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