There are some modes in images, the mode of an image defines the type and depth of a pixel in the image. In this tutorial, we will list all modes supported by python pillow.
Python pillow support many image modes. One image contains one mode, this mode can be got and converted to others. In this tutorial, we will introduce you how to get image mode and convert it to others.
In this tutorial, we will introduce how to compress a pdf file in python. The best way to compress a pdf file is use other application to compress pdf file using python. For example: Use python call ghostscript.
Matplotlib plt.subplot() function can allow us to display some graphics in one figure. In this tutorial, we will introdue how to use this function by using some examples.
TensorFlow tf.add_n() and tf.reduce_sum() can add tensors. However, there are some differences between them. In this tutorial, we will discuss this topic.
TensorFlow can allow us to multiply tensors. We can use * or tf.multiply(). We also can multiply tensors of different shapes in tensorflow. We will discuss this topic in this tutorial.
TensorFlow tf.add_n() function can allow us to add a list of tensors. In this tutorial, we will introduce how to use this function using some examples.
Accuracy and F1 measure are two important metrics to evaluate the performance of deep learning model. In this tutorial, we will introduce how to calculate F1-Measure with masking in tensorflow.
Accuracy is an important metrics to evaluate the ai model. In this tutorial, we will introduce how to calculate accuracy with maksing in TensorFlow.
Sigmoid cross-entropy loss is also often used in deep learning mode. In this tutorial, we will introduce how to compute sigmoid cross-entropy loss with masking in tensorflow.