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Hi,
I have been exploring on converting darknet yolov4 .weight file .cfg to tensorflow (.pb) and used mo.py to convert to IR .bin and .XML file.
I followed the instructions from here (https://docs.openvinotoolkit.org/latest/openvino_docs_MO_DG_prepare_model_convert_model_tf_specific_Convert_YOLO_From_Tensorflow.html ) for yolov3 and object detection worked fine however with less accuracy.
Now, I tried the procedure mentioned for yolov4 :
- Download YOLOv4 weights from yolov4.weights.
- Clone the repository with the YOLOv4 model.
content_copygit clone https://github.com/Ma-Dan/keras-yolo4.git ==========> did not work.git clone https://github.com/Runist/YOLOv4/ ==> Used this link to convert to .pb
- Convert the model to the TensorFlow 2* format. Save the code below to the
converter.py
file in the same folder as you downloadedyolov4.weights
and run it.content_copyfrom keras-yolo4.model import Mishmodel = tf.keras.models.load_model('yolo4_weight.h5', custom_objects={'Mish': Mish})tf.saved_model.save(model, 'yolov4')
- Run Model Optimizer to converter the model from the TensorFlow 2 format to an IR:
NOTE: Before you run the convertion, make sure you have installed all the Model Optimizer dependencies for TensorFlow 2.
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Hi Karthick,
Thanks for reaching out. Can I know which version of the OpenVINO toolkit you are using? Please share the screenshot of any error or issue that you got.
Regards,
Aznie
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Hi Karthick,
Thank you for your question. If you need any additional information from Intel, please submit a new question as this thread is no longer being monitored.
Regards,
Aznie
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