def meta_script_saveNpzScorePerShot_normalized(params,out_dir_scores,out_dir_actual):
mani=TubeHash_Manipulator(params['path_to_db']);
mani.openSession();
vals=mani.select((Tube.class_idx_pascal,Tube.video_id,Tube.shot_id),distinct=True);
mani.closeSession()
print len(vals)
args=[];
for idx,(class_idx,video_id,shot_id) in enumerate(vals):
params_curr = copy.deepcopy(params);
params_curr['class_idx'] = class_idx
params_curr['video_id'] = video_id
params_curr['shot_id'] = shot_id
file_curr = str(params_curr['class_idx'])+'_'+str(params_curr['video_id'])+'_'+str(params_curr['shot_id'])+'.p';
params_curr['out_file_scores'] = os.path.join(out_dir_scores,file_curr)
params_curr['idx'] = idx;
if os.path.exists(params_curr['out_file_scores']):
# continue;
# else:
params_curr['out_file_scores']=os.path.join(out_dir_actual,file_curr)
args.append(params_curr);
print len(args)
# args=args[3000:];
print len(args)
n_jobs=12
p = multiprocessing.Pool(min(multiprocessing.cpu_count(),n_jobs))
p.map(script_saveNpzScorePerShot_normalized,args);
def getScoreForIdx(table_idx,
path_to_db,
class_idx_pascal=None,
npz_path=None,
n_jobs=1,
total_counts=None):
mani = Tube_Manipulator(path_to_db)
mani.openSession()
mani_hash = TubeHash_Manipulator(path_to_db)
mani_hash.openSession()
toSelect = (Tube.class_idx_pascal, Tube.video_id, Tube.img_path)
criterion = (Tube.idx == table_idx, )
[(class_idx_gt, video_idx, frame_path)] = mani.select(toSelect, criterion)
if class_idx_pascal is not None:
class_idx = class_idx_pascal
else:
class_idx = class_idx_gt
toSelect = (TubeHash.hash_table, TubeHash.hash_val)
criterion = (TubeHash.idx == table_idx, )
hash_table_info = mani_hash.select(toSelect, criterion)
print len(hash_table_info)
mani_hash.closeSession()
mani.closeSession()
args = []
for hash_table_no in range(len(hash_table_info)):
hash_table = hash_table_info[hash_table_no][0]
hash_val = hash_table_info[hash_table_no][1]
if npz_path is not None:
args.append((npz_path, hash_table, hash_val, class_idx, video_idx,
class_idx_gt, total_counts))
else:
args.append((path_to_db, hash_table, hash_val, class_idx,
video_idx, class_idx_gt))
if n_jobs > 1:
p = multiprocessing.Pool(min(multiprocessing.cpu_count(), n_jobs))
if npz_path is not None:
scores = p.map(getScoreForHashValFromNpz, args)
else:
scores = p.map(getScoreForHashVal, args)
else:
scores = []
for arg in args:
if npz_path is not None:
scores.append(getScoreForHashValFromNpz(arg))
else:
scores.append(getScoreForHashVal(arg))
return scores, class_idx_gt, frame_path
def getScoreForIdx(table_idx,path_to_db,class_idx_pascal=None,npz_path=None,n_jobs=1,total_counts=None):
mani=Tube_Manipulator(path_to_db);
mani.openSession();
mani_hash=TubeHash_Manipulator(path_to_db);
mani_hash.openSession();
toSelect = (Tube.class_idx_pascal,Tube.video_id,Tube.img_path)
criterion = (Tube.idx==table_idx,);
[(class_idx_gt,video_idx,frame_path)] = mani.select(toSelect,criterion)
if class_idx_pascal is not None:
class_idx=class_idx_pascal;
else:
class_idx=class_idx_gt
toSelect=(TubeHash.hash_table,TubeHash.hash_val);
criterion=(TubeHash.idx==table_idx,)
hash_table_info=mani_hash.select(toSelect,criterion);
print len(hash_table_info);
mani_hash.closeSession();
mani.closeSession();
args=[];
for hash_table_no in range(len(hash_table_info)):
hash_table=hash_table_info[hash_table_no][0];
hash_val=hash_table_info[hash_table_no][1];
if npz_path is not None:
args.append((npz_path,hash_table,hash_val,class_idx,video_idx,class_idx_gt,total_counts));
else:
args.append((path_to_db,hash_table,hash_val,class_idx,video_idx,class_idx_gt));
