def get_cluster_faces():
params = request.get_json()
db.connect(os.path.join(params['data_dir'], params['dbfile']), args.debug)
res = db.get_cluster_faces(**params)
db.close()
return jsonify(res)
def compute_similarities():
params = request.get_json()
start_time = time.time()
db.connect(os.path.join(params['data_dir'], params['dbfile']), args.debug)
num_faces, num_similarities, num_clusters = faceid.compute_similarities(
**params)
db.close()
elapsed = time.time() - start_time
res = {
'num_similarities': num_similarities,
'num_clusters': num_clusters,
'num_faces': num_faces,
'elapsed': elapsed
}
return jsonify(res)
def scan():
params = request.get_json()
data_dir = params['data_dir']
dbfile = params['dbfile']
source = params['source']
files = params['files']
if faceid.args.save_resized:
faceid.makedirs(os.path.join(data_dir, faceid.args.save_resized))
if faceid.args.save_faces:
faceid.makedirs(os.path.join(data_dir, faceid.args.save_faces))
start_time = time.time()
db.connect(os.path.join(data_dir, dbfile), args.debug)
num_files = 0
num_images = 0
num_faces = 0
results = []
for file in files:
relpath = file['relpath']
del file['relpath']
file_images, file_faces, res = faceid.process_file(
data_dir, relpath, source, **file)
num_files += 1
num_images += file_images
num_faces += file_faces
results += res
db.close()
elapsed = time.time() - start_time
res = {
'num_files': num_files,
'num_images': num_images,
'num_faces': num_faces,
'elapsed': elapsed,
'images_per_s': num_images / elapsed,
'files': results
}
return jsonify(res)