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danbooru-v4-tfrecord

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Super-squash branch 'main' using huggingface_hub

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  1. .gitattributes +62 -0
  2. README.md +71 -0
  3. record_shards_train/train_0000.tfrecord +3 -0
  4. record_shards_train/train_0001.tfrecord +3 -0
  5. record_shards_train/train_0002.tfrecord +3 -0
  6. record_shards_train/train_0003.tfrecord +3 -0
  7. record_shards_train/train_0004.tfrecord +3 -0
  8. record_shards_train/train_0005.tfrecord +3 -0
  9. record_shards_train/train_0006.tfrecord +3 -0
  10. record_shards_train/train_0007.tfrecord +3 -0
  11. record_shards_train/train_0008.tfrecord +3 -0
  12. record_shards_train/train_0009.tfrecord +3 -0
  13. record_shards_train/train_0010.tfrecord +3 -0
  14. record_shards_train/train_0011.tfrecord +3 -0
  15. record_shards_train/train_0012.tfrecord +3 -0
  16. record_shards_train/train_0013.tfrecord +3 -0
  17. record_shards_train/train_0014.tfrecord +3 -0
  18. record_shards_train/train_0015.tfrecord +3 -0
  19. record_shards_train/train_0016.tfrecord +3 -0
  20. record_shards_train/train_0017.tfrecord +3 -0
  21. record_shards_train/train_0018.tfrecord +3 -0
  22. record_shards_train/train_0019.tfrecord +3 -0
  23. record_shards_train/train_0020.tfrecord +3 -0
  24. record_shards_train/train_0021.tfrecord +3 -0
  25. record_shards_train/train_0022.tfrecord +3 -0
  26. record_shards_train/train_0023.tfrecord +3 -0
  27. record_shards_train/train_0024.tfrecord +3 -0
  28. record_shards_train/train_0025.tfrecord +3 -0
  29. record_shards_train/train_0026.tfrecord +3 -0
  30. record_shards_train/train_0027.tfrecord +3 -0
  31. record_shards_train/train_0028.tfrecord +3 -0
  32. record_shards_train/train_0029.tfrecord +3 -0
  33. record_shards_train/train_0030.tfrecord +3 -0
  34. record_shards_train/train_0031.tfrecord +3 -0
  35. record_shards_train/train_0032.tfrecord +3 -0
  36. record_shards_train/train_0033.tfrecord +3 -0
  37. record_shards_train/train_0034.tfrecord +3 -0
  38. record_shards_train/train_0035.tfrecord +3 -0
  39. record_shards_train/train_0036.tfrecord +3 -0
  40. record_shards_train/train_0037.tfrecord +3 -0
  41. record_shards_train/train_0038.tfrecord +3 -0
  42. record_shards_train/train_0039.tfrecord +3 -0
  43. record_shards_train/train_0040.tfrecord +3 -0
  44. record_shards_train/train_0041.tfrecord +3 -0
  45. record_shards_train/train_0042.tfrecord +3 -0
  46. record_shards_train/train_0043.tfrecord +3 -0
  47. record_shards_train/train_0044.tfrecord +3 -0
  48. record_shards_train/train_0045.tfrecord +3 -0
  49. record_shards_train/train_0046.tfrecord +3 -0
  50. record_shards_train/train_0047.tfrecord +3 -0
.gitattributes ADDED
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+ *.7z filter=lfs diff=lfs merge=lfs -text
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+ *.arrow filter=lfs diff=lfs merge=lfs -text
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+ *.bin filter=lfs diff=lfs merge=lfs -text
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+ *.bz2 filter=lfs diff=lfs merge=lfs -text
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+ *.ckpt filter=lfs diff=lfs merge=lfs -text
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+ *.ftz filter=lfs diff=lfs merge=lfs -text
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+ *.gz filter=lfs diff=lfs merge=lfs -text
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+ *.h5 filter=lfs diff=lfs merge=lfs -text
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+ *.joblib filter=lfs diff=lfs merge=lfs -text
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+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
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+ *.lz4 filter=lfs diff=lfs merge=lfs -text
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+ *.mds filter=lfs diff=lfs merge=lfs -text
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+ *.mlmodel filter=lfs diff=lfs merge=lfs -text
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+ *.model filter=lfs diff=lfs merge=lfs -text
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+ *.msgpack filter=lfs diff=lfs merge=lfs -text
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+ *.npy filter=lfs diff=lfs merge=lfs -text
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+ *.npz filter=lfs diff=lfs merge=lfs -text
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+ *.onnx filter=lfs diff=lfs merge=lfs -text
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+ *.ot filter=lfs diff=lfs merge=lfs -text
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+ *.parquet filter=lfs diff=lfs merge=lfs -text
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+ *.pb filter=lfs diff=lfs merge=lfs -text
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+ *.pickle filter=lfs diff=lfs merge=lfs -text
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+ *.pkl filter=lfs diff=lfs merge=lfs -text
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+ *.pt filter=lfs diff=lfs merge=lfs -text
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+ *.pth filter=lfs diff=lfs merge=lfs -text
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+ *.rar filter=lfs diff=lfs merge=lfs -text
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+ *.safetensors filter=lfs diff=lfs merge=lfs -text
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+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+ *.tar.* filter=lfs diff=lfs merge=lfs -text
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+ *.tar filter=lfs diff=lfs merge=lfs -text
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+ *.tflite filter=lfs diff=lfs merge=lfs -text
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+ *.tgz filter=lfs diff=lfs merge=lfs -text
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+ *.wasm filter=lfs diff=lfs merge=lfs -text
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+ *.xz filter=lfs diff=lfs merge=lfs -text
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+ *.zip filter=lfs diff=lfs merge=lfs -text
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+ *.zst filter=lfs diff=lfs merge=lfs -text
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+ *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ # Audio files - uncompressed
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+ *.pcm filter=lfs diff=lfs merge=lfs -text
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+ *.sam filter=lfs diff=lfs merge=lfs -text
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+ *.raw filter=lfs diff=lfs merge=lfs -text
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+ # Audio files - compressed
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+ *.aac filter=lfs diff=lfs merge=lfs -text
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+ *.flac filter=lfs diff=lfs merge=lfs -text
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+ *.mp3 filter=lfs diff=lfs merge=lfs -text
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+ *.ogg filter=lfs diff=lfs merge=lfs -text
