def __init__(self, tub_paths_arg):
tub_paths = utils.expand_path_arg(tub_paths_arg)
print('TubGroup:tubpaths:', tub_paths)
self.tubs = [Tub(path) for path in tub_paths]
self.input_types = {}
record_count = 0
for t in self.tubs:
t.update_df()
record_count += len(t.df)
self.input_types.update(dict(zip(t.inputs, t.types)))
print('joining the tubs {} records together. This could take {} minutes.'
.format(record_count,round(float(record_count / 300000),1)))
self.meta = {'inputs': list(self.input_types.keys()),
'types': list(self.input_types.values())}
self.df = pd.concat([t.df for t in self.tubs], axis=0, join='inner')
def playback(cfg, tub_names, model_name=None):
if not tub_names:
tub_names = os.path.join(cfg.DATA_PATH, '*')
tubgroup = TubGroup(tub_names)
if not model_name is None:
from donkeycar.parts.keras import KerasCategorical
kl = KerasCategorical()
kl.load(model_name)
pilot_angles = []
pilot_throttles = []
print('tub_names', tub_names)
tub_paths = utils.expand_path_arg(tub_names)
print('TubGroup:tubpaths:', tub_paths)
user_angles = []
user_throttles = []
tubs = [Tub(path) for path in tub_paths]
for tub in tubs:
num_records = tub.get_num_records()
print(num_records)
for iRec in tub.get_index(shuffled=False):
record = tub.get_record(iRec)
#record = tubs.get_record(random.randint(1,num_records+1))
img = record["cam/image_array"]
user_angle = float(record["user/angle"])
user_throttle = float(record["user/throttle"])
user_angles.append(user_angle)
user_throttles.append(user_throttle)
if not model_name is None:
pilot_angle, pilot_throttle = kl.run(img)
pilot_angles.append(pilot_angle)
pilot_throttles.append(pilot_throttle)
record = tubs[0].get_record(random.randint(1,num_records+1))
user_angle = float(record["user/angle"])
user_throttle = float(record["user/throttle"])
print(img.shape)
print('-----')
print(user_angle)
print(user_throttle)
plt.figure()
plt.imshow(img)
plt.plot([80,80+10*user_throttle*np.cos(user_angle)],[120,120+100*user_throttle*np.sin(user_angle)])
plt.figure()
plt.plot(user_angles)
plt.plot(user_throttles)
fig = plt.figure()
ax1 = plt.subplot2grid((2,2),(0,0))
record = tubs[0].get_record(1)
img = record["cam/image_array"]
imPlot = ax1.imshow(img,animated=True)
floorImg = lookAtFloorImg(img)
print(floorImg)
ax3 = plt.subplot2grid((2,2),(0,1))
imPlot2 = ax3.imshow(floorImg,animated=True)
ax2 = plt.subplot2grid((2,2),(1,0), colspan=2)
line1, = ax2.plot(user_angles)
line2, = ax2.plot(user_throttles)
if not model_name is None:
line4, = ax2.plot(pilot_angles)
line5, = ax2.plot(pilot_throttles)
line3, = ax2.plot([0,0],[-1,1])
def animate(i):
record = tubs[0].get_record(i)
img = record["cam/image_array"]
imPlot.set_array(img)
imPlot2.set_array(lookAtFloorImg(img))
line3.set_data([i,i],[-1,1])
#print(i)
#sys.stdout.flush()
return imPlot,
# Init only required for blitting to give a clean slate.
def init():
record = tubs[0].get_record(1)
img = record["cam/image_array"]
imPlot.set_array(img)
line3.set_data([0,0],[-1,1])
return imPlot,
ani = animation.FuncAnimation(fig, animate, np.arange(1, tubs[0].get_num_records()),
interval=100, blit=False)
plt.show()