MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
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Convert trained yolov3 Darknet-53 custom model to tensorflow model #832
I have trained a custom yolov3 Darknet-53 model (yolo3_darknet53_custom.params) using gluon-cv (mxnet). I need to convert the yolo3_darknet53_custom.params (mxnet) model to yolo3_darknet53_custom.pb (tensorflow)
Queries:
Does mmdnn supports yolo models (object detection) conversion trained using gluon-cv (mxnet) in general?
Is there any way or work around by which I can convert yolo models?
Platform: ubuntu 16.04 Python version: 3.6 Source framework: mxnet (gluon-cv) Destination framework: Tensorflow Model Type: Object detection Pre-trained model path: https://gluon-cv.mxnet.io/build/examples_detection/demo_yolo.html#sphx-glr-build-examples-detection-demo-yolo-py
I have trained a custom yolov3 Darknet-53 model (yolo3_darknet53_custom.params) using gluon-cv (mxnet). I need to convert the yolo3_darknet53_custom.params (mxnet) model to yolo3_darknet53_custom.pb (tensorflow)
Also, I see https://pypi.org/project/mmdnn/ object detection is under on-going Models.
Queries: Does mmdnn supports yolo models (object detection) conversion trained using gluon-cv (mxnet) in general? Is there any way or work around by which I can convert yolo models?
Any leads would be great! Thank you