diff --git a/README.md b/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..c99e4830deb4b3aabd32e5a7dd32a3e7297cfb7e
--- /dev/null
+++ b/README.md
@@ -0,0 +1,29 @@
+A Crop/Weed Field Image Dataset
+=============
+
+The Crop/Weed Field Image Dataset (CWFID) accompanies the following publication: "Sebastian Haug, Jörn Ostermann: A Crop/Weed Field Image Dataset for the Evaluation of Computer Vision Based Precision Agriculture Tasks, [CVPPP 2014](http://www.plant-phenotyping.org/CVPPP2014) Workshop, [ECCV 2014](http://eccv2014.org)"
+
+This dataset comprises field [images](images), vegetation segmentation [masks](masks) and crop/weed plant type [annotations](annotations). The paper provides details, e.g. on the field setting, acquisition conditions, image and ground truth data format.
+
+Paper
+-----
+Paper available [here](http://rd.springer.com/chapter/10.1007%2F978-3-319-16220-1_8).
+
+Bibtex:
+```
+@inproceedings{haug15,
+  author={Haug, Sebastian and Ostermann, J{\"o}rn},
+  title={A Crop/Weed Field Image Dataset for the Evaluation of Computer Vision Based Precision Agriculture Tasks},
+  year={2015},
+  booktitle={Computer Vision - ECCV 2014 Workshops},
+  doi={10.1007/978-3-319-16220-1_8},
+  url={http://dx.doi.org/10.1007/978-3-319-16220-1_8},
+  pages={105--116},
+}
+```
+
+Use
+---
+All data is subject to copyright and may only be used for non-commercial research. In case of use please cite our publication.
+
+Contact Sebastian Haug (sebastian.haug@de.bosch.com) for any questions.
diff --git a/annotations/001_annotation.png b/annotations/001_annotation.png
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+filename: 001_image.png
+annotation:
+- type: weed
+  points:
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+      948.0, 937.0, 909.0, 837.0]
+    y: [225.0, 234.0, 266.0, 338.0, 408.0, 422.0, 317.0, 230.0, 126.0, 114.0, 130.0,
+      167.0, 170.0, 169.0]
+- type: weed
+  points:
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+      646.0, 681.0, 663.0, 721.0, 770.0, 851.0, 888.0, 939.0, 987.0]
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+      558.0, 523.0, 496.0, 490.0, 476.0, 517.0, 537.0, 533.0, 545.0]
+- type: crop
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+    y: [882.0, 872.0, 926.0, 948.0, 933.0]
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+    y: [769.0, 750.0, 736.0, 750.0, 790.0, 856.0, 918.0, 918.0, 871.0, 797.0]
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+    y: [477.0, 528.0, 576.0, 549.0, 501.0, 465.0]
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