jgrewe/efish_tracking
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[tracking] tear apart the positions function, offer method to access raw pixel positions

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This commit is contained in:
Jan Grewe 2022-08-11 11:06:45 +02:00
parent 16873702d4
commit e854ab591f
2 changed files with 41 additions and 25 deletions
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17
etrack/image_marker.py
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@ -140,13 +140,14 @@ class MarkerTask():
if __name__ == "__main__": if __name__ == "__main__":
print("Hello Jan!")
tank_task = MarkerTask("tank limits", ["bottom left corner", "top left corner", "top right corner", "bottom right corner"], "Mark tank corners") tank_task = MarkerTask("tank limits", ["bottom left corner", "top left corner", "top right corner", "bottom right corner"], "Mark tank corners")
feeder_task = MarkerTask("Feeder positions", list(map(str, range(1, 2))), "Mark feeder positions") #feeder_task = MarkerTask("Feeder positions", list(map(str, range(1, 2))), "Mark feeder positions")
tasks = [tank_task, feeder_task] #tasks = [tank_task, feeder_task]
im = ImageMarker(tasks) im = ImageMarker([tank_task])
# vid1 = "2020.12.11_lepto48DLC_resnet50_boldnessDec11shuffle1_200000_labeled.mp4" vid1 = "/data/personality/secondhome/fischies/lepto_03/position/lepto03_position_2021.06.07_60.mp4"
print(sys.argv[0]) # print(sys.argv[0])
print (sys.argv[1]) # print (sys.argv[1])
vid1 = sys.argv[1] # vid1 = sys.argv[1]
marker_positions = im.mark_movie(vid1, 10) marker_positions = im.mark_movie(vid1, 00)
print(marker_positions) print(marker_positions)

49
etrack/tracking_result.py
View File

@ -20,7 +20,7 @@ def coordinate_transformation(position,x_0, y_0, x_factor, y_factor):
return (x, y) #in m return (x, y) #in m
class TrackingResult(object): class TrackingResult(object):
def __init__(self, results_file, x_0=0, y_0= 0, width_pixel=1230, height_pixel=1100, width_meter=0.81, height_meter=0.81) -> None: def __init__(self, results_file, x_0=0, y_0= 0, width_pixel=1230, height_pixel=1100, width_meter=0.81, height_meter=0.81) -> None:
super().__init__() super().__init__()
if not os.path.exists(results_file): if not os.path.exists(results_file):
@ -109,7 +109,11 @@ class TrackingResult(object):
bp string: the body part bp string: the body part
[type]: [description] [type]: [description]
""" """
time, x, y, l, bp = self.pixel_positions(scorer, bodypart, framerate, interpolate, min_likelihood)
x, y = self._to_meter(x, y)
return time, x, y, l, bp
def pixel_positions(self, scorer=0, bodypart=0, framerate=30, interpolate=True, min_likelihood=0.95):
if isinstance(scorer, nb.Number): if isinstance(scorer, nb.Number):
sc = self._scorer[scorer] sc = self._scorer[scorer]
elif isinstance(scorer, str) and scorer in self._scorer: elif isinstance(scorer, str) and scorer in self._scorer:
@ -123,25 +127,37 @@ class TrackingResult(object):
else: else:
raise ValueError("Bodypart %s is not in dataframe!" % bodypart) raise ValueError("Bodypart %s is not in dataframe!" % bodypart)
x = self._data_frame[sc][bp]["x"] if "x" in self._positions else [] x = np.asarray(self._data_frame[sc][bp]["x"] if "x" in self._positions else [])
x = (np.asarray(x) - self.x_0) * self.x_factor y = np.asarray(self._data_frame[sc][bp]["y"] if "y" in self._positions else [])
y = self._data_frame[sc][bp]["y"] if "y" in self._positions else [] l = np.asarray(self._data_frame[sc][bp]["likelihood"] if "likelihood" in self._positions else [])
y = (np.asarray(y) - self.y_0) * self.y_factor
l = self._data_frame[sc][bp]["likelihood"] if "likelihood" in self._positions else [] time = np.arange(len(x))/framerate
if interpolate:
time = np.arange(len(self._data_frame))/framerate x, y = self.interpolate(time, x, y, l, min_likelihood)
time2 = time[l > min_likelihood] return time, x, y, l, bp
if len(l[l > min_likelihood]) < 100:
print("%s has not datapoints with likelihood larger than %.2f" % (self._file_name, min_likelihood) ) def _to_meter(self, x, y):
return None, None, None, None, None new_x = (np.asarray(x) - self.x_0) * self.x_factor
new_y = (np.asarray(y) - self.y_0) * self.y_factor
return new_x, new_y
def _speed(self, t, x, y):
speed = np.sqrt(np.diff(x)**2 + np.diff(y)**2) / np.diff(t)
return speed
def interpolate(self, t, x, y, l, min_likelihood=0.9):
time2 = t[l > min_likelihood]
if len(l[l > min_likelihood]) < 10:
print("%s has less than 10 datapoints with likelihood larger than %.2f" % (self._file_name, min_likelihood) )
return None, None
x2 = x[l > min_likelihood] x2 = x[l > min_likelihood]
y2 = y[l > min_likelihood] y2 = y[l > min_likelihood]
x3 = np.interp(time, time2, x2) x3 = np.interp(t, time2, x2)
y3 = np.interp(time, time2, y2) y3 = np.interp(t, time2, y2)
return time, x3, y3, l, bp return x3, y3
def plot(self, scorer=0, bodypart=0, threshold=0.9, framerate=30): def plot(self, scorer=0, bodypart=0, threshold=0.9, framerate=30):
t, x, y, l, name = self.position_values(scorer=scorer, bodypart=bodypart, framerate=framerate) t, x, y, l, name = self.position_values(scorer=scorer, bodypart=bodypart, framerate=framerate, min_likelihood=threshold)
plt.scatter(x[l > threshold], y[l > threshold], c=t[l > threshold], label=name) plt.scatter(x[l > threshold], y[l > threshold], c=t[l > threshold], label=name)
plt.scatter(self.center_meter[0], self.center_meter[1], marker="*") plt.scatter(self.center_meter[0], self.center_meter[1], marker="*")
plt.plot(x[l > threshold], y[l > threshold]) plt.plot(x[l > threshold], y[l > threshold])
@ -152,7 +168,6 @@ class TrackingResult(object):
bar.set_label("time [s]") bar.set_label("time [s]")
plt.legend() plt.legend()
plt.show() plt.show()
from IPython import embed
if __name__ == '__main__': if __name__ == '__main__':