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Xilinx / QNN-MO-PYNQ

BSD 3-Clause "New" or "Revised" License
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How to train on custom dataset? #3

Open nisssal opened 6 years ago

nisssal commented 6 years ago

Hi,

Could you please give us directions to train this to our own data set? Or is it possible to train this network on original yolo implementation and covert the .weights files to the required format? Any script?

giuliogamba commented 6 years ago

Hi,

I guess you are talking about Darknet training. First you will need to instrument Darknet to perform training on reduced precision weights and activations. The modified version used for this repo has not been open-sourced yet. Once the training on your dataset achieves the desired accuracy, you can export the .weights file into the .bin used in this example. The script to performe that will be released in the near future.

nisssal commented 6 years ago

Thank you. The .weights conversion script will be really helpful.

riple commented 6 years ago

What is the DL framework used in the training process for DoReFaNet? TensorFlow, Theano or MXNet?

giuliogamba commented 6 years ago

Tensorpack on top of TensorFlow has been used for DorefaNet

riple commented 6 years ago

If you use different frameworks for the 2 demo networks, you must have different scripts to covert the weight parameters to a unified form for the FPGA. Is this right? Will you share the training scripts and converting scripts in the future?

giuliogamba commented 6 years ago

Yes, we have planned to release those scripts

wenxingsen commented 6 years ago

When will it be released?? It's very urgent.

blgpb commented 6 years ago

Excuse me, when will it be released?

Ashsur commented 5 years ago

Excuse me, when will it be released?

Kr0n0 commented 5 years ago

Hi. Any plans for the scripts release dates? Thx.

rafferino commented 5 years ago

Hello, is the script still in progress or has the plan to release it to open-source changed?

ussamazahid96 commented 5 years ago

For quantized dorefanet training in tensorpack please have a look at this repo.

For quantized dorefanet training in pytorch please have a look at this repo.

For quantized TinyYolo training (pytorch) please have a look at this

Thanks!

mohitajais commented 1 year ago

Hello,

I want to implement quantized tiny yolo on FPGA. I found this link useful -https://github.com/mohdumar644/TinyYOLO-BNN. I have tried to implement quantized Tiny Yolo training (PyTorch) from this link. My question is how the quantization is working in tiny yolo layers. I am getting very low detection accuracy on the PASCAL VOC test set using this quantized model.

Please Help

For quantized dorefanet training in tensorpack please have a look at this repo.

For quantized dorefanet training in pytorch please have a look at this repo.

For quantized TinyYolo training (pytorch) please have a look at this

Thanks!