if (skip == 1 or noise >= 5) and status == 'night':
#os.system("mv " + dir_name + "/" + file_base_name + "* " + "/var/www/html/out/dist/")
move_file(dir_name + file_name, "dist")
elif avg_fps < 20:
move_file(dir_name + file_name, "calvid")
else:
if total_motion >= 3:
move_file(dir_name + file_name, "false")
else:
move_file(dir_name + file_name, "no_motion_night")
return (1)
# main video processing loop here
if status == "day":
mod_skip = 5
else:
mod_skip = 5
if frame_count % mod_skip == 0:
nice_frame = frame
alpha, tstamp_prev = iproc.getAlpha(tstamp_prev)
frame = cv2.resize(frame, (0, 0), fx=0.5, fy=0.5)
#print ("AFTER:", np.shape(frame))
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray_frame = frame
# if last_gray_frame is None:
# last_gray_frame = gray_frame
# else:
# gray_frame_cmb = gray_frame + last_gray_frame
# last_gray_frame = gray_frame
# gray_frame = gray_frame_cmb
frame = cv2.GaussianBlur(frame, (21, 21), 0)
if last_frame is None:
last_frame = nice_frame
if image_acc is None:
image_acc = np.empty(np.shape(frame))
image_diff = cv2.absdiff(
image_acc.astype(frame.dtype),
frame,
)
alpha = .076
hello = cv2.accumulateWeighted(frame, image_acc, alpha)
_, threshold = cv2.threshold(image_diff, 30, 255,
cv2.THRESH_BINARY)
thresh = cv2.dilate(threshold, None, iterations=2)
(_, cnts, xx) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
frame_img = Image.fromarray(frame)
if final_image is None:
final_image = frame_img
final_image = ImageChops.lighter(final_image, frame_img)
if frame_count > 5:
np_final_image = np.asarray(final_image)
gray_nice_frame = cv2.cvtColor(nice_frame, cv2.COLOR_BGR2GRAY)
total_stars, star_image = find_stars(gray_nice_frame)
if total_stars == 0:
print("Cloudy...???")
nostars = nostars + 1
else:
nostars = 0
# if you want to stack the accumulated frames..
#image_acc_pil = Image.fromarray(cv2.convertScaleAbs(image_acc))
#final_image=ImageChops.lighter(final_image,image_acc_pil)
data = str(frame_count) + "|"
color = 0
contours = len(cnts)
x, y, w, h = 0, 0, 0, 0
if contours > 3:
noise = noise + 1
if contours > 0 and frame_count > 5:
x, y, w, h = cv2.boundingRect(cnts[0])
mx = x + w
my = y + h
cx = int(x + (w / 2))
cy = int(y + (h / 2))
color = gray_frame[cy, cx]
xs.extend([x])
ys.extend([y])
colors.extend([color])
motion_frames.extend([frame_count])
prev_motion = 1
cons_motion = cons_motion + 1
else:
if cons_motion > 0:
motion_events.append(cons_motion)
prev_motion = 0
line_data = ""
#line_data = str(frame_count) + "|" + str(contours) + "|" + str(x) + "|" + str(y) + "|" + str(w) + "|" + str(h) + "|" + str(color) + "|" + frame_time_data[frame_count-1] + "\n"
#fp.write(line_data)
#fp2.write(line_data)
print(frame_count, contours, x, y, w, h, color)
if frame_count % 10 == 0:
np_final_image = np.asarray(final_image)
np_star_image = np.asarray(star_image)
small_star_image = cv2.resize(star_image, (0, 0),
fx=0.5,
fy=0.5)
#cv2.imshow('pepe', small_star_image)
cv2.imshow('pepe', np_final_image)
#cv2.imshow('pepe', cv2.convertScaleAbs(image_acc))
cv2.waitKey(1)
def show_loop(pipe_child):
