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README.md

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----
-license: cc-by-4.0
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+---
+license: cc-by-4.0
+language:
+- en
+tags:
+- computer-vision
+- anomaly-detection
+- industrial
+- defect-detection
+pretty_name: 'RobustAD: A Realworld Anomaly Detection Dataset for Robustness '
+size_categories:
+- 1K<n<10K
+---
+#About the Dataset
+
+RobustAD, specifically designed to evaluate the robustness of anomaly detection models in real-world scenarios. RobustAD features a curated dataset of defect detection images with meticulously controlled distribution shifts across multiple dimensions relevant to practical applications and more closely mirrors real-world deployment scenarios.
+RobustAD is designed to cover inspection challenges across multiple industries to ensure the diversity of use cases and
+encourage the development of generalizable methods. It is carefully curated to reflect the complexity of real-world
+anomaly detection task in terms of both the defect variations and the domain shifts captured in the data. Robus-
+tAD consists of 3 sub-datasets corresponding to 3 different objects of interest, each with a source domain data for
+training and multiple target domains with different shifts for testing. 
+The PCB sub-dataset captures the challenges
+of finding subtle scratches, soldering melts, and missing parts which comprise of the most common defects encoun-
+tered during inspection of Printed Circuit Boards in electronics and semiconductor manufacturing. The metal parts
+sub-dataset reflects the challenges of inspecting metal automotive parts with reflective surfaces for possible chipping,
+dents, or porosity (holes in metal) in the automotive industry. The pile of packets represents a common count-based
+anomaly detection task performed by packaging machines in the pharmaceutical industry. We believe this broad cov-
+erage of tasks and anomaly types across important sectors ensures a general model that is relevant for common in-
+dustry inspection problems and serves as a good starting point. The PCB and metal parts datasets are defined for
+localization and classification tasks where as piled packets subset is only defined for classification task. 
+
+
+
+#Dataset Card for RobustAD
+
+For more details, refer to this paper: COMING SOON!
+The three sub-datasets and the defects covered in each sub-dataset are listed below
+
+
+
+#How to Use
+TBD
+
+#License Information
+
+The RobustAD dataset is released under the Creative Commons license cc-by-4.0.
+
+#Citation Information
+
+COMING SOON!
+
+
+#Contact
+
+[email protected] (Latha Pemula) | [email protected] (Dongqing Zhang) | [email protected] (Onkar Dabeer)