CoolFace
20 results

localization

Pjzno /localization0 likes6.6k downloads5d agoHugging Faceamir-kazemi /aidovecl-vehicle-detection-classification-localization AIDOVECL: AI-generated Dataset of Outpainted Vehicles for Eye-level Classification and Localization We introduce an annotated AI-generated dataset of eye-level vehicle images using outpainting, offering versatile generation of diverse vehicle classes in varied contexts with pretrained models. Citation Notice Please ensure that all publications and presentations using this data reference the following paper: Kazemi, A., Fatima, Q. ul A., Kindratenko, V., & Tessum, C. W.… See the full description on the dataset page: https://huggingface.co/datasets/amir-kazemi/aidovecl-vehicle-detection-classification-localization.imageobject-detection1K<n<10K0 likes4k downloads5mo agoHugging FaceNamthukhoa214 /imagenet-object-localization0 likes1.7k downloads5mo agoHugging FaceJetBrains-Research /lca-bug-localization 🏟️ Long Code Arena (Bug localization) This is the benchmark for the Bug localization task as part of the 🏟️ Long Code Arena benchmark. The bug localization problem can be formulated as follows: given an issue with a bug description and a repository snapshot in a state where the bug is reproducible, identify the files within the repository that need to be modified to address the reported bug. The dataset provides all the required components for evaluation of bug localization… See the full description on the dataset page: https://huggingface.co/datasets/JetBrains-Research/lca-bug-localization.imagetext-generation10K<n<100K4 likes1.2k downloads2y agoHugging FacePGCodeLLM /amir-code-localization-data0 likes510 downloads3mo agoHugging Facetiginamaria /bug-localization Bug Localization This is the data for Bug Localization benchmark. How-to Since the dataset is private, if you haven't used HF Hub before, add your token via huggingface-cli first: huggingface-cli login List all the available configs via datasets.get_dataset_config_names and choose an appropriate one Load the data via load_dataset: from datasets import load_dataset # Select a configuration from ["py", "java", "kt", "mixed"] configuration = "py" # Select a split from… See the full description on the dataset page: https://huggingface.co/datasets/tiginamaria/bug-localization.tabular10K<n<100K3 likes339 downloads2y agoHugging Face