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OPENING JPEG IN GPROJECTOR HOW TO
OPENING JPEG IN GPROJECTOR PC
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OPENING JPEG IN GPROJECTOR MAC

Now, use TensorBoard to examine the image.

Tf.summary.image("Training data", img, step=0) # Using the file writer, log the reshaped image. # Creates a file writer for the log directory.įile_writer = tf.summary.create_file_writer(logdir) Logdir = "logs/train_data/" + datetime.now().strftime("%Y%m%d-%H%M%S") You're now ready to log this image and view it in TensorBoard. The images are grayscale, so set channels to 1. You're logging only one image, so batch_size is 1. Therefore, the tensors need to be reshaped. However, tf.summary.image() expects a rank-4 tensor containing (batch_size, height, width, channels). Notice that the shape of each image in the data set is a rank-2 tensor of shape (28, 28), representing the height and the width. Print("Label: ", train_labels, "->", class_names]) To understand how the Image Summary API works, you're now going to simply log the first training image in your training set in TensorBoard.īefore you do that, examine the shape of your training data: print("Shape: ", train_images.shape) # Names of the integer classes, i.e., 0 -> T-short/top, 1 -> Trouser, etc.Ĭlass_names = ['T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat', (train_images, train_labels), (test_images, test_labels) = \ # The labels are integers representing classes.įashion_mnist = _mnist The data is already divided into train and test.

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This dataset consist of 70,000 28x28 grayscale images of fashion products from 10 categories, with 7,000 images per category.įirst, download the data: # Download the data. You're going to construct a simple neural network to classify images in the the Fashion-MNIST dataset. "This notebook requires TensorFlow 2.0 or above." Print("TensorFlow version: ", tf._version_)Īssert version.parse(tf._version_).release >= 2, \ # Load the TensorBoard notebook extension. # %tensorflow_version only exists in Colab. You will work through a simple but real example that uses Image Summaries to help you understand how your model is performing.

OPENING JPEG IN GPROJECTOR HOW TO

You will also learn how to take an arbitrary image, convert it to a tensor, and visualize it in TensorBoard. In this tutorial, you will learn how to use the Image Summary API to visualize tensors as images. You can also log diagnostic data as images that can be helpful in the course of your model development. This can be extremely helpful to sample and examine your input data, or to visualize layer weights and generated tensors. After you've connected and powered on your projector click on the "Display Settings" button.Using the TensorFlow Image Summary API, you can easily log tensors and arbitrary images and view them in TensorBoard.Select the "Extend these displays" option.After you've connected to, and powered on, your projector scroll down to the "Multiple Displays" menu.

OPENING JPEG IN GPROJECTOR PC

For a PC (Note that instructions may vary slightly depending on which version of Windows you are operating):.

When you connect your projector to your computer and when your projector is powered on, your computer should automatically detect a second output.

Mac/PC only: Ensure that your monitor is extended (not mirrored) onto your projector. If your operator will be more than 50ft away from your projector, using CAT6 network cabling provides a much more reliable connection that reduces latency. If your projection operator will be cueing the projections from less than 50ft from your projector you can use a high-quality HDMI cable. Ensure that when you are changing the input of the projector with the remote that you are matching it with the port that your HDMI is plugged in to.Ĭheck your Connection Hardware - In some cases, HDMI cables that are too long and aren't sufficient quality will lose signal or won't be recognized by the projector. Typically it will say "HDMI 1" or "HDMI 2". Check the label on the port that the HDMI cable is plugged into on the projector. With your projector's remote, cycle through the input options to ensure the correct port is selected.

When in "Preview" or "Present" mode, click the "Display Fullscreen" button and the output window will resize to fill your projection.

While clicking and holding, drag the output window onto your extended display (typically by dragging it all the way left or all the way right of your desktop screen).

Click and hold the titlebar in the output window.

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Is your computer in mirroring mode? Be sure to extend your Mac or Windows computer's display onto your projector instead.Try some or all of the following, and if the content is still not displaying contact the Output Window to Projector With every setup being slightly different from the next, display errors can occur for any number of reasons. The content is not displaying on my projector.