tensorflow-yolov4-tflite VS tensorrt_demos

Compare tensorflow-yolov4-tflite vs tensorrt_demos and see what are their differences.

tensorflow-yolov4-tflite

YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.3.1, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite (by haroonshakeel)
Yolov4 Tensorflow2
Source Code
github.com
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tensorrt_demos

TensorRT MODNet, YOLOv4, YOLOv3, SSD, MTCNN, and GoogLeNet (by jkjung-avt)
Tensorrt Yolov4 Yolov3 ssd-mobilenet Mtcnn Googlenet modnet object-detection Jetson
Source Code
jkjung-avt.github.io
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tensorflow-yolov4-tflite tensorrt_demos
1 5
59 1,720
- -
5.4 3.1
over 3 years ago about 1 year ago
Python Python
MIT License MIT License
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tensorflow-yolov4-tflite

Posts with mentions or reviews of tensorflow-yolov4-tflite. We have used some of these posts to build our list of alternatives and similar projects.

tensorrt_demos

Posts with mentions or reviews of tensorrt_demos. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-06-04.
  • lowering size of YOLOV4 detection model
    1 project | /r/computervision | 10 Jul 2022
    tensorrt_demo github repository
  • Jetson Nano: TensorFlow model. Possibly I should use PyTorch instead?
    2 projects | /r/pytorch | 4 Jun 2021
    https://github.com/NVIDIA-AI-IOT/torch2trt <- pretty straightforward https://github.com/jkjung-avt/tensorrt_demos <- this helped me a lot
  • PyTorch 1.8 release with AMD ROCm support
    8 projects | news.ycombinator.com | 4 Mar 2021
    > I'll also add a caveat that toolage for Jetson boards is extremely incomplete.

    A hundred times this. I was about to write another rant here but I already did that[0] a while ago, so I'll save my breath this time. :)

    Another fun fact regarding toolage: Today I discovered that many USB cameras work poorly on Jetsons (at least when using OpenCV), probably due to different drivers and/or the fact that OpenCV doesn't support ARM64 as well as it does x86_64. :(

    > They supply you with a bunch of sorely outdated models for TensorRT like Inceptionv3 and SSD-MobileNetv2 and VGG-16.

    They supply you with such models? That's news to me. AFAIK converting something like SSD-MobileNetv2 from TensorFlow to TensorRT still requires substantial manual work and magic, as this code[1] attests to. There are countless (countless!) posts on the Nvidia forums by people complaining that they're not able to convert their models.

    [0]: https://news.ycombinator.com/item?id=26004235

    [1]: https://github.com/jkjung-avt/tensorrt_demos/blob/master/ssd... (In fact, this is the only piece of code I've found on the entire internet that managed to successfully convert my SSD-MobileNetV2.)

  • I'm tired of this anti-Wayland horseshit
    16 projects | news.ycombinator.com | 2 Feb 2021
  • H.264 hardware acceleration for surveillance station performance
    1 project | /r/synology | 12 Jan 2021
    It was some work getting compiled on nano but I used this guy's work to get started. https://jkjung-avt.github.io/tensorrt-yolov4/ and https://github.com/jkjung-avt/tensorrt_demos

What are some alternatives?

When comparing tensorflow-yolov4-tflite and tensorrt_demos you can also consider the following projects:

yolov4-deepsort - Object tracking implemented with YOLOv4, DeepSort, and TensorFlow.

YOLOX - YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

tensorflow-yolov4-tflite vs yolov4-deepsort tensorrt_demos vs YOLOX