image_acc = None
cal_image = None
nice_image_acc = None
stack = None
tstamp_prev = None
cv2.namedWindow('pepe')
count = 0
time_start = datetime.datetime.now()
Q = None
frame = pipe_child.recv()
#frames = deque(np.empty(np.shape(frame)), maxlen=256)
frames = deque(maxlen=256)
firstFrame = None
motion_on = 0
motion_off = 0
while True:
frame = pipe_child.recv()
frames.appendleft(frame)
if firstFrame is None:
firstFrame = frame
stack = frame
continue
if count % 1 == 0:
nice_frame = frame
alpha, tstamp_prev = iproc.getAlpha(tstamp_prev)
if nice_image_acc is None:
nice_image_acc = np.empty(np.shape(frame))
nice_image_diff = cv2.absdiff(nice_image_acc.astype(frame.dtype), nice_frame,)
hello = cv2.accumulateWeighted(nice_frame, nice_image_acc, alpha)
#hellp = cv2.addWeighted(nice_image_acc,.5, nice_frame, .5, .5 )
stack = stack + frame
if count % 30 == 0:
stack = frame
nice_avg = cv2.convertScaleAbs(nice_image_acc)
frame = cv2.resize(frame, (0,0), fx=0.5, fy=0.5)
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
frame = cv2.GaussianBlur(frame, (21, 21), 0)
if image_acc is None:
image_acc = np.empty(np.shape(frame))
image_diff = cv2.absdiff(image_acc.astype(frame.dtype), frame,)
hello = cv2.accumulateWeighted(frame, image_acc, alpha)
if cal_image is None:
cal_image = nice_image_acc
if count % 30 == 0:
cal_image = cal_image + nice_image_acc
cal_image_show = cv2.convertScaleAbs(cal_image)
if count % 100 == 0:
cal_iamge = nice_image_acc
#avg = cv2.convertScaleAbs(image_acc)
_, threshold = cv2.threshold(image_diff, 30, 255, cv2.THRESH_BINARY)
thresh= cv2.dilate(threshold, None , iterations=2)
(_, cnts, xx) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
if len(cnts) == 0:
motion_off = motion_off + 1
else:
motion_on = motion_on + 1
motion_off = 0
#for c in cnts:
## if cv2.contourArea(c) < 100:
# continue
# motion_on = motion_on + 1
# motion_off = 0
if motion_off > 10 and motion_on < 10:
motion_on = 0
motion_off = 0
if motion_off > 20 and motion_on > 10:
print ("RECORD BUFFER NOW!")
motion_off = 0
motion_on = 0
#write_buffer(frames)
i = 1000
timestamp = datetime.datetime.now()
outfile = "{}/{}.avi".format("out",
timestamp.strftime("%Y%m%d-%H%M%S"))
if record == 1:
writer = cv2.VideoWriter(outfile, cv2.VideoWriter_fourcc(*'MJPG'), 25, (frames[0].shape[1], frames[0].shape[0]), True)
while frames:
img = frames.pop()
#cv2.putText(img, datetime.datetime.now().strftime("%A %d %B %Y %I:%M:%S.%f%p"),
#(10, img.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 1)
#cv2.imwrite("out/" + str(i) + ".jpg", img)
writer.write(img)
i = i + 1
writer.release()
print ("motion_on, motion off, contours", motion_on, motion_off, len(cnts))
#(x, y, w, h) = cv2.boundingRect(c)
#cv2.rectangle(frame, (x, y), (x + w, y + w), (0, 255, 0), 2)
#closed = cv2.morphologyEx(dilated, cv2.MORPH_CLOSE, MORPH_KERNEL)
cv2.imshow('pepe', nice_frame)
#cv2.imshow('pepe', cal_image_show)
#cv2.imshow('pepe', cv2.convertScaleAbs(image_diff))
cv2.waitKey(1)
count = count + 1
now = datetime.datetime.now()
delta = now - time_start
limit = delta.total_seconds()