Initial upload: repackaged for HuggingFace with a full datacard

README.md

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+---
+license: cc-by-4.0
+pretty_name: Bodnár-Huawei Syn10k — synthetic + real barcode images with masks
+task_categories:
+- image-segmentation
+- object-detection
+tags:
+- qr-code
+- barcode
+- segmentation
+- synthetic
+size_categories:
+- 10K<n<100K
+configs:
+- config_name: warp2014
+  data_files:
+  - split: train
+    path: data/warp2014/train*.parquet
+- config_name: huawei
+  data_files:
+  - split: train
+    path: data/huawei/train*.parquet
+---
+
+# Bodnár-Huawei Syn10k
+
+A **mirror** of the `syn10k_plus_huawei` barcode dataset from the Szeged group
+(Bodnár, Grósz, Tóth), repackaged as parquet with each image joined to its
+ground-truth mask in the same row.
+
+Released under **CC BY 4.0**, so this mirror is permitted with attribution.
+
+## Configs
+
+| config | rows | content | with mask |
+|---|---:|---|---:|
+| `warp2014` | 10,000 | synthetic warped barcode images | 10,000 |
+| `huawei` | 98 | real photographs | 98 |
+
+**Every image has its mask** — the pairing was verified by stem, and zero images
+in either config are missing one.
+
+## Fields
+
+| field | notes |
+|---|---|
+| `image` | the picture (JPEG) |
+| `mask` | the ground-truth mask (PNG) |
+| `file_name`, `stem` | original filename and its stem |
+| `subset` | `warp2014` or `huawei` |
+| `has_mask` | always true in this build; kept so the schema stays honest if a future revision has gaps |
+
+## Two notes on how to read this
+
+**The split name is a container, not a protocol.** Both configs expose a single
+split called `train` because HuggingFace requires a split name — it does **not**
+encode the authors' intended train/test partition. `warp2014` is synthetic and
+`huawei` is real photographs, which is the natural synthetic-train / real-test
+arrangement, but this mirror does not assert that the authors used it that way.
+Consult the source publication before reporting numbers as theirs.
+
+**This is a barcode dataset, not a QR-only one.** It is included in a QR
+collection because it is standard in the barcode-localisation literature and is
+one of the few sets shipping pixel masks. Check the masks for what you need
+rather than assuming every symbol is a QR code.
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+syn  = load_dataset("devmandan/syn10k-huawei-barcodes", "warp2014", split="train")
+real = load_dataset("devmandan/syn10k-huawei-barcodes", "huawei",   split="train")
+syn[0]["image"], syn[0]["mask"]      # PIL images, aligned
+```
+
+## Citation
+
+Original source:
+<https://www.inf.u-szeged.hu/~bodnaar/barcode_database/syn10k_plus_huawei.zip>
+
+```bibtex
+@misc{bodnar_syn10k,
+  title  = {Syn10k + Huawei barcode database},
+  author = {Bodn\'ar, P\'eter and Gr\'osz, Tam\'as and T\'oth, L\'aszl\'o},
+  note   = {Synthetic and real barcode images with ground-truth masks},
+  url    = {https://www.inf.u-szeged.hu/~bodnaar/barcode_database/}
+}
+```
+
+Licence: CC BY 4.0 — <https://creativecommons.org/licenses/by/4.0/>
+Please cite the authors above, not this mirror.

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