datumaro
synthetic-computer-vision
datumaro | synthetic-computer-vision | |
---|---|---|
2 | 1 | |
486 | 991 | |
2.5% | 0.0% | |
9.4 | 0.0 | |
3 days ago | about 1 year ago | |
Python | Python | |
MIT License | MIT License |
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datumaro
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Does anyone use CVAT for image annotation?
1) CVAT has internal inference for models. If you upload model there in the correct format, then it will be able to generate the detection box itself - https://onepanel.medium.com/train-an-object-detection-model-from-scratch-and-run-inference-on-it-in-10-minutes-16147ef656aa 2) Yes you can upload your prediction. But last time i did it - there were some problems and it took me several hours. It seems to me that you just need to load the markup in one of the formats that it supported by CVAT. If your format is not supported, then you will need to convert. For example like this - https://github.com/openvinotoolkit/datumaro
- Can I know what kind of dataset annotation for object detection is this?
synthetic-computer-vision
What are some alternatives?
cocojson - Utility scripts for COCO json annotation format
ORBIT-Dataset - The ORBIT dataset is a collection of videos of objects in clean and cluttered scenes recorded by people who are blind/low-vision on a mobile phone. The dataset is presented with a teachable object recognition benchmark task which aims to drive few-shot learning on challenging real-world data.
sahi - Framework agnostic sliced/tiled inference + interactive ui + error analysis plots
CREStereo - Official MegEngine implementation of CREStereo(CVPR 2022 Oral).
datasets - 🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
pycococreator - Helper functions to create COCO datasets
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
DA-RetinaNet - Official Detectron2 implementation of DA-RetinaNet of our Image and Vision Computing 2021 work 'An unsupervised domain adaptation scheme for single-stage artwork recognition in cultural sites'
Meta-SelfLearning - Meta Self-learning for Multi-Source Domain Adaptation: A Benchmark
UCF-SST-CitySim1-Dataset - Official github page of UCF SST CitySim Dataset
fashion-mnist - A MNIST-like fashion product database. Benchmark :point_down: