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its about running this #56
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@Rimsha7777 python3 convert_weights_pb.py \
--class_names coco.names \
--weights_file weights/yolov3-tiny.weights \
--data_format NHWC \
--tiny \
--output_graph pbmodels/frozen_tiny_yolo_v3.pb sudo python3 /opt/intel/openvino/deployment_tools/model_optimizer/mo_tf.py \
--input_model pbmodels/frozen_tiny_yolo_v3.pb \
--output_dir lrmodels/tiny-YoloV3/FP16 \
--data_type FP16 \
--batch 1 \
--tensorflow_use_custom_operations_config yolo_v3_tiny_changed.json python3 openvino_yolov3_test.py -d MYRIAD |
Thank you so much for your reply...this is indeed sounds helpful...I will
update you right after implementing .
…On Saturday, October 5, 2019, Katsuya Hyodo ***@***.***> wrote:
@Rimsha7777 <https://github.com/Rimsha7777>
Just execute the commands listed in the following file in order from the
top.
*https://github.com/PINTO0309/OpenVINO-YoloV3/blob/master/script.txt
<https://github.com/PINTO0309/OpenVINO-YoloV3/blob/master/script.txt>*
python3 convert_weights_pb.py \
--class_names coco.names \
--weights_file weights/yolov3-tiny.weights \
--data_format NHWC \
--tiny \
--output_graph pbmodels/frozen_tiny_yolo_v3.pb
sudo python3 /opt/intel/openvino/deployment_tools/model_optimizer/mo_tf.py \
--input_model pbmodels/frozen_tiny_yolo_v3.pb \
--output_dir lrmodels/tiny-YoloV3/FP16 \
--data_type FP16 \
--batch 1 \
--tensorflow_use_custom_operations_config yolo_v3_tiny_changed.json
python3 openvino_yolov3_test.py -d MYRIAD
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Hi, |
The OpenVINO installer for RaspberryPi does not include a model optimizer. So if you want to convert the model, you need a HostPC with the full version of OpenVINO installed. HostPC ex) Ubuntu Next, execute the following command on HostPC. python3 convert_weights_pb.py \
--class_names coco.names \
--weights_file weights/yolov3-tiny.weights \
--data_format NHWC \
--tiny \
--output_graph pbmodels/frozen_tiny_yolo_v3.pb sudo python3 /opt/intel/openvino/deployment_tools/model_optimizer/mo_tf.py \
--input_model pbmodels/frozen_tiny_yolo_v3.pb \
--output_dir lrmodels/tiny-YoloV3/FP16 \
--data_type FP16 \
--batch 1 \
--tensorflow_use_custom_operations_config yolo_v3_tiny_changed.json Next, copy the .bin and .xml generated on HostPC to RaspberryPi. |
Ok, thanks you so very much for helping.
…On Sunday, October 6, 2019, Katsuya Hyodo ***@***.***> wrote:
The OpenVINO installer for RaspberryPi does not include a model optimizer.
So if you want to convert the model, you need a HostPC with the full
version of OpenVINO installed.
*HostPC ex) Ubuntu*
First, download the latest OpenVINO from the following. And, install.
*https://github.com/PINTO0309/OpenVINO-bin.git
<https://github.com/PINTO0309/OpenVINO-bin.git>*
Next, execute the following command on HostPC.
python3 convert_weights_pb.py \
--class_names coco.names \
--weights_file weights/yolov3-tiny.weights \
--data_format NHWC \
--tiny \
--output_graph pbmodels/frozen_tiny_yolo_v3.pb
sudo python3 /opt/intel/openvino/deployment_tools/model_optimizer/mo_tf.py \
--input_model pbmodels/frozen_tiny_yolo_v3.pb \
--output_dir lrmodels/tiny-YoloV3/FP16 \
--data_type FP16 \
--batch 1 \
--tensorflow_use_custom_operations_config yolo_v3_tiny_changed.json
Next, copy the .bin and .xml generated on HostPC to RaspberryPi.
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[Required] Your device (RaspberryPi3, LaptopPC, or other device name):
[Required] Your device's CPU architecture (armv7l, x86_64, or other architecture name):
[Required] Your OS (Raspbian, Ubuntu1604, or other os name):
[Required] Overview of problems and questions:
can you help me how i can generate .bin and .xml files. I am just new to using NCS2. I wanted to run using PRI3+. If you help me what I have to do with model optimizer exactly with command-line-arguments, I am not getting that I just visited other issues find some with this but did not get how to do.
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