|  |  | @ -8,7 +8,7 @@ To view the architecture of the ONNX networks, you can use [netron](https://netr | 
			
		
	
		
		
			
				
					
					|  |  |  |     * Each 256 * 512 image is represented in YUV420 with 6 channels : 6 * 128 * 256 |  |  |  |     * Each 256 * 512 image is represented in YUV420 with 6 channels : 6 * 128 * 256 | 
			
		
	
		
		
			
				
					
					|  |  |  |       * Channels 0,1,2,3 represent the full-res Y channel and are represented in numpy as Y[::2, ::2], Y[::2, 1::2], Y[1::2, ::2], and Y[1::2, 1::2] |  |  |  |       * Channels 0,1,2,3 represent the full-res Y channel and are represented in numpy as Y[::2, ::2], Y[::2, 1::2], Y[1::2, ::2], and Y[1::2, 1::2] | 
			
		
	
		
		
			
				
					
					|  |  |  |       * Channel 4 represents the half-res U channel |  |  |  |       * Channel 4 represents the half-res U channel | 
			
		
	
		
		
			
				
					
					|  |  |  |       * Channel 4 represents the half-res V channel |  |  |  |       * Channel 5 represents the half-res V channel | 
			
				
				
			
		
	
		
		
	
		
		
			
				
					
					|  |  |  | * **desire** |  |  |  | * **desire** | 
			
		
	
		
		
			
				
					
					|  |  |  |   * one-hot encoded vector to command model to execute certain actions, bit only needs to be sent for 1 frame : 8 |  |  |  |   * one-hot encoded vector to command model to execute certain actions, bit only needs to be sent for 1 frame : 8 | 
			
		
	
		
		
			
				
					
					|  |  |  | * **traffic convention** |  |  |  | * **traffic convention** | 
			
		
	
	
		
		
			
				
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