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{
    "id": 22309,
    "url": "https://patchwork.libcamera.org/api/1.1/patches/22309/?format=api",
    "web_url": "https://patchwork.libcamera.org/patch/22309/",
    "project": {
        "id": 1,
        "url": "https://patchwork.libcamera.org/api/1.1/projects/1/?format=api",
        "name": "libcamera",
        "link_name": "libcamera",
        "list_id": "libcamera_core",
        "list_email": "libcamera-devel@lists.libcamera.org",
        "web_url": "",
        "scm_url": "",
        "webscm_url": ""
    },
    "msgid": "<20241213094602.2083174-5-naush@raspberrypi.com>",
    "date": "2024-12-13T09:38:27",
    "name": "[4/6] controls: ipa: rpi: Add CNN controls",
    "commit_ref": null,
    "pull_url": null,
    "state": "superseded",
    "archived": false,
    "hash": "c22c8de3cb75ccba0304c80ce88eb833ddf386d3",
    "submitter": {
        "id": 34,
        "url": "https://patchwork.libcamera.org/api/1.1/people/34/?format=api",
        "name": "Naushir Patuck",
        "email": "naush@raspberrypi.com"
    },
    "delegate": null,
    "mbox": "https://patchwork.libcamera.org/patch/22309/mbox/",
    "series": [
        {
            "id": 4881,
            "url": "https://patchwork.libcamera.org/api/1.1/series/4881/?format=api",
            "web_url": "https://patchwork.libcamera.org/project/libcamera/list/?series=4881",
            "date": "2024-12-13T09:38:23",
            "name": "Raspberry Pi: Various changes",
            "version": 1,
            "mbox": "https://patchwork.libcamera.org/series/4881/mbox/"
        }
    ],
    "comments": "https://patchwork.libcamera.org/api/patches/22309/comments/",
    "check": "pending",
    "checks": "https://patchwork.libcamera.org/api/patches/22309/checks/",
    "tags": {},
    "headers": {
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        "From": "Naushir Patuck <naush@raspberrypi.com>",
        "To": "libcamera-devel@lists.libcamera.org",
        "Cc": "Naushir Patuck <naush@raspberrypi.com>",
        "Subject": "[PATCH 4/6] controls: ipa: rpi: Add CNN controls",
        "Date": "Fri, 13 Dec 2024 09:38:27 +0000",
        "Message-ID": "<20241213094602.2083174-5-naush@raspberrypi.com>",
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    },
    "content": "Add the follwing RPi vendor controls to handle Convolutional Neural\nNetwork processing:\n\nCnnOutputTensor\nCnnOutputTensorInfo\nCnnEnableInputTensor\nCnnInputTensor\nCnnInputTensorInfo\nCnnKpiInfo\n\nThese controls will be used to support the new Raspberry Pi AI Camera,\nusing an IMX500 sensor with on-board neural network processing.\n\nSigned-off-by: Naushir Patuck <naush@raspberrypi.com>\n---\n src/ipa/rpi/controller/controller.h |  33 +++++++++\n src/libcamera/control_ids_rpi.yaml  | 108 ++++++++++++++++++++++++++++\n 2 files changed, 141 insertions(+)",
    "diff": "diff --git a/src/ipa/rpi/controller/controller.h b/src/ipa/rpi/controller/controller.h\nindex 64f93f414524..489188b44d9b 100644\n--- a/src/ipa/rpi/controller/controller.h\n+++ b/src/ipa/rpi/controller/controller.h\n@@ -25,6 +25,39 @@\n \n namespace RPiController {\n \n+/*\n+ * The following structures are used to export the CNN input/output tensor information\n+ * through the rpi::CnnOutputTensorInfo and rpi::CnnInputTensorInfo controls.\n+ * Applications must cast the span to these structures exactly.\n+ */\n+static constexpr unsigned int NetworkNameLen = 64;\n+static constexpr unsigned int MaxNumTensors = 16;\n+static constexpr unsigned int MaxNumDimensions = 16;\n+\n+struct OutputTensorInfo {\n+\tuint32_t tensorDataNum;\n+\tuint32_t numDimensions;\n+\tuint16_t size[MaxNumDimensions];\n+};\n+\n+struct CnnOutputTensorInfo {\n+\tchar networkName[NetworkNameLen];\n+\tuint32_t numTensors;\n+\tOutputTensorInfo info[MaxNumTensors];\n+};\n+\n+struct CnnInputTensorInfo {\n+\tchar networkName[NetworkNameLen];\n+\tuint32_t width;\n+\tuint32_t height;\n+\tuint32_t numChannels;\n+};\n+\n+struct CnnKpiInfo {\n+\tuint32_t dnnRuntime;\n+\tuint32_t dspRuntime;\n+};\n+\n class Algorithm;\n typedef std::unique_ptr<Algorithm> AlgorithmPtr;\n \ndiff --git a/src/libcamera/control_ids_rpi.yaml b/src/libcamera/control_ids_rpi.yaml\nindex 34bbdfc863c5..c0b5f63df525 100644\n--- a/src/libcamera/control_ids_rpi.yaml\n+++ b/src/libcamera/control_ids_rpi.yaml\n@@ -55,4 +55,112 @@ controls:\n         official libcamera API support for per-stream controls in the future.