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Keeping your digital photography neat Photoshop doesn’t come with any type of organizing or management functions. However, you can manage your images in the way that works best for you. For example, if you’re working with images, especially digital photos, then you’ve probably realized that lots of new images tend to grow and grow until you have a digital scrapbook of all the holidays, vacations, and so on. The problem is that your hard drive is full of digital images, and the images
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The new version of Photoshop Elements for MacBook (for macOS Mojave and Catalina) was recently released. The version 16.0 update has a lot of changes, and we have already shared with you a number of In addition to the usual bug fixes, new tools, performance boosts and stability, it also offers several new features. Below you can learn more about them. Separation of Elements The first way to immediately notice the update is an easy way to Separation of Elements. This function allows you to separate a layer or a group of layers without having to copy them. It is essential when you need to change the color or size of a group of layers. For example, if you have a group of layers made with a pattern stamp, you may want to change the colors or the size of the entire group. You can implement separation of Elements on all your layers or only a specific group of layers. New Morphology editor Introduced in PS3 version 16, a new Morphology editor, The Morphology tool is a set of tools to edit the physical properties of a mesh. You can use this function to convert a regular mesh into a procedural mesh (e.g., a procedural ragdoll) or to repair imperfections (e.g., an eyebrow). Essential reading: New element size (field size) This new feature allows you to change the size of elements in a field. There are two tabs, one for vertical and one for horizontal elements. New built-in texture and camera RAW formats Also in version 16, a new built-in texture format and a new camera RAW format have been added. The format has an improved color space, and you can import and export them with a few mouse clicks or by copying and pasting to and from another editor. And finally a new option is available in the Preferences section The Color Management mode is now off by default. But you can activate it in the Preferences menu. New perspective view In PS3 version 16, you can define a new perspective view. This allows you to create a new perspective view in the same way as you would create a standard view in the previous versions. The following image gives a graphical example of a new perspective view. Spot Healing Brush The Spot Healing Brush tool allows you to identify and fix the 388ed7b0c7
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Q: SVM training model with a huge amount of features Hi guys I have an issue training a SVM with high dimensional feature vectors. Even though I saw some SO threads about this, when I start my training, it seems that SVM returns always the same low accuracy, even if I train with a different dataset. I’m using SVC and in each iteration I evaluate my model with: from sklearn.externals import joblib training_model = joblib.load(‘training_model’) testing_model = joblib.load(‘testing_model’) testing_model.fit(y_train, x_train) training_model.fit(y_test, x_test) Obviously y_train and y_test are vectors of 1 and 0, respectively. I used to train my model (which returned always very low accuracy) with the following process in a loop: X_train = some train/validation dataset # Use this instruction to transform float to integer (float values are not # always integers) X_train = X_train.astype(‘int’) # vectorize the dataset X_train = X_train.astype(‘float’) X_train = X_train.reshape(-1, 2800) # my features are vectors X_train = X_train.transpose() # normalize the dataset X_train = X_train.astype(‘float’) X_train = sklearn.preprocessing.normalize(X_train) # reduce the dataset size by removing rows with all 0s (this depends on # the data distribution) X_train.shape # does not work #try: #X_train.shape #X_train = X_train[np.nonzero(X_train > 0.0)] # add all the features of each row to a single vector, of float # each sample is a row in the input matrix X_train_single_vector = np.array([x1, x2, x3,…, xn], dtype=float) # create a matrix like X_train_single_vector[:,ncol] X_train_single_vector =
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Lopavitra Lopavitra or lopaviteera, is a type of cooking utensil used in South India. It is used for cooking bitter, spicy, or green chutneys. Though the word lopaviteera literally means “berry picker” in Telugu, the term is also used for a kitchen utensil having an outer shell with a semicircular mouth and a handle. The word is used for a kitchen utensil in many parts of the world: Malayalam lopamvitra (literal translation: small pot) means a small pot or pan in Kerala; Indian lopamvitra refers to a pan or skillet in general. Characteristics The lopaviteera has a bowl-shaped body with a semicircular mouth and with handles. A flat cover is lifted off the mouth when the utensil is in use. The lopaviteera bowl is either glued or fitted in a base with a circular opening with a diameter of about 7 to 8 centimeters. The base is fitted on a flat metal top or a base pad. The bowl has a bottom with a diameter of about 3 to 4 centimeters and diameter of the semicircle of the mouth is 6 to 7 centimeters. The top of the base is fitted with a groove for a metal plate to sit over it. A lopaviteera for chutney, tamarind, or jaggery is made in various sizes from 5 centimeters to 18 centimeters in diameter. The larger lopaviteera is used for bitter or spicy chutneys such as tamarind and jaggery. Smaller lopaviteeras are used to cook less bitter chutneys such as coconut or mango. The size of lopaviteera is customized according to the quantity of chutney required. Lopaviteera are also available in a combination of two for cooking both dry and wet chutney. References Category:Indian cooking toolsThere are various medical procedures used to create an opening through soft tissue to facilitate the passage of an instrument through the tissue, and in particular, to allow a percutaneous passage through tissue such as soft tissue, for example, tissue in the center of the chest wall, in the abdomen, and in the back of the human body. An example of one such procedure is a standard thoracotomy used to resect a
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