mirror of
https://github.com/boltgolt/howdy.git
synced 2024-09-12 09:41:18 +02:00
Fix typos
Found via `codespell -S .mypy_cache,.git -L timout,ans,intenal`
This commit is contained in:
parent
db3a8cbfd4
commit
767176c804
16 changed files with 27 additions and 27 deletions
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@ -105,7 +105,7 @@ class StickyWindow(gtk.Window):
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ctx.set_source_surface(self.logo_surface)
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ctx.paint()
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# Calculate main message positioning, as the text is heigher if there's a subtext
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# Calculate main message positioning, as the text is higher if there's a subtext
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if self.subtext:
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ctx.move_to(380, 145)
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else:
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@ -179,7 +179,7 @@ class OnboardingWindow(gtk.Window):
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self.treeview = gtk.TreeView()
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self.treeview.set_vexpand(True)
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# Set the coloums
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# Set the columns
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for i, column in enumerate([_("Camera identifier or path"), _("Recommended")]):
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cell = gtk.CellRendererText()
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cell.set_property("ellipsize", pango.EllipsizeMode.END)
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@ -41,7 +41,7 @@ class MainWindow(gtk.Window):
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self.treeview = gtk.TreeView()
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self.treeview.set_vexpand(True)
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# Set the coloums
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# Set the columns
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for i, column in enumerate([_("ID"), _("Created"), _("Label")]):
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col = gtk.TreeViewColumn(column, gtk.CellRendererText(), text=i)
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self.treeview.append_column(col)
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@ -75,7 +75,7 @@ class MainWindow(gtk.Window):
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user = 'none'
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if self.active_user: user = self.active_user
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# Execute the list commond to get the models
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# Execute the list command to get the models
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status, output = subprocess.getstatusoutput(["howdy list --plain -U " + user])
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# Create a datamodel
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@ -1,5 +1,5 @@
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#!/usr/bin/python3
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# Used to check cameras before commiting to install
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# Used to check cameras before committing to install
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# Executed before primary apt install of files
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import subprocess
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@ -25,7 +25,7 @@ _howdy() {
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[ "$status" == "false" ] && COMPREPLY="true" || COMPREPLY="false"
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return 0
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;;
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# List the users availible
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# List the users available
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"-U")
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COMPREPLY=( $(compgen -u -- ${cur}) )
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return 0
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@ -43,7 +43,7 @@ parser.add_argument(
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metavar="command",
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choices=["add", "clear", "config", "disable", "list", "remove", "set", "snapshot", "test", "version"])
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# Add an argument for the extra arguments of diable and remove
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# Add an argument for the extra arguments of disable and remove
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parser.add_argument(
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_("arguments"),
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help=_("Optional arguments for the add, disable, remove and set commands."),
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@ -94,7 +94,7 @@ if os.geteuid() != 0:
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print("\tsudo howdy " + " ".join(sys.argv[1:]))
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sys.exit(1)
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# Beond this point the user can't change anymore, if we still have root as user we need to abort
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# Beyond this point the user can't change anymore, if we still have root as user we need to abort
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if args.user == "root":
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print(_("Can't run howdy commands as root, please run this command with the --user flag"))
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sys.exit(1)
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@ -186,7 +186,7 @@ if not face_locations:
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print(_("No face detected, aborting"))
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sys.exit(1)
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# If more than 1 faces are detected we can't know wich one belongs to the user
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# If more than 1 faces are detected we can't know which one belongs to the user
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elif len(face_locations) > 1:
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print(_("Multiple faces detected, aborting"))
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sys.exit(1)
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@ -98,7 +98,7 @@ sec = int(time.time())
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# recognition time
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rec_tm = 0
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# Wrap everything in an keyboard interupt handler
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# Wrap everything in an keyboard interrupt handler
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try:
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while True:
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frame_tm = time.time()
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@ -131,7 +131,7 @@ try:
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hist = cv2.calcHist([frame], [0], None, [8], [0, 256])
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# All values combined for percentage calculation
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hist_total = int(sum(hist)[0])
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# Fill with the overal containing percentage
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# Fill with the overall containing percentage
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hist_perc = []
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# Loop though all values to calculate a percentage and add it to the overlay
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@ -139,7 +139,7 @@ try:
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value_perc = float(value[0]) / hist_total * 100
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hist_perc.append(value_perc)
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# Top left pont, 10px margins
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# Top left point, 10px margins
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p1 = (20 + (10 * index), 10)
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# Bottom right point makes the bar 10px thick, with an height of half the percentage
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p2 = (10 + (10 * index), int(value_perc / 2 + 10))
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@ -86,7 +86,7 @@ def send_to_ui(type, message):
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"""Send message to the auth ui"""
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global gtk_proc
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# Only execute of the proccess started
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# Only execute of the process started
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if "gtk_proc" in globals():
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# Format message so the ui can parse it
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message = type + "=" + message + " \n"
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@ -155,7 +155,7 @@ save_successful = config.getboolean("snapshots", "save_successful", fallback=Fal
