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')
good_bag_timestamps = list(
set(BF['data']['good_start_timestamps']) & set(bag_left_timestamps))
plot(good_bag_timestamps, 2000 + np.zeros(len(good_bag_timestamps)), 'ro')
ts = sorted(bid['left'].keys())
for t in ts:
mi(bid['left'][t], 'left')
#mi(bid['right'][BF['left_image_bound_to_data'][t]['right_image']],'right')
plt.pause(0.0001)
plot(BF['data']['steer'], BF['data']['gyro_y'], 'o')
"""
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')
good_bag_timestamps = list(set(BF['data']['good_start_timestamps']) & set(bag_left_timestamps))
plot(good_bag_timestamps,2000+np.zeros(len(good_bag_timestamps)),'ro')
ts = sorted(bid['left'].keys())
for t in ts:
mi(bid['left'][t],'left')
#mi(bid['right'][BF['left_image_bound_to_data'][t]['right_image']],'right')
plt.pause(0.0001)
plot(BF['data']['steer'],BF['data']['gyro_y'],'o')
def bag_file_loader_thread(BF_dic,delay_before_delete,loaded_bag_files_names,played_bagfile_dic):
while True: # 50 brings us to 80.9 GiB, 75 brings us to 106.2. This is 56 loaded bag files, about 28 minutes of data, about 1% of 40 hours.
#print ("here",time.time())
if bag_file_loader_thread_please_exit:
cprint('THREAD:: exiting bag_file_loader_thread()')
return
elif not thread_please_load_data:
time.sleep(1)
else:
if len(loaded_bag_files_names) > 50: # if using flip images, halve the number of bag files loaded
cprint('\n\nTHREAD:: pause before deleting '+bf+'\n\n,'blue','on_red')
time.sleep(delay_before_delete)
played_bagfile_dic_keys = []
played_bagfile_dic_values = []
for b in played_bagfile_dic.keys():
played_bagfile_dic_keys.append(b)
played_bagfile_dic_values.append(played_bagfile_dic[b])
indicies = [i[0] for i in sorted(enumerate(played_bagfile_dic_values),key=lambda x:x[1])]
indicies.reverse()
ctr = 0
for i in indicies:
if ctr >= 25:
break
bf = played_bagfile_dic_keys[i]
if bf in loaded_bag_files_names:
#bf = a_key(loaded_bag_files_names)
cprint('THREAD:: deleting '+bf,'blue','on_red')
r = loaded_bag_files_names[bf]
loaded_bag_files_names.pop(bf)
BF = BF_dic[r]
BF['bag_file_image_data'].pop(bf)
ctr += 1
try:
r = random.choice(BF_dic.keys())
BF = BF_dic[r]
dic_keys = ['bag_file_image_data','good_bag_timestamps','binned_timestamps','binned_steers','bid_timestamps']
for dk in dic_keys:
if dk not in BF:
BF[dk] = {}
bf = random.choice(BF['bag_file_num_dic'])
if bf in BF['bag_file_image_data']:
continue
BF['bag_file_image_data'][bf] = Bag_File.load_images(bf,color_mode="rgb8",include_flip=True)
loaded_bag_files_names[bf] = r
bid = BF['bag_file_image_data'][bf]
bag_left_timestamps = sorted(bid['left'].keys())
good_bag_timestamps = list(set(BF['data']['good_start_timestamps']) & set(bag_left_timestamps))
cprint(d2s('THREAD:: ',bf.split('/')[-1],'len(good_bag_timestamps) =',len(good_bag_timestamps)),'blue')
binned_timestamps = [[],[]]
binned_steers = [[],[]]
for t in good_bag_timestamps:
steer = BF['left_image_bound_to_data'][t]['steer']
if steer < 43 or steer > 55:
binned_timestamps[0].append(t)
binned_steers[0].append(steer)
else:
binned_timestamps[1].append(t)
binned_steers[1].append(steer)
BF['good_bag_timestamps'][bf] = good_bag_timestamps
BF['binned_timestamps'][bf] = binned_timestamps
BF['binned_steers'][bf] = binned_steers
BF['bid_timestamps'][bf] = sorted(bid['left'].keys())
except Exception as e:
cprint("THREAD:: ********** Exception ***********************",'red')
print(e.message, e.args)
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')
good_bag_timestamps = list(set(BF['data']['good_start_timestamps']) & set(bag_left_timestamps))
plot(good_bag_timestamps,2000+np.zeros(len(good_bag_timestamps)),'ro')
ts = sorted(bid['left'].keys())
for t in ts:
mi(bid['left'][t],'left')
#mi(bid['right'][BF['left_image_bound_to_data'][t]['right_image']],'right')
plt.pause(0.0001)
plot(BF['data']['steer'],BF['data']['gyro_y'],'o')
