This example is used to demonstrate how to quantize a TensorFlow checkpoint and run with a dummy dataloader.
pip install -r requirements.txt
git clone https://github.com/openvinotoolkit/open_model_zoo.git
git checkout 2021.4
python ./open_model_zoo/tools/downloader/downloader.py --name rfcn-resnet101-coco-tf --output_dir model
python test.py
We will create a dummy dataloader and only need to add the following lines for quantization to create an int8 model.
quantizer = Quantization('./conf.yaml')
dataset = quantizer.dataset('dummy_v2', \
input_shape=(100, 100, 3), label_shape=(1, ))
quantizer.model = common.Model('./model/public/rfcn-resnet101-coco-tf/rfcn_resnet101_coco_2018_01_28/')
quantizer.calib_dataloader = common.DataLoader(dataset)
quantized_model = quantizer.fit()