def run_train_test(seed_image_id,
filedata,
max_value_cutoff,
test_id,
multi_image_training=False):
create_single_lmdb(seed_image_id, filedata, test_id, multi_image_training)
for test_id in range(0, test_id + 1):
create_test_script(seed_image_id, test_id, multi_image_training)
run_script(train_dir + str(seed_image_id) + '/train-single-coin-lmdbs.sh')
run_script(test_dir + str(test_id) + '/test-' + str(seed_image_id) + '.sh')
read_test([seed_image_id], test_id)
# in the metadata dir rm *.png
image_set.read_results(max_value_cutoff, data_dir, [seed_image_id])
def link_seed_by_graph(seed_id, cut_off, min_connections, max_depth):
image_set.read_results(cut_off, data_dir, seeds_share_test_images=False, remove_widened_seeds=True)
image_set.save_widened_seeds(data_dir, seed_id, cut_off)
image_set.read_results(cut_off, data_dir, seeds_share_test_images=True, remove_widened_seeds=True)
save_graph()
most_connected_seeds = image_set.find_most_connected_seeds(data_dir, seed_id, min_connections, max_depth)
filedata = []
if len(most_connected_seeds) != 0:
# image_set.create_composite_image(crop_dir, data_dir, 130, 30, 10, most_connected_seeds.iterkeys())
for seed_image_id, values in most_connected_seeds.iteritems():
print values
filedata.append([seed_image_id, crop_dir + str(seed_image_id) + '.png', values[2]])
print 'Count of images linked by graph:', len(most_connected_seeds)
image_set.create_composite_image_from_filedata(crop_dir, data_dir, 140, rows=150, cols=10, filedata=filedata)
if len(filedata) > 9:
run_train_test(seed_id, filedata, cut_off, test_id=5, multi_image_training=True)
run_test(seed_id, cut_off, test_id=5)
read_all_results(cut_off)
else:
print 'Not enough seeds found'
def read_all_results(cut_off=0,
seed_image_ids=None,
seeds_share_test_images=True,
remove_widened_seeds=False):
image_set.read_results(cut_off, data_dir, seed_image_ids,
seeds_share_test_images, remove_widened_seeds)
def run_test(seed_image_id, max_value_cutoff, test_id):
for test_id in range(0, test_id + 1):
run_script(test_dir + str(test_id) + '/test-' + str(seed_image_id) +
'.sh')
read_test([seed_image_id], test_id)
image_set.read_results(max_value_cutoff, data_dir, [seed_image_id])
# seed_images = seed_image_data[int(seed_image_id / 100)]
# for image_id in seed_images:
# test_image_id = seed_image_id + image_id
# filedata.append([test_image_id, crop_dir + str(test_image_id) + '.png', 0])
# # # the test_id = 5 just adds more data for now:
# # create_single_lmdb(seed_image_id, filedata, 0, True, 700)
# # run_script(train_dir + str(seed_image_id) + '/train-single-coin-lmdbs.sh')
# create_test_script(seed_image_id, 0, True)
# scripts_to_run.append(test_dir + str(0) + '/test-' + str(seed_image_id) + '.sh')
# #run_script(test_dir + str(0) + '/test-' + str(seed_image_id) + '.sh')
# run_scripts(scripts_to_run,max_workers=6)
#
# read_test(seed_image_ids, 360)
# image_set.read_results(0, data_dir, seeds_share_test_images=False, bad_coin_ids=bad_coin_ids, ground_truth=ground_truth)
image_set.read_results(0, data_dir, seeds_share_test_images=False)
multi_point_error_test_image_ids = get_multi_point_error_test_image_ids()
print 'The following test_image_ids where taking out of the image:'
print multi_point_error_test_image_ids
print 'multi_point_error_test_image_ids length:' + str(
len(multi_point_error_test_image_ids))
image_set.create_composite_images(crop_dir, data_dir, 125, 40, 10, None,
multi_point_error_test_image_ids, True)
#image_set.create_composite_images(crop_dir, data_dir, 125, 40, 10, None, multi_point_error_test_image_ids, True)
#image_set.create_composite_image(crop_dir, data_dir, 140, 100, 10, multi_point_error_test_image_ids)
print 'Done in %s seconds' % (time.time() - start_time, )
sys.exit("End")
# ********
# Step 2:
def run_multi_point():
init_dir()
start_time = time.time()
test_image_ids = []
new_test_image_ids = []
new_seed_image_ids = []
count = 0
seed_image_ids = pickle.load(open(data_dir + 'seed_image_ids_all.pickle', "rb"))
for coin_id in seed_image_ids:
if (count < 99999999) and (coin_id % 2 == 0):
new_seed_image_ids.append(coin_id * 100)
new_seed_image_ids.append((coin_id +3) * 100)
for image_id in range(0,57):
new_test_image_ids.append(coin_id * 100 + image_id)
new_test_image_ids.append((coin_id +3) * 100 + image_id)
count += 2