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+ *.wav filter=lfs diff=lfs merge=lfs -text
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+ # Image files - uncompressed
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+ *.bmp filter=lfs diff=lfs merge=lfs -text
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+ *.gif filter=lfs diff=lfs merge=lfs -text
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+ *.png filter=lfs diff=lfs merge=lfs -text
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+ *.tiff filter=lfs diff=lfs merge=lfs -text
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+ # Image files - compressed
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+ *.jpg filter=lfs diff=lfs merge=lfs -text
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+ *.jpeg filter=lfs diff=lfs merge=lfs -text
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+ *.webp filter=lfs diff=lfs merge=lfs -text
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+ # Video files - compressed
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+ *.mp4 filter=lfs diff=lfs merge=lfs -text
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+ *.webm filter=lfs diff=lfs merge=lfs -text
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+ # TFRecord files - uncompressed
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+ *.tfrecord filter=lfs diff=lfs merge=lfs -text
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+ train_processed.txt filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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+ ---
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+ size_categories:
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+ - 1M<n<10M
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+ ---
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+
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+ Danbooru TFRecords to train classifiers and other stuff with my codebases.
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+
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+ TFRecord serialization/deserialization code:
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+
10
+ ```python
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+ NUM_CLASSES = 12822
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+
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+
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+ # Function to convert value to bytes_list
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+ def _bytes_feature(value):
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+ if isinstance(value, type(tf.constant(0))):
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+ value = value.numpy()
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+ elif isinstance(value, str):
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+ value = value.encode()
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+ return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))
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+
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+
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+ # Function to convert bool/enum/int/uint to int64_list
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+ def _int64_feature(value):
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+ int64_list = tf.train.Int64List(value=tf.reshape(value, (-1,)))
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+ return tf.train.Feature(int64_list=int64_list)
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+
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+
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+ # Function to create a tf.train.Example message
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+ def serialize_example(image_id, image_bytes, label_indexes, tag_string):
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+ feature = {
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+ "image_id": _int64_feature(image_id),
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+ "image_bytes": _bytes_feature(image_bytes),
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+ "label_indexes": _int64_feature(label_indexes),
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+ "tag_string": _bytes_feature(tag_string),
36
+ }
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+ example_proto = tf.train.Example(features=tf.train.Features(feature=feature))
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+ return example_proto.SerializeToString()
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+
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+
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+ # Function to deserialize a single tf.train.Example message
42
+ def deserialize_example(example_proto):
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+ feature_description = {
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+ "image_id": tf.io.FixedLenFeature([], tf.int64),
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+ "image_bytes": tf.io.FixedLenFeature([], tf.string),
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+ "label_indexes": tf.io.VarLenFeature(tf.int64),
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+ "tag_string": tf.io.FixedLenFeature([], tf.string),
48
+ }
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+
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+ # Parse the input 'tf.train.Example' proto using the dictionary above.
51
+ parsed_example = tf.io.parse_single_example(example_proto, feature_description)
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+ image_tensor = tf.io.decode_jpeg(parsed_example["image_bytes"], channels=3)
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+
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+ # We only stored label indexes in the TFRecords to save space
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+ # Emulate MultiLabelBinarizer to get a tensor of 0s and 1s
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+ label_indexes = tf.sparse.to_dense(
57
+ parsed_example["label_indexes"],
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+ default_value=0,
59
+ )
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+ one_hots = tf.one_hot(label_indexes, NUM_CLASSES)
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+ labels = tf.reduce_max(one_hots, axis=0)
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+ labels = tf.cast(labels, tf.float32)
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+
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+ sample = {
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+ "image_ids": parsed_example["image_id"],
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+ "images": image_tensor,
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+ "labels": labels,
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+ "tags": parsed_example["tag_string"],
69
+ }
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+ return sample
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+ ```
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