def process(options, collection, features):
rootpath = options.rootpath
blocksize = options.blocksize
newfeature = options.newfeature
src_features = features.split(',')
if not newfeature:
newfeature = '+'.join(src_features)
new_feat_dir = os.path.join(rootpath, collection, 'FeatureData', newfeature)
new_feat_file = os.path.join(new_feat_dir, 'feature.bin')
if checkToSkip(new_feat_file, options.overwrite):
return 0
imset = readImageSet(collection, collection, rootpath)
nr_to_read = len(imset) / blocksize
if blocksize*nr_to_read < len(imset):
nr_to_read += 1
src_feat_files = [BigFile(os.path.join(rootpath, collection,'FeatureData',feature)) for feature in src_features]
nr_fea = len(src_feat_files)
src_feat_dims = [x.ndims for x in src_feat_files]
new_feat_dim = sum(src_feat_dims)
printStatus(INFO, '%s -> %s,%d' % (' '.join(['(%s,%d)' % (x[0],x[1]) for x in zip(src_features,src_feat_dims)]), newfeature, new_feat_dim))
makedirsforfile(new_feat_file)
fw = open(new_feat_file, 'wb')
id_images = []
for t in range(nr_to_read):
start = t*blocksize
end = min(len(imset), start + blocksize)
printStatus(INFO, 'processing images from %d to %d' % (start, end-1))
todo = imset[start:end]
nr_images = len(todo)
if nr_images == 0:
break
mapping = dict(zip(todo, range(nr_images)))
renamed = [None] * nr_fea
vectors = [None] * nr_fea
for i in range(nr_fea):
tmp_names, tmp_vecs = src_feat_files[i].read(todo)
assert(len(tmp_names) == nr_images)
renamed[i] = [None] * nr_images
vectors[i] = [None] * nr_images
for name,vec in zip(tmp_names, tmp_vecs):
j = mapping[name]
renamed[i][j] = name
vectors[i][j] = vec
for j in range(nr_images):
new_vec = vectors[0][j]
for i in range(1,nr_fea):
assert (renamed[i-1][j] == renamed[i][j]), '%s %s' % (renamed[i-1][j], renamed[i][j])
new_vec += vectors[i][j]
assert(len(new_vec) == new_feat_dim)
name = renamed[0][j]
np.array(new_vec, dtype=np.float32).tofile(fw)
id_images.append(name)
fw.close()
new_id_file = os.path.join(new_feat_dir, 'id.txt')
fw = open(new_id_file, 'w')
fw.write(' '.join(id_images))
fw.close()
fw = open(os.path.join(new_feat_dir,'shape.txt'), 'w')
fw.write('%d %d' % (len(id_images), new_feat_dim))
fw.close()
dstCollection = args[2]
overwrite = 0
concepts = readConcepts(srcCollection, annotationName, rootpath)
todo = []
for concept in concepts:
resfile = os.path.join(rootpath, dstCollection, 'Annotations', 'Image',
annotationName, '%s.txt' % concept)
if checkToSkip(resfile, overwrite):
continue
todo.append(concept)
if not todo:
print('nothing to do')
sys.exit(0)
imset = set(readImageSet(dstCollection, dstCollection, rootpath))
for concept in todo:
names, labels = readAnnotationsFrom(srcCollection,
annotationName,
concept,
rootpath=rootpath)
selected = [x for x in zip(names, labels) if x[0] in imset]
print concept, len(selected)
writeAnnotationsTo([x[0] for x in selected], [x[1] for x in selected],
dstCollection,
annotationName,
concept,
rootpath=rootpath)
writeConceptsTo(concepts, dstCollection, annotationName, rootpath)
if __name__ == '__main__':
args = sys.argv[1:]
rootpath = '/var/scratch2/xirong/VisualSearch'
srcCollection = args[0]
annotationName = args[1]
dstCollection = args[2]
overwrite = 0
concepts = readConcepts(srcCollection, annotationName, rootpath)
todo = []
for concept in concepts:
resfile = os.path.join(rootpath, dstCollection, 'Annotations', 'Image', annotationName, '%s.txt'%concept)
if checkToSkip(resfile, overwrite):
continue
todo.append(concept)
if not todo:
print ('nothing to do')
sys.exit(0)
imset = set(readImageSet(dstCollection, dstCollection, rootpath))
for concept in todo:
names,labels = readAnnotationsFrom(srcCollection, annotationName, concept, rootpath=rootpath)
selected = [x for x in zip(names,labels) if x[0] in imset]
print concept, len(selected)
writeAnnotationsTo([x[0] for x in selected], [x[1] for x in selected], dstCollection, annotationName, concept, rootpath=rootpath)
writeConceptsTo(concepts, dstCollection, annotationName, rootpath)
def process(options, collection, features):
rootpath = options.rootpath
blocksize = options.blocksize
newfeature = options.newfeature
src_features = features.split(',')
if not newfeature:
newfeature = '+'.join(src_features)
new_feat_dir = os.path.join(rootpath, collection, 'FeatureData',
newfeature)
new_feat_file = os.path.join(new_feat_dir, 'feature.bin')
if checkToSkip(new_feat_file, options.overwrite):
return 0
imset = readImageSet(collection, collection, rootpath)
nr_to_read = len(imset) / blocksize
if blocksize * nr_to_read < len(imset):
nr_to_read += 1
src_feat_files = [
BigFile(os.path.join(rootpath, collection, 'FeatureData', feature))
for feature in src_features
]
nr_fea = len(src_feat_files)
src_feat_dims = [x.ndims for x in src_feat_files]
new_feat_dim = sum(src_feat_dims)
printStatus(
INFO, '%s -> %s,%d' % (' '.join([
'(%s,%d)' % (x[0], x[1]) for x in zip(src_features, src_feat_dims)
]), newfeature, new_feat_dim))
makedirsforfile(new_feat_file)
fw = open(new_feat_file, 'wb')
id_images = []
for t in range(nr_to_read):
start = t * blocksize
end = min(len(imset), start + blocksize)
printStatus(INFO, 'processing images from %d to %d' % (start, end - 1))
todo = imset[start:end]
nr_images = len(todo)
if nr_images == 0:
break
mapping = dict(zip(todo, range(nr_images)))
renamed = [None] * nr_fea
vectors = [None] * nr_fea
for i in range(nr_fea):
tmp_names, tmp_vecs = src_feat_files[i].read(todo)
assert (len(tmp_names) == nr_images)
renamed[i] = [None] * nr_images
vectors[i] = [None] * nr_images
for name, vec in zip(tmp_names, tmp_vecs):
j = mapping[name]
renamed[i][j] = name
vectors[i][j] = vec
for j in range(nr_images):
new_vec = vectors[0][j]
for i in range(1, nr_fea):
assert (renamed[i - 1][j] == renamed[i][j]
), '%s %s' % (renamed[i - 1][j], renamed[i][j])
new_vec += vectors[i][j]
assert (len(new_vec) == new_feat_dim)
name = renamed[0][j]
np.array(new_vec, dtype=np.float32).tofile(fw)
id_images.append(name)
fw.close()
new_id_file = os.path.join(new_feat_dir, 'id.txt')
fw = open(new_id_file, 'w')
fw.write(' '.join(id_images))
fw.close()
fw = open(os.path.join(new_feat_dir, 'shape.txt'), 'w')
fw.write('%d %d' % (len(id_images), new_feat_dim))
fw.close()