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gtk_stdout = config.getboolean("debug", "gtk_stdout", fallback=False)
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rotate = config.getint("video", "rotate", fallback=0)
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# Send the gtk outupt to the terminal if enabled in the config
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# Send the gtk output to the terminal if enabled in the config
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gtk_pipe = sys.stdout if gtk_stdout else subprocess.DEVNULL
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# Start the auth ui, register it to be always be closed on exit
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@ -353,7 +353,7 @@ while True:
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scale_height, scale_width = frame.shape[:2]
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print(_(" Used: %dx%d") % (scale_height, scale_width))
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# Show the total number of frames and calculate the FPS by deviding it by the total scan time
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# Show the total number of frames and calculate the FPS by dividing it by the total scan time
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print(_("\nFrames searched: %d (%.2f fps)") % (frames, frames / timings["fl"]))
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print(_("Black frames ignored: %d ") % (black_tries, ))
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print(_("Dark frames ignored: %d ") % (dark_tries, ))
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@ -209,7 +209,7 @@ auto identify(pam_handle_t *pamh, int flags, int argc, const char **argv,
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// Will contain the responses from PAM functions
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int pam_res = PAM_IGNORE;
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// Check if we shoud continue
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// Check if we should continue
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if ((pam_res = check_enabled(config)) != PAM_SUCCESS) {
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return pam_res;
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}
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@ -44,7 +44,7 @@ auto optional_task<T>::wait(std::chrono::duration<R, P> dur)
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}
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// Get the value.
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// WARNING: The function hould be run only if the task has successfully been
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// WARNING: The function should be run only if the task has successfully been
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// stopped.
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template <typename T> auto optional_task<T>::get() -> T {
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assert(!is_active && spawned);
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@ -97,7 +97,7 @@ class ffmpeg_reader:
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)
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def read(self):
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""" Read a sigle frame from the self.video array. Will record a video if array is empty. """
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""" Read a single frame from the self.video array. Will record a video if array is empty. """
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# First time we are called, we want to initialize the camera by probing it, to ensure we have height/width
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# and then take numframes of video to fill the buffer for faster recognition.
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@ -72,11 +72,11 @@ class pyv4l2_reader:
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self.frame = Frame(self.device_name)
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def grab(self):
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""" Read a sigle frame from the IR camera. """
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""" Read a single frame from the IR camera. """
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self.read()
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def read(self):
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""" Read a sigle frame from the IR camera. """
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""" Read a single frame from the IR camera. """
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if not self.frame:
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self.record()
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@ -24,7 +24,7 @@ class VideoCapture:
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Config can either be a string to the path, or a pre-setup configparser.
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"""
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# Parse config from string if nedded
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# Parse config from string if needed
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if isinstance(config, str):
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self.config = configparser.ConfigParser()
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self.config.read(config)
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@ -136,7 +136,7 @@ def execute(config, gtk_proc, opencv):
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# Error out if a key has been set that was not declared by the module before
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if key not in instance.options:
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print("Unknow config option for rubberstamp " + type + ": " + key)
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print("Unknown config option for rubberstamp " + type + ": " + key)
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continue
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# Convert the argument string to an int or float if the declared option has that type
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@ -22,7 +22,7 @@ class nod(RubberStamp):
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last_reldist = -1
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# Last point the nose was at
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last_nosepoint = {"x": -1, "y": -1}
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# Contans booleans recording successful nods and their directions
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# Contains booleans recording successful nods and their directions
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recorded_nods = {"x": [], "y": []}
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starttime = time.time()
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@ -38,7 +38,7 @@ class nod(RubberStamp):
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# Detect all faces in the frame
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face_locations = self.face_detector(frame, 1)
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# Only continue if exacty 1 face is visible in the frame
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# Only continue if exactly 1 face is visible in the frame
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if len(face_locations) != 1:
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continue
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@ -47,10 +47,10 @@ class nod(RubberStamp):
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# Calculate the relative distance between the 2 eyes
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reldist = face_landmarks.part(0).x - face_landmarks.part(2).x
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# Avarage this out with the distance found in the last frame to smooth it out
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# Average this out with the distance found in the last frame to smooth it out
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avg_reldist = (last_reldist + reldist) / 2
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# Calulate horizontal movement (shaking head) and vertical movement (nodding)
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# Calculate horizontal movement (shaking head) and vertical movement (nodding)
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for axis in ["x", "y"]:
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# Get the location of the nose on the active axis
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nosepoint = getattr(face_landmarks.part(4), axis)
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@ -61,7 +61,7 @@ class nod(RubberStamp):
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last_reldist = reldist
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mindist = self.options["min_distance"]
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# Get the relative movement by taking the distance traveled and deviding it by eye distance
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# Get the relative movement by taking the distance traveled and dividing it by eye distance
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movement = (nosepoint - last_nosepoint[axis]) * 100 / max(avg_reldist, 1)
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# If the movement is over the minimal distance threshold
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