Latest docker image: error: unrecognized arguments
MaHoef opened this issue · 7 comments
Hello Pinto,
I am following the tutorial form here:
https://github.com/geaxgx/openvino_hand_tracker
Can it be that in the latest docker version the API has changed?
This is what I do:
marco@CHROTZ:/tmp/depthai_hand_tracker$ docker run --gpus all -it --rm
-v pwd
:/workspace/resources
-e LOCAL_UID=$(id -u $USER)
-e LOCAL_GID=$(id -g $USER)
pinto0309/tflite2tensorflow:latest bash
NVIDIA Release 20.09 (build 15985252)
NVIDIA TensorRT 7.1.3 (c) 2016-2020, NVIDIA CORPORATION. All rights reserved.
Container image (c) 2020, NVIDIA CORPORATION. All rights reserved.
https://developer.nvidia.com/tensorrt
To install Python sample dependencies, run /opt/tensorrt/python/python_setup.sh
To install open source parsers, plugins, and samples, run /opt/tensorrt/install_opensource.sh. See https://github.com/NVIDIA/TensorRT for more information.
error: XDG_RUNTIME_DIR not set in the environment.
[setupvars.sh] OpenVINO environment initialized
wget https://github.com/google/mediapipe/blob/master/mediapipe/modules/hand_landmark/hand_landmark.tflite
wget https://github.com/google/mediapipe/blob/master/mediapipe/modules/palm_detection/palm_detection.tflite
tflite2tensorflow --model_path ./hand_landmark.tflite --model_output_path palm_detection --flatc_path /home/user/flatc --schema_path /home/user/schema.fbs --output_pb True
tflite2tensorflow: error: unrecognized arguments: True
tflite2tensorflow --model_path ./hand_landmark.tflite --model_output_path palm_detection --flatc_path /home/user/flatc --schema_path /home/user/schema.fbs --output_pb
output json command = /home/user/flatc -t --strict-json --defaults-json -o . /home/user/schema.fbs -- ./hand_landmark.tflite
/home/user/flatc: error: binary "./hand_landmark.tflite" does not have expected file_identifier "TFL3", use --raw-binary to read this file anyway.
Thanks
Marco
You have issued a Pull Request to the repository you are referring to.
Hi Pinto,
thanks for the quick replay.
I have seen the command line change.
However, I still can't convert the google models to TF as the tool claims: does not have expected file_identifier "TFL3"
I don't need the openvino outputs. My intention is to use a TF float model, convert it to the h5 format and use the Xilinx compiler with it.
I'm going to bed now since it's late at night today, but I'll check tomorrow. I'm not sure, but updating to tf-nightly might work.
@MaHoef
To generate .h5, which is very old and officially deprecated, a special procedure is required; to generate saved_model, it can be easily converted without any particular error. I don't know the specifics of Xilinx compiler, but I would not recommend using .h5.
$ docker run -it --rm \
-v `pwd`:/home/user/workdir \
--net=host \
--privileged \
pinto0309/openvino2tensorflow:latest
$ cd workdir
$ wget https://github.com/google/mediapipe/blob/master/mediapipe/modules/hand_landmark/hand_landmark.tflite
$ tflite2tensorflow \
--model_path hand_landmark.tflite \
--flatc_path ../flatc \
--schema_path ../schema.fbs \
--output_pb
$ tflite2tensorflow \
--model_path hand_landmark.tflite \
--flatc_path ../flatc \
--schema_path ../schema.fbs \
--output_no_quant_float32_tflite
$ $INTEL_OPENVINO_DIR/deployment_tools/model_optimizer/mo_tf.py \
--saved_model_dir saved_model \
--output_dir saved_model/openvino/FP32
$ openvino2tensorflow \
--model_path saved_model/openvino/FP32/saved_model.xml \
--output_h5
- hand_landmark.tflite to .h5 converted model / .pb / saved_model / float32 tflite
https://drive.google.com/file/d/16TTLpcZxl-llunxSJc2zQ42LSnoZSWEw/view?usp=sharing
Hello Pinto,
thanks for the hint with the old format. Even for tf2 Xilinx uses this format:
vai_c_tensorflow2 -m ./tf2_resnet50_imagenet_224_224_7.76G_1.3/quantized/quantized.h5 -a ./arch.json -n resnet50
Thanks for providing the files via google drive, really nice from you.
I tried to reproduce exactly what you did. Very strange as I still get the error:
../flatc: error: binary "hand_landmark.tflite" does not have expected file_identifier "TFL3"
I attached the full log, maybe you have an idea
tflite2tensorflow.log
Can you successfully visualize the tflite file you downloaded with the tool at the URL below? There is a good chance that the file you downloaded is corrupt.
https://netron.app/
You were absolutely right, the image was corrupt. Wget is not the tool to download something from github.
It works now as expected.
I will proceed now to get the converted model compiled by the Xilinx tools which might be a challenge.
Thank you
Marco