![]() If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly. 02:38:35.373466: W tensorflow/compiler/tf2tensorrt/utils/py_:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. 02:38:35.373455: W tensorflow/compiler/xla/stream_executor/platform/default/dso_:64] Could not load dynamic library 'libnvinfer_plugin.so.7' dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory 02:38:35.373345: W tensorflow/compiler/xla/stream_executor/platform/default/dso_:64] Could not load dynamic library 'libnvinfer.so.7' dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory Use the tf.image methods, such as tf.image.flip_left_right, tf.image.rgb_to_grayscale, tf.image.adjust_brightness, tf.image.central_crop, and tf.image.stateless_random*.Use the Keras preprocessing layers, such as tf., tf., tf., and tf.You will learn how to apply data augmentation in two ways: This tutorial demonstrates data augmentation: a technique to increase the diversity of your training set by applying random (but realistic) transformations, such as image rotation. If images was 3-D, a 3-D float Tensor of shape. If images was 4-D, a 4-D float Tensor of shape. If an unsupported resize method is specified. If the shape of images is incompatible with the shape arguments to this function Whether to use an anti-aliasing filter when downsampling an image. Scales up the image if size is bigger than the current size of the image. If this is set, then images will be resized to a size that fits in size while preserving the aspect ratio of the original image. The new size for the images.Īn image.ResizeMethod, or string equivalent. Ī 1-D int32 Tensor of 2 elements: new_height, new_width. Max_10_20 = tf.image.resize(image,, preserve_aspect_ratio=True)Ĥ-D Tensor of shape or 3-D Tensor of shape. With preserve_aspect_ratio=True, the aspect ratio is preserved, so size is the maximum for each dimension: Nn = tf.image.resize(image,, method='nearest') The return value has type float32, unless the method is ResizeMethod.NEAREST_NEIGHBOR, then the return dtype is the dtype of images: For these pixels, only input pixels inside the image will be included in the filter sum, and the output value will be appropriately normalized. Note: Near image edges the filtering kernel may be partially outside the image boundaries. For synthetic images (especially those lacking proper prefiltering), less ringing than Keys cubic kernel but less sharp. ![]()
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