Make-sense Alternatives

Similar projects and alternatives to make-sense

  1. yolov5

    131 make-sense VS yolov5

    YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

  2. Nutrient

    Nutrient – The #1 PDF SDK Library, trusted by 10K+ developers. Other PDF SDKs promise a lot - then break. Laggy scrolling, poor mobile UX, tons of bugs, and lack of support cost you endless frustrations. Nutrient’s SDK handles billion-page workloads - so you don’t have to debug PDFs. Used by ~1 billion end users in more than 150 different countries.

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  3. cvat

    26 make-sense VS cvat

    Discontinued Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/cvat-ai/cvat]

  4. notebooks

    21 make-sense VS notebooks

    This repository offers a comprehensive collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like YOLO11, RT-DETR, SAM 2, Florence-2, PaliGemma 2, and Qwen2.5VL.

  5. VoTT

    8 make-sense VS VoTT

    Discontinued Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.

  6. sahi

    11 make-sense VS sahi

    Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

  7. roboflow-100-benchmark

    Code for replicating Roboflow 100 benchmark results and programmatically downloading benchmark datasets

  8. SynthDet

    Discontinued SynthDet - An end-to-end object detection pipeline using synthetic data

  9. CodeRabbit

    CodeRabbit: AI Code Reviews for Developers. Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.

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  10. label-studio

    50 make-sense VS label-studio

    Label Studio is a multi-type data labeling and annotation tool with standardized output format

  11. awesome-open-data-annotation

    Open Source Data Annotation & Labeling Tools

  12. AID

    4 make-sense VS AID

    One-Stop System for Machine Learning.

  13. MiVOS

    2 make-sense VS MiVOS

    [CVPR 2021] Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware Fusion. Semi-supervised VOS as well!

  14. awesome-object-detection

    Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html (by amusi)

  15. pytorch-pose-hg-3d

    PyTorch implementation for 3D human pose estimation

  16. narya

    1 make-sense VS narya

    The Narya API allows you track soccer player from camera inputs, and evaluate them with an Expected Discounted Goal (EDG) Agent. This repository contains the implementation of the flowing paper https://arxiv.org/abs/2101.05388. We also make available all of our pretrained agents, and the datasets we used as well.

  17. roboflow-100-benchmark

    1 make-sense VS roboflow-100-benchmark

    Discontinued Code for replicating Roboflow 100 benchmark results and programmatically downloading benchmark datasets [Moved to: https://github.com/roboflow/roboflow-100-benchmark] (by roboflow-ai)

  18. Universal Data Tool

    Collaborate & label any type of data, images, text, or documents, in an easy web interface or desktop app.

  19. SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better make-sense alternative or higher similarity.

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1.3
7 months ago

Sponsored
Nutrient – The #1 PDF SDK Library, trusted by 10K+ developers
Other PDF SDKs promise a lot - then break. Laggy scrolling, poor mobile UX, tons of bugs, and lack of support cost you endless frustrations. Nutrient’s SDK handles billion-page workloads - so you don’t have to debug PDFs. Used by ~1 billion end users in more than 150 different countries.
www.nutrient.io

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