embedeep/Free-TPU
Free TPU for FPGA with compiler supporting Pytorch/Caffe/Darknet/NCNN. An AI processor for using Xilinx FPGA to solve image classification, detection, and segmentation problem.
This solution helps engineers and researchers working with embedded systems to accelerate deep learning tasks like image classification, object detection, and segmentation directly on Xilinx FPGAs. It takes your pre-trained AI models (from frameworks like PyTorch, Caffe, Darknet, or NCNN) and compiles them into an optimized format that runs efficiently on an FPGA. The result is faster, more power-efficient AI inference at the edge.
273 stars. No commits in the last 6 months.
Use this if you need to deploy existing deep learning models onto Xilinx FPGAs for high-performance, low-power inference in edge computing applications.
Not ideal if you are looking to train deep learning models, or if your target hardware is not a Xilinx FPGA.
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273
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MIT
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Last pushed
May 06, 2023
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