How convert darknet model to onnx?

Hi,

Can someone give me instructions how convert my custom darknet model (yolov2-tiny) to ONNX? I know I should convert my darknet model to tensorflow, then to onnx, but I struggle with this for several days.

What I’ve tried: Convert darknet model (weights + cfg) to tensorflow using darkflow -> I got .pb file (SUCCESS)

Then I wanted to convert pb file to onnx:

1. Tried to convert pb file to onnx using mmconvert: mmconvert -sf tensorflow -iw path_to_my_pb_file -df onnx -om yolotfonnx --inNodeName input --dstNodeName output error: TypeError: can only concatenate list (not "NoneType") to list
2. Tried to convert using tf2onnx: python3 -m tf2onnx.convert --graphdef path_to_my_pb_file --output yolov2-tiny.onnx --inputs input:0 --outputs output:0 error: AssertionError: output is not in graph

this also doesn’t work: python3 -m tf2onnx.convert --saved-model path_to_my_pb_file --output yolov2-tiny.onnx error:

RuntimeError: MetaGraphDef associated with tags 'serve' could not be found in SavedModel. To inspect available tag-sets in the SavedModel, please use the SavedModel CLI: `saved_model_cli`
available_tags: []

1. Tried to convert using onnx-tf: onnx-tf convert -i path_to_my_pb_file -o path_for_output_onnx_file error: ValidationError: The model does not have an ir_version set properly.

I think darkflow can be not compatible with yolov2-tiny. I also tried to convert original darknet yolov2 model and have same problems after conversion with darkflow.

[jjeongmin0308]

Hello, I’m having a hard time converting the darknet yolov2 model to onnx. It has been converted but does not detect anything when running Barracuda. I want to know in detail how you did it, is it possible?

https://github.com/derenlei/Unity_Detection2AR/issues/39

Here’s what I tried.

[BeiieB]

Hi,

I tried your ‘yolov2-tiny_freeze’ model and I think it works well. Set the INPUT_NAME to yolov2-tiny/net1 and OUTPUT_NAME to yolov2-tiny/convolutional9/BiasAdd. Also, we use different scripts for yolov2 and v3 so make sure the Selected_detector under Camera Image is yolo 2_tiny.