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ultralytics/yolov5

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Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.

15 mentions on Hacker News by 15 people: 2 stories, 13 comments · first 2020-06-10 · latest 2025-05-02

Mentions per year 15 mentions · busiest year 2020 (8)
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  1. …based content, you might need something smarter. I think maybe it is a place where tools such as https://github.com/ultralytics/yolov5 can shine for me. simple enough to work with most of my images and tag them according to some…
    comment by SansGuidon · 2025-05-02 · in Linkwarden: FOSS self-hostable bookmarking with AI-tagging and page archival
  2. …and finally ran across a helpfully commented top-level call to fix an obscure performance problem: https://github.com/ultralytics/yolov5/blob/master/utils/gene... cv2.setNumThreads(0) # prevent OpenCV from multithreading (incompatible with…
    comment by DonHopkins · 2024-08-18 · in Micro-libraries should never be used
  3. …[1] https://docs.roboflow.com/rest-api [2] https://github.com/SkalskiP/make-sense/pull/298 [3] https://github.com/ultralytics/yolov5/discussions/10425 [4] https://docs.roboflow.com/train/pro-third-party-training-int... [5]…
    comment by yeldarb · 2023-01-01 · in Roboflow 100: A New Object Detection Benchmark
  4. Tangentially related: There is some controversy around YOLOv5's name: https://github.com/ultralytics/yolov5/issues/2
    comment by enricozb · 2021-09-10 · in YOLOv5 on CPUs: Sparsifying to Achieve GPU-Level Performance
  5. I'm pretty sure this isn't using the Tensor cores on the GPU. If you see here ( https://github.com/ultralytics/yolov5/blob/master/README.md ), the speed of inference on a V100 for YOLOv5s should be 2 ms per image, or 500 imgs/s, not the…
    comment by deepnotderp · 2021-09-10 · in YOLOv5 on CPUs: Sparsifying to Achieve GPU-Level Performance
  6. I made a custom component to integrate this object detection lib with pytorch. https://github.com/ultralytics/yolov5 The tensorflow one it comes with didn't work on python 3.8 or on my gpu. I should blog about it.
    comment by acidburnNSA · 2020-08-08 · in Google speakers are listening to more than just voice commands
  7. …the first official announcement.[5] [1] https://github.com/AlexeyAB/darknet/issues/5920 [2] https://github.com/ultralytics/yolov5/issues/2 [3] https://github.com/AlexeyAB/darknet/issues/5920#issuecomment... [4]…
    comment by CompleteSkeptic · 2020-08-04 · in PP-YOLO Surpasses YOLOv4 – State-of-the-art object detection techniques
  8. …[i] will allow a rpi4 to more ably do this without piping the video to another processor. [i] https://github.com/ultralytics/yolov5
    comment by canada_dry · 2020-06-21 · in Tensorflow on edge, or – Building a “smart” security camera with a Raspberry Pi
  9. …matter what I think"), he said another maintainer of darknet/yolo should have more say. [2] [1] https://github.com/ultralytics/yolov5/issues/2 [2] https://github.com/AlexeyAB/darknet/issues/5920
    comment by voqv · 2020-06-14 · in Responding to the Controversy about YOLOv5
  10. …make a real COCO comparison instead. The YoloV5 repo itself shows performance comparable to YoloV3: https://github.com/ultralytics/yolov5#pretrained-checkpoints Another comparison suggests YoloV5 is slightly WORSE than YoloV4:…
    comment by anthiras · 2020-06-11 · in YOLOv5: State-of-the-art object detection at 140 FPS
  11. …the bottom of this with the creators of YOLOv4: https://github.com/AlexeyAB/darknet/issues/5920 [1] https://github.com/ultralytics/yolov5/issues/2 [2] https://github.com/ultralytics/yolov5/issues/4
    comment by bArray · 2020-06-10 · in YOLOv5: State-of-the-art object detection at 140 FPS
  12. …was trained on the 90-class COCO challenge (1), while YOLOv5 was trained on 80 classes (2). [1] https://github.com/ultralytics/yolov5/blob/master/data/coco.... [2] https://github.com/google/automl/blob/master/efficientdet/in...
    comment by ely-s · 2020-06-10 · in YOLOv5: State-of-the-art object detection at 140 FPS
  13. If anyone's interested in the direct GitHub link to the repository: https://github.com/ultralytics/yolov5
    comment by qchris · 2020-06-10 · in YOLOv5: State-of-the-art object detection at 140 FPS