test_image_ids = sorted(new_test_image_ids)
#seed_image_ids = sorted(new_seed_image_ids)
#pickle.dump(seed_image_ids, open(data_dir + 'seed_image_ids.pickle', "wb"))
pickle.dump(test_image_ids, open(data_dir + 'test_image_ids.pickle', "wb"))
#save_multi_point_ids()
seed_image_data = pickle.load(open(data_dir + 'multi_point_ids.pickle', "rb"))
seed_image_ids = (200,1100)
scripts_to_run = []
images_per_angle = 200
#seed_image_ids = pickle.load(open(data_dir + 'seed_image_ids.pickle', "rb"))
#test_image_ids = pickle.load(open(data_dir + 'seed_image_ids.pickle', "rb"))
#create_test_lmdb_batches(test_image_ids,seed_image_ids,1)
test_batch_ids = []
for test_image_id in test_image_ids:
test_batch_id = test_image_id / 1000
if test_batch_id not in test_batch_ids:
test_batch_ids.append(test_batch_id)
for seed_image_id in seed_image_ids:
pass
# filedata = []
# seed_images = seed_image_data[int(seed_image_id / 100)]
# for image_id in seed_images:
# test_image_id = seed_image_id + image_id
# filename = get_filename_from(test_image_id)
# filedata.append([test_image_id, filename, 0])
#create_single_lmdb(seed_image_id, filedata, 0, True, images_per_angle)
#run_script(train_dir + str(seed_image_id) + '/train-single-coin-lmdbs.sh')
# for test_batch_id in test_batch_ids:
# filename = test_dir + str(test_batch_id) + '/' + str(seed_image_id) + '.dat'
# if os.path.isfile(filename):
# file_size = os.path.getsize(filename)
# if file_size > 0:
# print 'Exists:', filename
# continue
# create_test_script(seed_image_id,test_batch_id,True)
# scripts_to_run.append(test_dir + str(test_batch_id) + '/test-' + str(seed_image_id) + '.sh')
#
# run_scripts(scripts_to_run,max_workers=6)
#read_test(test_batch_ids,seed_image_ids)
# ********
# Step 2:
# Then widen the seed to include all crops in all results for each seed:
# Check out the results in the png
# Note the cutoff
# This should be changed to include the step 3 double check
# for seed_image_id in widen_seed_image_ids:
# cutoff = 13
# filedata = get_single_lmdb_multi_point_filedata(seed_image_id, cutoff, multi_point_error_test_image_ids)
# create_single_lmdb(seed_image_id, filedata, 0, True, 2800, retraining=True)
# run_script(train_dir + str(seed_image_id) + '/train-single-coin-lmdbs.sh')
# run_script(test_dir + str(0) + '/test-' + str(seed_image_id) + '.sh')
# read_test(seed_image_ids, 360)
# # image_set.read_results(0, data_dir, seeds_share_test_images=False, bad_coin_ids=bad_coin_ids, ground_truth=ground_truth)
# image_set.read_results(0, data_dir, seeds_share_test_images=False)
# multi_point_error_test_image_ids = get_multi_point_error_test_image_ids()
# print 'The following test_image_ids where taking out of the image:'
# print multi_point_error_test_image_ids
# print 'multi_point_error_test_image_ids length:' + str(len(multi_point_error_test_image_ids))
# image_set.create_composite_images(crop_dir, data_dir, 125, 40, 10, None, multi_point_error_test_image_ids, True)
# #image_set.create_composite_images(crop_dir, data_dir, 125, 40, 10)
#Dates ************************************************************************************
# filename = data_dir + 'good_coin_ids.pickle'
# if os.path.exists(filename):
# good_coin_ids = set(pickle.load(open(filename, "rb")))
# image_set.read_results(0, data_dir, seeds_share_test_images=False,remove_coin_ids=good_coin_ids)
image_set.read_results(0, data_dir, seeds_share_test_images=False)
multi_point_error_test_image_ids, coin_angles,total_coin_results = get_errors_and_angles(False)
print total_coin_results
# Create a composite image for dates:
#save_good_test_ids is not correct this needs a database:
#image_set.save_good_test_ids(data_dir, 1100,0,multi_point_error_test_image_ids)#image_set.save_good_test_ids(data_dir, 200,31.4,multi_point_error_test_image_ids)
#image_set.create_composite_images(crop_dir, data_dir, 125, 40, 10, None, multi_point_error_test_image_ids, True)
#image_set.create_composite_images(crop_dir, data_dir, 125, 40, 10, None,[], True)
ground_truth_designs = get_ground_truth_designs(total_coin_results,for_dates=False)
#image_set.create_composite_image_ground_truth_designs(crop_dir, data_dir, 125, 50, 10,coin_angles,ground_truth_designs,False,True,True)
image_set.create_date_composite_image(crop_dir, data_dir, 1100, 200000, coin_angles,ground_truth_designs,False,True)