| import numpy as np |
| def parse_tfrec(filename): |
| |
| feature = None |
| for raw_record in tf.data.TFRecordDataset(filename): |
| example = tf.train.Example() |
| example.ParseFromString(raw_record.numpy()) |
| feature = example.features.feature |
| |
| return feature |
| |
| def show_info(feature): |
| keys = list(feature.keys()) |
| for k in keys: |
| |
| if feature[k].HasField('bytes_list'): |
| print(k, "bytes_list", feature[k].bytes_list.value) |
| if feature[k].HasField('float_list'): |
| feature_numpy = np.array(feature[k].float_list.value) |
| if len(feature_numpy) == 1: |
| print(k, "float_list", feature_numpy) |
| else: |
| print(k, "float_list",feature_numpy.shape) |
| |
| |
| |
| |
| feature = parse_tfrec("./samples_split/AO7_2016_2_8.tfrec") |
| show_info(feature) |
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