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Ecolite Inference for Tensorflow

This repository provides a script and recipe to Inference of the Ecolite model.

Notice

This sample only provides reference for you to learn the Ascend software stack and is not for commercial purposes.

Before starting, please pay attention to the following adaptation conditions. If they do not match, may leading in failure.

Quick Start Guide

1. Clone the respository

git clone https://gitee.com/ascend/ModelZoo-TensorFlow.git
cd Modelzoo-TensorFlow/ACL_TensorFlow/contrib/cv/Ecolite_for_ACL

2. Generate random test dataset

1. Because of this is not a well trained model we test the model with random test dataset

2. Generate random test dataset:

cd scripts
mkdir input_bins
python3 generate_random_data.py --path=./input_bins/ --nums=32

There will random testdata bin fils under input_bins/.

3. Offline Inference

Convert pb to om.

• configure the env

  Please follow the guide to set the envs

• convert pb to om

  pb download link

  atc --model=ecolite_tf_4batch.pb --framework=3 --output=ecolite_tf_4batch --output_type=FP32 --soc_version=Ascend310 --input_shape="input_tensor:4,224,224,3" --insert_op_conf=ecolite.json --enable_small_channel=1 --log=info
  

• Build the program

  bash build.sh
  

• Run the program:

  cd scripts
  bash benchmark_tf.sh
  

Performance

Result

Our result was obtained by running the applicable inference script. To achieve the same results, follow the steps in the Quick Start Guide.

Inference accuracy results