结合一下，然后给我一个讲解视频---**Chart/Diagram Description:** * **Type:** Block diagram representing sequences of operations, likely modules in a neural network or processing pipeline. * **Main Elements:** * Three distinct modules are shown, enclosed in rounded rectangular outlines. * **Module 1:** Contains three rectangular blocks connected by right-pointing arrows. The blocks are labeled "Depthwise Conv2D", "Batch Normalization", and "Activation". The module is labeled "Module 1" below the outline. The outline has a light yellow background. * **Module 2:** Contains six rectangular blocks connected by right-pointing arrows, arranged horizontally. The blocks are labeled "Depthwise Conv2D", "Batch Normalization", "Activation", "Zero Padding", "Depthwise Conv2D", "Batch Normalization", and "Activation". The module is labeled "Module 2" below the outline. The outline has a light gray background. * **Module 3:** Contains four rectangular blocks connected by right-pointing arrows, arranged horizontally. The blocks are labeled "Global Average Pooling", "Rescaling", "Conv2D", and "Conv2D". The module is labeled "Module 3" below the outline. The outline has a light pink background. * **Blocks:** Each block is a colored rectangle with text labels inside. Colors used are red ("Depthwise Conv2D", "Conv2D"), blue ("Batch Normalization"), purple ("Activation"), green ("Zero Padding"), orange ("Global Average Pooling"), and yellow ("Rescaling"). * **Arrows:** Black arrows connect the blocks, indicating the direction of flow from left to right within each module. * **Labels:** Text labels are present within the blocks (operation names) and below the module outlines (module names). **Textual Information:** * **Module 1:** * Depthwise Conv2D -> Batch Normalization -> Activation * Label: Module 1 * **Module 2:** * Depthwise Conv2D -> Batch Normalization -> Activation -> Zero Padding -> Depthwise Conv2D -> Batch Normalization -> Activation * Label: Module 2 * **Module 3:** * Global Average Pooling -> Rescaling -> Conv2D -> Conv2D * Label: Module 3 **Diagram Description:** * Type: Flowchart or Neural Network Architecture Diagram. * Layout: Arranged horizontally as a sequence of blocks labeled Block 1 through Block 7, with data flow generally from left to right. There are also final layers after Block 7. * Elements: The diagram consists of various rectangular shapes with rounded corners, representing processing steps or modules (labeled Stem, conv, Module 1, Module 2, Module 3, Add, upsample, Final layers). These shapes have different background colors (pink, orange, blue, yellow, green). * Connections: Directed arrows indicate the flow of data between elements. Some arrows show sequential processing, while others represent skip connections bypassing one or more steps. **Textual Content and Structure:** * **Overall Structure:** Blocks are labeled Block 1, Block 2, Block 3, Block 4, Block 5, Block 6, Block 7. The diagram starts with 'Stem' and ends with 'Final layers'. * **Block 1:** * Contains: Stem, conv, Module 1, Module 3, Add. * Connections: * Stem -> conv * conv -> Module 1 * Module 1 -> Module 3 * Module 3 -> Add * Stem -> Add (skip connection) * **Block 2, Block 3, Block 4, Block 5, Block 6:** (These blocks share the same internal structure) * Each contains: Module 2, two instances of Module 3, two instances of Add. * Connections within this structure: * Input from previous block -> Module 2 * Module 2 -> Module 3 (first instance) * Module 3 (first instance) -> Add (first instance) * Input from previous block -> Add (first instance) (skip connection) * Add (first instance) -> Module 3 (second instance) * Module 3 (second instance) -> Add (second instance) * Add (first instance) -> Add (second instance) (skip connection) * Output of Add (second instance) -> next block * **Block 7:** * Contains: Module 2, Module 3, Add. * Connections within this structure: * Input from previous block -> Module 2 * Module 2 -> Module 3 * Module 3 -> Add * Input from previous block -> Add (skip connection) * **Final Layers:** * Contains: upsample, conv, Final layers. * Connections: * Output of Add in Block 7 -> upsample * upsample -> conv * conv -> Final layers * **Connections between Blocks:** * Output of Add in Block 1 connects to the input of Block 2 (connecting to Module 2 and the first Add). * Output of Add (second instance) in Block 2 connects to the input of Block 3 (connecting to Module 2 and the first Add). * Output of Add (second instance) in Block 3 connects to the input of Block 4 (connecting to Module 2 and the first Add). * Output of Add (second instance) in Block 4 connects to the input of Block 5 (connecting to Module 2 and the first Add). * Output of Add (second instance) in Block 5 connects to the input of Block 6 (connecting to Module 2 and the first Add). * Output of Add (second instance) in Block 6 connects to the input of Block 7 (connecting to Module 2 and the Add). * **Annotations:** * `x3` (red text) is located below the arrow connecting the output of Block 4 (second Add) to the input of Block 5. * `x3` (red text) is located below the arrow connecting the output of Block 5 (second Add) to the input of Block 6. * `x4` (red text) is located below the arrow connecting the output of Block 6 (second Add) to the input of Block 7.