def load_Bag_Folders(bag_folders_path = opjD('runs')):
BF_dic = {}
bag_folders_paths_list = sorted(gg(opj(bag_folders_path,'*')),key=natural_keys)
for bfp in bag_folders_paths_list:
run_name = bfp.split('/')[-1]
preprocessed_dir,left_image_bound_to_data_name = get_preprocess_dir_name_info(bfp)
if len(gg(opj(bfp,preprocessed_dir,'Bag_Folder.pkl'))) == 1:
print('')
cprint(opj(run_name,preprocessed_dir,'Bag_Folder.pkl')+' exists, loading it.','yellow','on_red')
BF = load_obj(opj(bfp,preprocessed_dir,'Bag_Folder.pkl'))
else:
if False:
BF = Bag_Folder.init(bfp,
preprocessed_dir=preprocessed_dir,
left_image_bound_to_data_name=left_image_bound_to_data_name,
NUM_STATE_ONE_STEPS=NUM_STATE_ONE_STEPS)
save_obj(BF,opj(bfp,preprocessed_dir,'Bag_Folder.pkl'))
cprint('ERROR!!! '+opj(run_name,preprocessed_dir,'Bag_Folder.pkl')+' does not exist!','yellow','on_red')
assert(False)
if run_name in BF_dic:
cprint('ERROR!!! '+run_name+' already in BF_dic!','yellow','on_red')
assert(False)
BF_dic[run_name] = BF
return BF_dic
def preprocess_Bag_Folder(bag_folders_path=opjD("runs"), NUM_STATE_ONE_STEPS=30, graphics=True):
bag_folders_paths_list = sorted(gg(opj(bag_folders_path, "*")), key=natural_keys)
try:
for bfp in bag_folders_paths_list:
run_name = bfp.split("/")[-1]
preprocessed_dir, left_image_bound_to_data_name = get_preprocess_dir_name_info(bfp)
if len(gg(opj(bfp, preprocessed_dir, "Bag_Folder.pkl"))) == 1:
print("")
cprint(opj(run_name, preprocessed_dir, "Bag_Folder.pkl") + " exists, loading it.", "yellow", "on_red")
BF = load_obj(opj(bfp, preprocessed_dir, "Bag_Folder.pkl"))
else:
BF = Bag_Folder.init(
bfp,
preprocessed_dir=preprocessed_dir,
left_image_bound_to_data_name=left_image_bound_to_data_name,
NUM_STATE_ONE_STEPS=NUM_STATE_ONE_STEPS,
)
save_obj(BF, opj(bfp, preprocessed_dir, "Bag_Folder.pkl"))
if graphics:
figure(run_name + " timecourses")
plot(BF["data"]["raw_timestamps"], 100 * BF["data"]["encoder"], "y")
plot(BF["data"]["raw_timestamps"], BF["data"]["state_one_steps"], "bo-")
plot(BF["data"]["good_start_timestamps"], zeros(len(BF["data"]["good_start_timestamps"])) + 100, "go")
plot(BF["data"]["raw_timestamps"], 2000 * BF["data"]["raw_timestamp_deltas"], "r")
ylim(0, 1000)
figure(run_name + " raw_timestamp_deltas")
rtd = BF["data"]["raw_timestamp_deltas"].copy()
rtd[rtd > 0.08] = 0.08
hist(rtd)
# plot(BF['data']['raw_timestamps'],100*BF['data']['state'],'r')
# plot(BF['data']['raw_timestamps'],100*BF['data']['acc_z'],'r')
figure(run_name + " scatter")
plot(
BF["data"]["steer"][BF["data"]["good_start_indicies"]],
BF["data"]["gyro_x"][BF["data"]["good_start_indicies"]],
"o",
)
plt.pause(0.001)
except Exception as e:
cprint("********** Exception ***********************", "red")
print(e.message, e.args)
def preprocess_Bag_Folder(bag_folders_path = opjD('runs'),NUM_STATE_ONE_STEPS=30,graphics=True):
bag_folders_paths_list = sorted(gg(opj(bag_folders_path,'*')),key=natural_keys)
try:
for bfp in bag_folders_paths_list:
run_name = bfp.split('/')[-1]
preprocessed_dir,left_image_bound_to_data_name = get_preprocess_dir_name_info(bfp)
if len(gg(opj(bfp,preprocessed_dir,'Bag_Folder.pkl'))) == 1:
print('')
cprint(opj(run_name,preprocessed_dir,'Bag_Folder.pkl')+' exists, loading it.','yellow','on_red')
BF = load_obj(opj(bfp,preprocessed_dir,'Bag_Folder.pkl'))
else:
