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+# DOTA-v1.0 data preparation
+
+Download DOTA-v1.0 from the official project or an equivalent complete mirror.
+The original dataset contains 1,411 training images, 458 validation images and
+937 unlabeled test images with 15 classes.
+
+## Patch generation
+
+Use the mmrotate DOTA splitter with the single-scale settings used by
+Point2RBox-v3:
+
+| Option | Value |
+|---|---|
+| patch size | 1024 |
+| gap | 200 |
+| scale rate | 1.0 |
+| image-rate threshold | 0.6 |
+| instance IoF threshold | 0.7 |
+| padding value | `[104, 116, 124]` |
+
+The JSON splitter configurations are provided in `tools/dota_split/`. A correct
+single-scale split contains 21,046 trainval patches and 10,833 test patches.
+
+Expected layout:
+
+```text
+split_ss_dota/
+├── trainval/
+│   ├── images/
+│   └── annfiles/
+└── test/
+    └── images/
+```
+
+The pseudo-label exporter writes
+`point2rbox_v3_pseudo_labels.bbox.json` under the configured data root. The
+second-stage dataset reads this JSON together with `trainval/images`.
+
+Update `images_dir`, `annotations_file` and pseudo-label paths in
+`configs/point2rbox_v3/` if your data root differs from the provided config.
+
+## Input validation
+
+Before training, verify that no Git LFS pointer files remain, every image can be
+decoded, trainval image and annotation stems match, and each annotation line has
+eight polygon coordinates followed by class name and difficulty flag. Parsers
+accept both official headers and headerless files, as well as LF or CRLF line
+endings.