Flower_classification_vai_tf_dataset
The project show how to quick train a model and deploy it on Xilinx FPGA using TensorFlow and Vitis AI. It uses tf.data.Dataset API to handle input data, so that the input function need to be rewritten. And there is a backup for DNNDK 3.1 tag
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| Flower_classification_vai_tf_numpy_array | 10 | 4 years ago | 1 | mit | C++ | |||||
| The project is a simple example about how to use TensorFlow to train a ConNet model from labeled dataset and then use Vitis AI tools to deploy the model into Xilinx FPGA(ZCU102 board). To make it easier to deploy with Vitis AI. I just use numpy array as input data and OpenCV function to open images. And there is backup for DNNDK3.1 tag | ||||||||||
| Flower_classification_vai_tf_dataset | 6 | 4 years ago | mit | C++ | ||||||
| The project show how to quick train a model and deploy it on Xilinx FPGA using TensorFlow and Vitis AI. It uses tf.data.Dataset API to handle input data, so that the input function need to be rewritten. And there is a backup for DNNDK 3.1 tag | ||||||||||
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Python
Dataset
Tensorflow
Artificial Intelligence
Deployment
Fpga