tfrecord type looks like txt or image











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I'm generating tfrecords of BDD dataset from a 20000 subset. While creating tfrecords I choose 1000 images per tfrecord, and everything is fine.



However if I choose 500 images per tfrecord, some of them (very rare) have type TGA image (image/x-tga) or MATLAB script/function (text/x-matlab) while normally they should have had Program (application/octet-stream) or Binary (application/octet-stream).



Why would this happen, and does it mean the tfrecords are broken?



feature = self._get_tf_feature(

                   picture_id, os.path.join(full_images_path, f),

                   m.group(2), picture_id_annotations, new_format)

example = tf.train.Example(features=feature)

writer.write(example.SerializeToString())





python-3.x tensorflow tfrecord







share|improve this question
























  • From the code snippet above it's not totally clear how the features are generated. But probably this problem has nothing to do with tfrecord format, because this format just stores the data. That means, that the data, which you provide while generating tfrecords are "wrong" - incorrect image type. Maybe it's worthy to check source images itself.
    – Vlad-HC
    11 hours ago










  • I was thinking the same, but I have a flag for elements per tfrecord, and I only change the number without changing the the way I get the features. Since the records are fine with 1000 samples each, I don't think the problem is caused by the features..
    – kneazle
    11 hours ago















up vote
0
down vote

favorite












I'm generating tfrecords of BDD dataset from a 20000 subset. While creating tfrecords I choose 1000 images per tfrecord, and everything is fine.



However if I choose 500 images per tfrecord, some of them (very rare) have type TGA image (image/x-tga) or MATLAB script/function (text/x-matlab) while normally they should have had Program (application/octet-stream) or Binary (application/octet-stream).



Why would this happen, and does it mean the tfrecords are broken?



feature = self._get_tf_feature(

                   picture_id, os.path.join(full_images_path, f),

                   m.group(2), picture_id_annotations, new_format)

example = tf.train.Example(features=feature)

writer.write(example.SerializeToString())





python-3.x tensorflow tfrecord







share|improve this question
























  • From the code snippet above it's not totally clear how the features are generated. But probably this problem has nothing to do with tfrecord format, because this format just stores the data. That means, that the data, which you provide while generating tfrecords are "wrong" - incorrect image type. Maybe it's worthy to check source images itself.
    – Vlad-HC
    11 hours ago










  • I was thinking the same, but I have a flag for elements per tfrecord, and I only change the number without changing the the way I get the features. Since the records are fine with 1000 samples each, I don't think the problem is caused by the features..
    – kneazle
    11 hours ago













up vote
0
down vote

favorite









up vote
0
down vote

favorite











I'm generating tfrecords of BDD dataset from a 20000 subset. While creating tfrecords I choose 1000 images per tfrecord, and everything is fine.



However if I choose 500 images per tfrecord, some of them (very rare) have type TGA image (image/x-tga) or MATLAB script/function (text/x-matlab) while normally they should have had Program (application/octet-stream) or Binary (application/octet-stream).



Why would this happen, and does it mean the tfrecords are broken?



feature = self._get_tf_feature(

                   picture_id, os.path.join(full_images_path, f),

                   m.group(2), picture_id_annotations, new_format)

example = tf.train.Example(features=feature)

writer.write(example.SerializeToString())





python-3.x tensorflow tfrecord







share|improve this question















I'm generating tfrecords of BDD dataset from a 20000 subset. While creating tfrecords I choose 1000 images per tfrecord, and everything is fine.



However if I choose 500 images per tfrecord, some of them (very rare) have type TGA image (image/x-tga) or MATLAB script/function (text/x-matlab) while normally they should have had Program (application/octet-stream) or Binary (application/octet-stream).



Why would this happen, and does it mean the tfrecords are broken?



feature = self._get_tf_feature(

                   picture_id, os.path.join(full_images_path, f),

                   m.group(2), picture_id_annotations, new_format)

example = tf.train.Example(features=feature)

writer.write(example.SerializeToString())





python-3.x tensorflow tfrecord




python-3.x tensorflow tfrecord






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited 11 hours ago









Vlad-HC

627711




627711










asked 11 hours ago









kneazle

166




166












  • From the code snippet above it's not totally clear how the features are generated. But probably this problem has nothing to do with tfrecord format, because this format just stores the data. That means, that the data, which you provide while generating tfrecords are "wrong" - incorrect image type. Maybe it's worthy to check source images itself.
    – Vlad-HC
    11 hours ago










  • I was thinking the same, but I have a flag for elements per tfrecord, and I only change the number without changing the the way I get the features. Since the records are fine with 1000 samples each, I don't think the problem is caused by the features..
    – kneazle
    11 hours ago


















  • From the code snippet above it's not totally clear how the features are generated. But probably this problem has nothing to do with tfrecord format, because this format just stores the data. That means, that the data, which you provide while generating tfrecords are "wrong" - incorrect image type. Maybe it's worthy to check source images itself.
    – Vlad-HC
    11 hours ago










  • I was thinking the same, but I have a flag for elements per tfrecord, and I only change the number without changing the the way I get the features. Since the records are fine with 1000 samples each, I don't think the problem is caused by the features..
    – kneazle
    11 hours ago
















From the code snippet above it's not totally clear how the features are generated. But probably this problem has nothing to do with tfrecord format, because this format just stores the data. That means, that the data, which you provide while generating tfrecords are "wrong" - incorrect image type. Maybe it's worthy to check source images itself.
– Vlad-HC
11 hours ago




From the code snippet above it's not totally clear how the features are generated. But probably this problem has nothing to do with tfrecord format, because this format just stores the data. That means, that the data, which you provide while generating tfrecords are "wrong" - incorrect image type. Maybe it's worthy to check source images itself.
– Vlad-HC
11 hours ago












I was thinking the same, but I have a flag for elements per tfrecord, and I only change the number without changing the the way I get the features. Since the records are fine with 1000 samples each, I don't think the problem is caused by the features..
– kneazle
11 hours ago




I was thinking the same, but I have a flag for elements per tfrecord, and I only change the number without changing the the way I get the features. Since the records are fine with 1000 samples each, I don't think the problem is caused by the features..
– kneazle
11 hours ago

















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