\n \n         \\sa ScalerCrop\n+\n+  - CnnOutputTensor:\n+      type: float\n+      size: [n]\n+      description: |\n+        This control returns a span of floating point values that represent the\n+        output tensors from a Convolutional Neural Network (CNN). The size and\n+        format of this array of values is entirely dependent on the neural\n+        network used, and further post-processing may need to be performed at\n+        the application level to generate the final desired output. This control\n+        is agnostic of the hardware or software used to generate the output\n+        tensors.\n+\n+        The structure of the span is described by the CnnOutputTensorInfo\n+        control.\n+\n+        \\sa CnnOutputTensorInfo\n+\n+  - CnnOutputTensorInfo:\n+      type: uint8_t\n+      size: [n]\n+      description: |\n+        This control returns the structure of the CnnOutputTensor. This structure\n+        takes the following form:\n+\n+        constexpr unsigned int NetworkNameLen = 64;\n+        constexpr unsigned int MaxNumTensors = 16;\n+        constexpr unsigned int MaxNumDimensions = 16;\n+\n+        struct CnnOutputTensorInfo {\n+          char networkName[NetworkNameLen];\n+          uint32_t numTensors;\n+          OutputTensorInfo info[MaxNumTensors];\n+        };\n+\n+        with\n+\n+        struct OutputTensorInfo {\n+          uint32_t tensorDataNum;\n+          uint32_t numDimensions;\n+          uint16_t size[MaxNumDimensions];\n+        };\n+\n+        networkName is the name of the CNN used,\n+        numTensors is the number of output tensors returned,\n+        tensorDataNum gives the number of elements in each output tensor,\n+        numDimensions gives the dimensionality of each output tensor,\n+        size gives the size of each dimension in each output tensor.\n+\n+        \\sa CnnOutputTensor\n+\n+  - CnnEnableInputTensor:\n+      type: bool\n+      description: |\n+        Boolean to control if the IPA returns the input tensor used by the CNN\n+        to generate the output tensors via the CnnInputTensor control. Because\n+        the input tensor may be relatively large, for efficiency reason avoid\n+        enabling input tensor output unless required for debugging purposes.\n+\n+        \\sa CnnInputTensor\n+\n+  - CnnInputTensor:\n+       type: uint8_t\n+       size: [n]\n+       description: |\n+        This control returns a span of uint8_t pixel values that represent the\n+        input tensor for a Convolutional Neural Network (CNN). The size and\n+        format of this array of values is entirely dependent on the neural\n+        network used, and further post-processing (e.g. pixel normalisations) may\n+        need to be performed at the application level to generate the final input\n+        image.\n+\n+        The structure of the span is described by the CnnInputTensorInfo\n+        control.\n+\n+        \\sa CnnInputTensorInfo\n+\n+  - CnnInputTensorInfo:\n+      type: uint8_t\n+      size: [n]\n+      description: |\n+        This control returns the structure of the CnnInputTensor. This structure\n+        takes the following form:\n+\n+        constexpr unsigned int NetworkNameLen = 64;\n+\n+        struct CnnInputTensorInfo {\n+          char networkName[NetworkNameLen];\n+          uint32_t width;\n+          uint32_t height;\n+          uint32_t numChannels;\n+        };\n+\n+        where\n+\n+        networkName is the name of the CNN used,\n+        width and height are the input tensor image width and height in pixels,\n+        numChannels is the number of channels in the input tensor image.\n+\n+        \\sa CnnInputTensor\n+\n+  - CnnKpiInfo:\n+      type: int32_t\n+      size: [2]\n+      description: |\n+        This control returns performance metrics for the CNN processing stage.\n+        Two values are returned in this span, the runtime of the CNN/DNN stage\n+        and the DSP stage in milliseconds.\n ...\n",
    "prefixes": [
        "4/6"
    ]
}