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REST API

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A representational state transfer (REST) API is a way to provide compatibility between computer systems on the Internet. The concept was first outlined in a dissertation by Roy Fielding in 2000.

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axnsan12 / drf-yasg

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Provide a drf-hal-json integration

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webjunkie
webjunkie commented Aug 24, 2018

I'm using https://github.com/Artory/drf-hal-json/ that basically provides custom base serializers that add dynamically fields like _links into the response via the to_representation method.

I tried to somehow get that into the schema as well, but I'm getting stuck. Are there any directions on what I need to provide/subclass/overwrite, so to make it work?

I imagine I could inspect my seri

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feature proposal good first issue help wanted

prkumar / uplink

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BMW-InnovationLab / BMW-TensorFlow-Training-GUI

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This repository allows you to get started with a gui based training a State-of-the-art Deep Learning model with little to no configuration needed! NoCode training with TensorFlow has never been so easy.

docker gui deep-neural-networks computer-vision deep-learning neural-network tensorflow rest-api tensorboard resnet deeplearning object-detection nvidia-docker computervision objectdetection no-code tensorflow-training detection-api tensorflow-gui inference-api
  • Updated Sep 26, 2020
  • Python

BMW-InnovationLab / BMW-YOLOv4-Training-Automation

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This repository allows you to get started with training a state-of-the-art Deep Learning model with little to no configuration needed! You provide your labeled dataset or label your dataset using our BMW-LabelTool-Lite and you can start the training right away and monitor it in many different ways like TensorBoard or a custom REST API and GUI. NoCode training with YOLOv4 and YOLOV3 has never been so easy.

docker gui automation monitoring deep-learning neural-network rest-api yolo tensorboard deeplearning object-detection darknet computervision objectdetection no-code yolov3 alexeyab-darknet yolo-gui yolo-tensorboard yolov4
  • Updated Jul 30, 2020
  • Python

ctuning / ck

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Collective Knowledge framework (CK) helps to organize any software project as a database of reusable components with common automation actions and extensible meta descriptions based on FAIR principles (findability, accessibility, interoperability, and reusability). See real-world use cases from Arm, General Motors, IBM, RPi, ACM, and MLPerf:

docker elasticsearch workflow devops automation database rest-api open-science reproducibility knowledge-management reusable-components reusable-artifacts reusability best-practises common-api fair-principles mlops mlperf
  • Updated Sep 25, 2020
  • Python
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