BF = Bag_Folder.init(bfp,
preprocessed_dir=preprocessed_dir,
left_image_bound_to_data_name=left_image_bound_to_data_name,
NUM_STATE_ONE_STEPS=NUM_STATE_ONE_STEPS)
save_obj(BF,opj(bfp,preprocessed_dir,'Bag_Folder.pkl'))
if graphics:
figure(run_name+' timecourses')
plot(BF['data']['raw_timestamps'],100*BF['data']['encoder'],'y')
plot(BF['data']['raw_timestamps'],BF['data']['state_one_steps'],'bo-')
plot(BF['data']['good_start_timestamps'],zeros(len(BF['data']['good_start_timestamps']))+100,'go')
plot(BF['data']['raw_timestamps'],2000*BF['data']['raw_timestamp_deltas'],'r')
ylim(0,1000)
figure(run_name+' raw_timestamp_deltas')
rtd = BF['data']['raw_timestamp_deltas'].copy()
rtd[rtd>0.08] = 0.08
hist(rtd)
#plot(BF['data']['raw_timestamps'],100*BF['data']['state'],'r')
#plot(BF['data']['raw_timestamps'],100*BF['data']['acc_z'],'r')
figure(run_name+' scatter')
plot(BF['data']['steer'][BF['data']['good_start_indicies']],BF['data']['gyro_x'][BF['data']['good_start_indicies']],'o')
plt.pause(0.001)
except Exception as e:
cprint("********** Exception ***********************",'red')
print(e.message, e.args)
if False:
ts = sorted(L.keys())
dts = [0]
for i in range(1, len(ts)):
dts.append(ts[i] - ts[i - 1])
figure(1)
plot(ts, dts)
figure(2)
hist(dts)
import kzpy3.teg3.data.access.Bag_Folder as Bag_Folder
import kzpy3.teg3.data.access.Bag_File as Bag_File
BF = Bag_Folder.init(
'/home/karlzipser/Desktop/direct_home_06Dec16_16h01m42s_Mr_Blue',
preprocessed_dir='.preprocessed2',
left_image_bound_to_data_name='left_image_bound_to_data.pkl',
NUM_STATE_ONE_STEPS=10)
#plot(BF['data']['raw_timestamps'],BF['data']['state_one_steps'],'bo-')
plot(BF['data']['good_start_timestamps'],
zeros(len(BF['data']['good_start_timestamps'])) + 100, 'go')
#plot(BF['data']['raw_timestamps'],2000*np.array(BF['data']['raw_timestamp_deltas']),'r')
#plot(BF['data']['raw_timestamps'],100*BF['data']['encoder'],'r')
#plot(BF['data']['raw_timestamps'],100*BF['data']['state'],'r')
#plot(BF['data']['raw_timestamps'],100*BF['data']['acc_z'],'r')
bf = BF['bag_file_num_dic'][15]
bid = Bag_File.load_images(bf)
bag_left_timestamps = sorted(bid['left'].keys())
plot(bag_left_timestamps, 2000 + np.zeros(bag_left_timestamps), 'go')
if False:
ts = sorted(L.keys())
dts = [0]
for i in range(1,len(ts)):
dts.append(ts[i] - ts[i-1])
figure(1)
plot(ts,dts)
figure(2)
hist(dts)
import kzpy3.teg3.data.access.Bag_Folder as Bag_Folder
import kzpy3.teg3.data.access.Bag_File as Bag_File
BF = Bag_Folder.init('/home/karlzipser/Desktop/direct_home_06Dec16_16h01m42s_Mr_Blue',
preprocessed_dir='.preprocessed2',
left_image_bound_to_data_name='left_image_bound_to_data.pkl',
NUM_STATE_ONE_STEPS=10)
#plot(BF['data']['raw_timestamps'],BF['data']['state_one_steps'],'bo-')
plot(BF['data']['good_start_timestamps'],zeros(len(BF['data']['good_start_timestamps']))+100,'go')
#plot(BF['data']['raw_timestamps'],2000*np.array(BF['data']['raw_timestamp_deltas']),'r')
#plot(BF['data']['raw_timestamps'],100*BF['data']['encoder'],'r')
#plot(BF['data']['raw_timestamps'],100*BF['data']['state'],'r')
#plot(BF['data']['raw_timestamps'],100*BF['data']['acc_z'],'r')
bf = BF['bag_file_num_dic'][15]
bid = Bag_File.load_images(bf)
bag_left_timestamps = sorted(bid['left'].keys())
plot(bag_left_timestamps,2000+np.zeros(bag_left_timestamps),'go')