Keyshape masking5/24/2023 ![]() Clicking this will overlay a circular shape mask atop your clip in the Viewer.Clicking this icon will reveal 2 options, the first of which is Add Shape Mask.It only appears when your mouse cursor is over it. ![]() At the top of those effect controls, to the right of the effect’s name, there is a small icon that looks like an oval inside a rectangle. Whenever you add an effect to a clip in Final Cut Pro, controls for that effect will appear in the Inspector. There are 2 main tools for creating masks in Final Cut Pro: Shape Mask effect, which can be accessed in the Inspector, and Draw Mask which is available in the Effects Browser. Another example is creating an artificial spotlight by applying the Brighten effect in a circular mask focused on your subject. For example, you could draw a mask over a TV screen in the background and then overlay your own video content to appears like it’s on the TV. This omission can be used for a variety of creative purposes. When you create a mask, you tell FCPX to omit a spatial portion of your video. Part 1: Learn Basic Masking in Final Cut Pro Part 3: 3 Cool Ways to Use Masks in Final Cut Pro.Part 1: Learn Basic Masking in Final Cut Pro.Or that consume the mask associated with the inputs. You can easily write layers that modify the current mask, that generate a new mask,.When using layers in a standalone way, you can pass the mask arguments to layers.In the Functional API and Sequential API, mask information is propagated.Some layers are mask-consumers: they expose a mask argument in their _call_.(if mask_zero=True), and so can the Masking layer. Some layers are mask-generators: Embedding can generate a mask from input values."Masking" is how layers are able to know when to skip / ignore certain timesteps in.That is all you need to know about padding & masking in Keras. Model ( inputs, outputs ) y = model ( np. Dense ( 1 )( x ) outputs = TemporalSoftmax ()( x ) model = keras. Embedding ( input_dim = 10, output_dim = 32, mask_zero = True )( inputs ) x = layers. Input ( shape = ( None ,), dtype = "int32" ) x = layers. reduce_sum ( inputs * broadcast_float_mask, axis = 1, keepdims = True ) return inputs_exp / inputs_sum inputs = keras. exp ( inputs ) * broadcast_float_mask inputs_sum = tf. cast ( mask, "float32" ), - 1 ) inputs_exp = tf. Layer ): def call ( self, inputs, mask = None ): broadcast_float_mask = tf. Here is an example of a TemporalSplit layer that needs to modify the current mask.Ĭlass TemporalSoftmax ( keras. Produces a new mask given the input and the current mask. To do this, your layer should implement the pute_mask() method, which Need to modify the current mask so that downstream layers will be able to properly Input, such as a Concatenate layer that concatenates on the time dimension, will Layers that need to modify the current mask.įor instance, any layer that produces a tensor with a different time dimension than its Sometimes, you may need to write layers that generate a mask (like Embedding), or Receive a mask, which means it will ignore padded values: Mask corresponding to an input and pass it to any layer that knows how to use it.įor instance, in the following Sequential model, the LSTM layer will automatically Or Masking layer will be propagated through the network for any layer that isĬapable of using them (for example, RNN layers). ![]() When using the Functional API or the Sequential API, a mask generated by an Embedding Mask propagation in the Functional API and Sequential API The corresponding timestep should be ignored during processing. ![]() (batch_size, sequence_length), where each individual False entry indicates that ], shape=(3, 6), dtype=bool)Īs you can see from the printed result, the mask is a 2D boolean tensor with shape
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