def find_threshold(args, filter_string, feature_vector, query_image_id):
data_matrix, image_ids = get_data_matrix(args.model, filter_string)
if args.model == "SIFT":
# Sift needs special hand-holding here, as it is slightly tricky.
max_vector_length = data_matrix.shape[1]
sift_vectors = []
for feature in feature_vector:
if len(sift_vectors) == max_vector_length:
break
sift_vectors.extend(feature)
new_data_matrix = np.append(data_matrix,
np.array(sift_vectors).reshape(
1, len(sift_vectors)),
axis=0)
else:
new_data_matrix = np.append(data_matrix,
np.array(feature_vector).reshape(
1, len(feature_vector)),
axis=0)
image_ids.append(query_image_id)
dimensionality_reduction(new_data_matrix, image_ids, args, args.label)
max_threshold = float("-inf")
for image_id in image_ids:
similar_images = find_similar_images(image_id, args.model,
len(image_ids) - 1, args.label)
distance_score = 0
for similar_image in similar_images:
distance_score += similar_image["distance_score"]
max_threshold = max(max_threshold,
distance_score / (len(image_ids) - 1))
return max_threshold
def main():
parser = setup_arg_parse()
args = parser.parse_args()
populate_database(args)
data_matrix, image_ids = get_data_matrix(args.model)
dimensionality_reduction(data_matrix, image_ids, args, viz=True)
similar_images = find_similar_images(args.query_image, args.model, args.m)
for similar_image in similar_images:
print(similar_image)
plot_results(similar_images, args.image_folder + "/" + args.query_image)
def main():
parser = setup_arg_parse()
args = parser.parse_args()
mongo_client = connect_to_db()
images = list(
mongo_client.mwdb_project.image_features.find({}, {"label": 1}))
mongo_client.close()
if len(images) == 0:
print("Running task3")
filter_string = convert_label_to_filterstring(args.label)
data_matrix, image_ids = get_data_matrix(args.model, filterstring)
dimensionality_reduction(data_matrix, image_ids, args, args.label)
similar_images = find_similar_images(args.query_image, args.model, args.m,
args.label)
for similar_image in similar_images:
print(similar_image)
plot_results(similar_images, args.image_folder + "/" + args.query_image)