CodeXGLUE is a benchmark dataset and open challenge for code intelligence. It includes a collection of code intelligence tasks and a platform for model evaluation and comparison. CodeXGLUE stands for General Language Understanding Evaluation benchmark for CODE. It includes 14 datasets for 10 diversified code intelligence tasks covering the following scenarios:
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The dataset is constructed from images of defective production items that were provided and annotated by Kolektor Group d.o.o.. The images were captured in a controlled industrial environment in a real-world case.
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KolektorSDD2 is a surface-defect detection dataset with over 3000 images containing several types of defects, obtained while addressing a real-world industrial problem.
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This is a synthetic dataset for defect detection on textured surfaces. It was originally created for a competition at the 2007 symposium of the DAGM (Deutsche Arbeitsgemeinschaft für Mustererkennung e.V., the German chapter of the International Association for Pattern Recognition). The competition was hosted together with the GNSS (German Chapter of the European Neural Network Society).
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ARMBench is a large-scale, object-centric benchmark dataset for robotic manipulation in the context of a warehouse. ARMBench contains images, videos, and metadata that corresponds to 235K+ pick-and-place activities on 190K+ unique objects. The data is captured at different stages of manipulation, i.e., pre-pick, during transfer, and after placement.
3 PAPERS • NO BENCHMARKS YET
DeepPCB
2 PAPERS • 1 BENCHMARK
The directory HiCIS contains two datasets for instance segmentation of honeycombs in concrete in COCO Format. The datasets orginate from images scraped from the internet and the other one is provided by Metis Systems AG. The directory HiCC/web contains the dataset using the images from the internet and HICC/metis contains the dataset using the images provided by Metis Systems AG as part of the research project Smart Design and Construction (SDaC).
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This dataset is a collection of 5348 links from bug-introducing and bug-fixing commit sets extracted from Mozilla's Bugzilla with the use of bugbug. In this repository, you will find two shapes of it: