def widen_model(seed_image_id, max_test_id, max_value_cutoff):
for test_id in range(0, max_test_id + 1):
for x in range(0, 2):
filedata = get_single_lmdb_filedata(seed_image_id,
max_value_cutoff)
run_train_test(seed_image_id, filedata, max_value_cutoff, test_id)
image_set.create_composite_images(crop_dir, data_dir, 120, 8, 20)
def retrain_widened_seed(seed_image_id, cut_off):
# This did not seem to add much to the model
# usage: retrain_widened_seed(7855,27)
max_value_cutoff = 10
read_all_results(max_value_cutoff, seeds_share_test_images=False, remove_widened_seeds=True)
filedata = get_single_lmdb_filedata(seed_image_id, cut_off)
run_train_test(seed_image_id, filedata, max_value_cutoff, test_id=5,multi_image_training = True)
read_all_results(max_value_cutoff, seeds_share_test_images=False, remove_widened_seeds=True)
image_set.create_composite_images(crop_dir, data_dir, crop_size=140, rows=50, cols=10)
# # 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:
# 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
