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NaturalIntelligence / imglab

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Speed up labeling

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TheDeathConqueror
TheDeathConqueror commented Aug 19, 2019

I found a new tool makesense who is trying to do the same thing that you're already doing. Probably with some new thoughts in mind. I recently asked the author how that tool is doing differently: SkalskiP/make-sense#23

The author responded that we need multiple clicks while labeling in imglab. Though I didn't understand it well as I can control most of the things with

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good first issue feature-request
Find more good first issues

yoshitomo-matsubara / torchdistill

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PyTorch-based modular, configuration-driven framework for knowledge distillation. 🏆20 methods presented at CVPR, ICLR, ECCV, NeurIPS, ICCV, etc are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark.

nlp natural-language-processing glue pytorch transformer imagenet image-classification coco object-detection semantic-segmentation knowledge-distillation cifar10 pascal-voc cifar100 google-colab colab-notebook
  • Updated Sep 14, 2021
  • Python

obss / sahi

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yolov4 support

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Fetulhak
Fetulhak commented Jun 17, 2021

@fcakyon I have trained and YOLOV4 model using AlexyAB's repo and I have generated a weight file for my custom dataset which was sliced using your repo. Now I want to check the test results for predicted YOLOV4 results. How can I integrate YOLOV4 weight file to your test folder so that I can use the YOLOV4 like you have used the YOLOV5 model which was from from ultralytics repo.

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enhancement good first issue help wanted

RubensZimbres / Repo-2018

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Deep Learning Summer School + Tensorflow + OpenCV cascade training + YOLO + COCO + CycleGAN + AWS EC2 Setup + AWS IoT Project + AWS SageMaker + AWS API Gateway + Raspberry Pi3 Ubuntu Core

raspberry-pi opencv iot computer-vision tensorflow keras coco aws-ec2 ec2-instance aws-iot opencv-library generative-adversarial-networks raspberry-pi-3 opencv3 cyclegan haarcascade sagemaker yolo-model ubuntucore aws-sagemaker
  • Updated Feb 3, 2021
  • Jupyter Notebook

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