Create README.md

README.md

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+---
+task_categories:
+- image-feature-extraction
+---
+
+# Google Image Malaysian Vehicle Dedup
+
+Original dataset https://huggingface.co/datasets/malaysia-ai/crawl-google-image-malaysian-vehicle
+
+Source code at https://github.com/mesolitica/malaysian-dataset/tree/master/vlm/dedup-malaysian-vehicle
+
+## Dedup 50% similar
+
+[dedup-0.5.jsonl](dedup-0.7.jsonl), total deduped 97598 images,
+
+```
+{'filename': 'train-00075-of-00165-c0ebcc169b1f62d2.parquet',
+ 'keyword': '2021 Honda City 1.5 E',
+ 'no': 2,
+ 'selected_indices': [696,
+  702,
+  705,
+  707,
+  712,
+  716,
+  720,
+  723,
+  727,
+  732,
+  742,
+  745,
+  775,
+  779,
+  780,
+  787,
+  797,
+  817,
+  844,
+  876,
+  894,
+  898,
+  905,
+  917,
+  962,
+  965,
+  966,
+  988,
+  993,
+  995,
+  1000,
+  1009,
+  1012,
+  1015,
+  1016,
+  1029,
+  1044,
+  1049,
+  1054,
+  1077,
+  1086,
+  1096,
+  1131,
+  1174,
+  1185,
+  1188,
+  1198,
+  1208,
+  1216,
+  1217,
+  1219,
+  1223,
+  1229,
+  1237,
+  1247,
+  1253,
+  1274,
+  1276,
+  1286,
+  1305,
+  1314,
+  1347,
+  1348,
+  1353,
+  1355,
+  1401,
+  1412]}
+```
+
+- `filename` is the parquet file from the original repository.
+- `selected_indices` is the index of dataframe of that filename.
+
+## Embedding
+
+We convert to embedding using https://huggingface.co/google/siglip-base-patch16-512, we use MosaicML for faster indexing,
+
+```python
+from streaming import MDSWriter
+from streaming.base.format.mds.encodings import Encoding, _encodings
+from streaming import LocalDataset
+import streaming
+import numpy as np
+from tqdm import tqdm
+
+class Float32(Encoding):
+    def encode(self, obj) -> bytes:
+        return obj.tobytes()
+
+    def decode(self, data: bytes):
+        return np.frombuffer(data, np.float32)
+
+_encodings['float32'] = Float32
+
+dataset = LocalDataset('embedding')
+```