a TensorFlow Lite classifier model that identifies what is in the image. Up to three results with the highest confidence returned by the classifier are shown on the screen, if there is an attached display. Also, the result is spoken out loud using Text-To-Speech to the default audio output...
Image classification with NVIDIA TensorRT from TensorFlow models. - NVIDIA-AI-IOT/tf_to_trt_image_classification
TensorFlowis a well established, open source machine learning and deep learning framework that can be used to create and run a wide range of different models, usually using powerful machines in the cloud. In addition, TensorFlow also supports running models on mobile devices through theTensorFlow.M...
TF-slim is a new lightweight high-level API of TensorFlow (tensorflow.contrib.slim) for defining, training and evaluating complex models. This directory contains code for training and evaluating several widely used Convolutional Neural Network (CNN) image classification models using TF-slim. It conta...
git clone https://github.com/Azure/azureml-examples.git Understand the code The code for this tutorial uses TensorFlow to train an image classification machine learning model that categorizes handwritten digits from 0-9. It does so by creating a neural network that takes the pixel val...
Deep learning– FAST provides a common interface for neural networks supporting different model formats (ONNX, protobuf, SavedModel, OpenVINO, UFF) and backends (Google TensorFlow, NVIDIA TensorRT, Intel OpenVINO, Microsoft ONNX Runtime), making it possible to create real-time neural network pipeli...
Using a simulated optical convolution with this phase mask, the classification model achieves a test accuracy of 70.1%, comparable to the accuracy of digital convolution with the target tiled kernels. These results suggest that the opt-conv layer is able to learn behavior similar to a digital ...
Download the inference YOLOv4(tiny) TensorFlow Lite model Go to https://github.com/Azure/live-video-analytics and download zip in your local machine. Go to the following path in the downloaded folder. Copy live-video-analytics-master/utilities/video-analysis/yolov4-tfli...
=tf.image.random_flip_left_right(distorted_image)#Because these operations are not commutative, consider randomizing#the order their operation.#NOTE: since per_image_standardization zeros the mean and makes#the stddev unit, this likely has no effect see tensorflow#1458.distorted_image =tf.image....
To train the discriminator, first the generator generates an output image. The discriminator looks at the input/target pair and the input/output pair and produces its guess about how realistic they look. The weights of the discriminator are then adjusted based on the classification error of the ...