if n_jobs>1:
p = multiprocessing.Pool(min(multiprocessing.cpu_count(),n_jobs))
if npz_path is not None:
scores=p.map(getScoreForHashValFromNpz,args)
else:
scores=p.map(getScoreForHashVal,args)
else:
scores=[];
for arg in args:
if npz_path is not None:
scores.append(getScoreForHashValFromNpz(arg));
else:
scores.append(getScoreForHashVal(arg));
return scores,class_idx_gt,frame_path
def getHashInfoForImg(path_to_db,img_path):
mani=Tube_Manipulator(path_to_db);
mani.openSession();
#get patch id
patch_id=mani.select((Tube.idx,),(Tube.img_path==img_path,));
assert len(patch_id)==1;
patch_id=patch_id[0][0];
mani.closeSession();
#get hash vals
mani_hash=TubeHash_Manipulator(path_to_db);
mani_hash.openSession();
toSelect=(TubeHash.hash_table,TubeHash.hash_val)
criterion=(TubeHash.idx==patch_id,);
hash_info_patch=mani_hash.select(toSelect,criterion);
mani_hash.closeSession();
return hash_info_patch
def getHashInfoForImg(path_to_db, img_path):
mani = Tube_Manipulator(path_to_db)
mani.openSession()
#get patch id
patch_id = mani.select((Tube.idx, ), (Tube.img_path == img_path, ))
assert len(patch_id) == 1
patch_id = patch_id[0][0]
mani.closeSession()
#get hash vals
mani_hash = TubeHash_Manipulator(path_to_db)
mani_hash.openSession()
toSelect = (TubeHash.hash_table, TubeHash.hash_val)
criterion = (TubeHash.idx == patch_id, )
hash_info_patch = mani_hash.select(toSelect, criterion)
mani_hash.closeSession()
return hash_info_patch
def script_saveHashTableDensities(hash_table, path_to_db, out_file):
mani_hash = TubeHash_Manipulator(path_to_db)
mani_hash.openSession()
toSelect = (TubeHash.hash_val, )
criterion = (TubeHash.hash_table == hash_table, )
hash_vals = mani_hash.select(toSelect, criterion)
mani_hash.closeSession()
hash_vals = [hash_val[0] for hash_val in hash_vals]
hash_vals = np.array(hash_vals, dtype=np.uint8)
hash_dict = {}
for val_curr in np.unique(hash_vals):
hash_dict[val_curr] = (hash_vals == val_curr).sum()
pickle.dump(hash_dict, open(out_file, 'wb'))
def script_saveHashTableDensities(hash_table,path_to_db,out_file):
mani_hash=TubeHash_Manipulator(path_to_db);
mani_hash.openSession();
toSelect=(TubeHash.hash_val,);
criterion=(TubeHash.hash_table==hash_table,);
hash_vals=mani_hash.select(toSelect,criterion);
mani_hash.closeSession();
hash_vals=[hash_val[0] for hash_val in hash_vals];
hash_vals=np.array(hash_vals,dtype=np.uint8);
hash_dict={};
for val_curr in np.unique(hash_vals):
hash_dict[val_curr]=(hash_vals==val_curr).sum();
pickle.dump(hash_dict,open(out_file,'wb'));
def meta_script_saveNpzScorePerShot_normalized(params, out_dir_scores,
out_dir_actual):
mani = TubeHash_Manipulator(params['path_to_db'])
mani.openSession()
vals = mani.select((Tube.class_idx_pascal, Tube.video_id, Tube.shot_id),
distinct=True)
mani.closeSession()
print len(vals)
args = []
for idx, (class_idx, video_id, shot_id) in enumerate(vals):
params_curr = copy.deepcopy(params)
params_curr['class_idx'] = class_idx
params_curr['video_id'] = video_id
params_curr['shot_id'] = shot_id
file_curr = str(params_curr['class_idx']) + '_' + str(
params_curr['video_id']) + '_' + str(params_curr['shot_id']) + '.p'
params_curr['out_file_scores'] = os.path.join(out_dir_scores,
file_curr)
params_curr['idx'] = idx
if os.path.exists(params_curr['out_file_scores']):
# continue;
# else:
params_curr['out_file_scores'] = os.path.join(
out_dir_actual, file_curr)
args.append(params_curr)
print len(args)
# args=args[3000:];
print len(args)
n_jobs = 12
p = multiprocessing.Pool(min(multiprocessing.cpu_count(), n_jobs))
p.map(script_saveNpzScorePerShot_normalized, args)
