Indicates that the.npz file cannot be found

[1301358882]

Hello, when I was training 1_train_xe.sh, there was no error 446093.npz, how can I solve this problem? Previous address path... /open_source_dataset/mscoco_dataset/features/up_down The data can be queried.

[lph223]

May I ask if your problem has been resolved？

[1301358882]

May I ask if your problem has been resolved？

just do the python tools/create_feats.py operation for each.tsv

[lph223]

运行create_feats.py文件报错，请问这个问题怎么解决 tools/create_feats.py:27: DeprecationWarning: decodestring() is a deprecated alias since Python 3.1, use decodebytes() item[field] = np.frombuffer(base64.decodestring(bytes(item[field], 'utf-8')), Traceback (most recent call last): File "tools/create_feats.py", line 41, in main(args) File "tools/create_feats.py", line 32, in main np.savez_compressed(os.path.join(args.outfolder, str(image_id)), feat=feats) File "<array_function internals>", line 5, in savez_compressed File "/root/miniconda3/lib/python3.8/site-packages/numpy/lib/npyio.py", line 689, in savez_compressed _savez(file, args, kwds, True) File "/root/miniconda3/lib/python3.8/site-packages/numpy/lib/npyio.py", line 715, in _savez zipf = zipfile_factory(file, mode="w", compression=compression) File "/root/miniconda3/lib/python3.8/site-packages/numpy/lib/npyio.py", line 112, in zipfile_factory return zipfile.ZipFile(file, *args, **kwargs) File "/root/miniconda3/lib/python3.8/zipfile.py", line 1251, in init self.fp = io.open(file, filemode) FileNotFoundError: [Errno 2] No such file or directory: 'open_source_dataset/mscoco_dataset/feature/up_down_10_100/524881.npz

[1301358882]

运行create_feats.py文件报错，请问这个问题怎么解决 tools/create_feats.py:27: DeprecationWarning: decodestring() is a deprecated alias since Python 3.1, use decodebytes() item[field] = np.frombuffer(base64.decodestring(bytes(item[field], 'utf-8')), Traceback (most recent call last): File "tools/create_feats.py", line 41, in main(args) File "tools/create_feats.py", line 32, in main np.savez_compressed(os.path.join(args.outfolder, str(image_id)), feat=feats) File "<array_function internals>", line 5, in savez_compressed File "/root/miniconda3/lib/python3.8/site-packages/numpy/lib/npyio.py", line 689, in savez_compressed _savez(file, args, kwds, True) File "/root/miniconda3/lib/python3.8/site-packages/numpy/lib/npyio.py", line 715, in _savez zipf = zipfile_factory(file, mode="w", compression=compression) File "/root/miniconda3/lib/python3.8/site-packages/numpy/lib/npyio.py", line 112, in zipfile_factory return zipfile.ZipFile(file, *args, **kwargs) File "/root/miniconda3/lib/python3.8/zipfile.py", line 1251, in init self.fp = io.open(file, filemode) FileNotFoundError: [Errno 2] No such file or directory: 'open_source_dataset/mscoco_dataset/feature/up_down_10_100/524881.npz

item[field] = np.frombuffer(base64.decodebytes(bytes(item[field],encoding="utf8")) I did make some changes here.

[lph223]

Do other areas still need to be modified

[1301358882]

Do other areas still need to be modified

The data address needs to be changed, you can look at the code

[lph223]

Traceback (most recent call last): File "tools/create_feats.py", line 39, in main(args) File "tools/create_feats.py", line 15, in main for item in reader: File "/root/miniconda3/lib/python3.8/csv.py", line 111, in next row = next(self.reader) _csv.Error: iterator should return strings, not bytes (did you open the file in text mode?)

def main(args):
count = 0 with open(args.infeats, "r+b") as tsv_in_file: reader = csv.DictReader(tsv_in_file, delimiter='\t', fieldnames = FIELDNAMES) for item in reader: if count % 1000 == 0: print(count) count += 1

        item['image_id'] = int(item['image_id'])
        item['image_h'] = int(item['image_h'])
        item['image_w'] = int(item['image_w'])
        item['num_boxes'] = int(item['num_boxes'])
        for field in ['boxes', 'features']:
            item[field] = np.frombuffer(base64.decodebytes(bytes(item[field], 'utf-8')),
                    dtype=np.float32).reshape((item['num_boxes'],-1))
        image_id = item['image_id']                    
        
        feats = item['features']
        np.savez_compressed(os.path.join(args.outfolder, str(image_id)), feat=feats)
        

if name == "main": parser = argparse.ArgumentParser()

parser.add_argument('--infeats', default='trainval/karpathy_train_resnet101_faster_rcnn_genome.tsv.0', help='image features')
parser.add_argument('--outfolder', default='open_source_dataset/mscoco_dataset/feature/up_down', help='output folder')

args = parser.parse_args()
main(args)