modulesettings.json

{
  "Modules": {

    "ObjectDetectionYoloRKNN": {
      "Name": "Object Detection (YOLOv5 RKNN)",
      "Version": "1.9.1",

      "PublishingInfo" : {
        "Description": "Provides Object Detection using YOLOv5 RKNN models. This module only works with Rockchip RK3588/RK3588S NPUs like the Orange Pi 5/5B/5 Plus",
        "IconURL": null,
        "Category": "Computer Vision",
        "Stack": "Python, FastDeploy, YOLO",
        "License": "Apache-2.0",
        "LicenseUrl": "https://opensource.org/licenses/Apache-2.0",
        "Author": "Mike Lud",
        "Homepage": null,
        "BasedOn": null,
        "BasedOnUrl": null
      },

      "LaunchSettings": {
        "AutoStart": true,
        "FilePath": "objectdetection_fd_rknn_adapter.py",
        "Runtime": "python3.9",
        "RuntimeLocation": "Local",       // Can be Local, Shared or System
        "PostStartPauseSecs": 1,          // Generally 1 if using GPU, 0 for CPU
        "Queue": "objectdetection_queue", // We make all Object detectors use the same queue.
        "Parallelism": 1                  // 0 = Default = number of CPUs / 2
      },

      "EnvironmentVariables": {
        "MODELS_DIR": "%CURRENT_MODULE_PATH%/assets",
        "CUSTOM_MODELS_DIR": "%CURRENT_MODULE_PATH%/custom-models",
        "MODEL_SIZE": "Small"
      },
      
      "GpuOptions" : {
        "InstallGPU": true,
        "EnableGPU": true,                // Will be coerced to false if InstallGPU = false
        "AcceleratorDeviceName": null,    // = default
        "HalfPrecision": "enable"         // 'Force', 'Enable', 'Disable': whether to force on, allow, or disable half-precision ops
      },

      "InstallOptions" : {
        "Platforms":      [ "orangepi", "radxarock" ], // The platforms this module can and cannot be installed on
       "ModuleReleases": [               // Which server version is compatible with each version of this module.
          { "ModuleVersion": "1.0",   "ServerVersionRange": [ "2.1",   "2.1.12" ], "ReleaseDate": "2023-08-06" },
          { "ModuleVersion": "1.1",   "ServerVersionRange": [ "2.1",   "2.1.12" ], "ReleaseDate": "2023-08-06", "ReleaseNotes": "Corrected installer in docker environment" },
          { "ModuleVersion": "1.2",   "ServerVersionRange": [ "2.2",   "2.2.4"  ], "ReleaseDate": "2023-09-09", "ReleaseNotes": "Updated installer" },
          { "ModuleVersion": "1.3",   "ServerVersionRange": [ "2.2",   "2.2.4"  ], "ReleaseDate": "2023-09-16", "ReleaseNotes": "Updates to help Blue Iris users" },
          { "ModuleVersion": "1.4",   "ServerVersionRange": [ "2.3.0", "2.3.0"  ], "ReleaseDate": "2023-10-01", "ReleaseNotes": "Updated to match new installer SDK." },
          { "ModuleVersion": "1.4.1", "ServerVersionRange": [ "2.3.1", "2.3.5"  ], "ReleaseDate": "2023-10-10", "ReleaseNotes": "Updated to match new installer SDK." },
          { "ModuleVersion": "1.4.2", "ServerVersionRange": [ "2.3.5", "2.3.4"  ], "ReleaseDate": "2023-11-10", "ReleaseNotes": "Updated installer", "Importance": "Minor" },
          { "ModuleVersion": "1.4.3", "ServerVersionRange": [ "2.4.1", "2.4.1"  ], "ReleaseDate": "2023-12-06", "ReleaseNotes": "Updated modulesettings schema", "Importance": "Minor" },
          { "ModuleVersion": "1.4.4", "ServerVersionRange": [ "2.4.2", "2.4.7"  ], "ReleaseDate": "2023-12-09", "ReleaseNotes": "Installer updates", "Importance": "Minor" },
          { "ModuleVersion": "1.5.0", "ServerVersionRange": [ "2.5.0-RC1", "2.5.0-RC6" ], "ReleaseDate": "2024-01-06", "ReleaseNotes": "Additions for dynamic explorer UI" },
          { "ModuleVersion": "1.5.1", "ServerVersionRange": [ "2.5.0-RC1", "2.5.0-RC5" ], "ReleaseDate": "2024-01-13", "ReleaseNotes": "Changes to SDK" },
          { "ModuleVersion": "1.5.2", "ServerVersionRange": [ "2.5.0-RC6", ""   ], "ReleaseDate": "2024-01-16", "ReleaseNotes": "Updated modulesettings schema" },
          { "ModuleVersion": "1.5.3", "ServerVersionRange": [ "2.5.0-RC6", ""   ], "ReleaseDate": "2024-01-18", "ReleaseNotes": "Updated explorer" },
          { "ModuleVersion": "1.6.0", "ServerVersionRange": [ "2.5.0-RC6", ""   ], "ReleaseDate": "2024-01-21", "ReleaseNotes": "Module performance statistics added" },
          { "ModuleVersion": "1.6.1", "ServerVersionRange": [ "2.5.2", "2.6.0"  ], "ReleaseDate": "2024-02-08", "ReleaseNotes": "Support for CodeProject.AI Server 2.5.2" },
          { "ModuleVersion": "1.6.2", "ServerVersionRange": [ "2.5.2", "2.6.0"  ], "ReleaseDate": "2024-04-20", "ReleaseNotes": "Support for Radxa ROCK hardware" },
          { "ModuleVersion": "1.7.0", "ServerVersionRange": [ "2.6.5", "2.7.0"  ], "ReleaseDate": "2024-04-25", "ReleaseNotes": "Update to CodeProject.AI 2.6.5" },
          { "ModuleVersion": "1.7.1", "ServerVersionRange": [ "2.6.5", "2.7.0"  ], "ReleaseDate": "2024-06-21", "ReleaseNotes": "Corrected Numpy 2.0 issue" },
          { "ModuleVersion": "1.8.0", "ServerVersionRange": [ "2.8.0", ""       ], "ReleaseDate": "2024-08-02", "ReleaseNotes": "Updated for server 2.8" },
          { "ModuleVersion": "1.8.1", "ServerVersionRange": [ "2.8.0", ""       ], "ReleaseDate": "2024-08-02", "ReleaseNotes": "Corrected Numpy 2.0 issue" },
          { "ModuleVersion": "1.9.0", "ServerVersionRange": [ "2.8.0", ""       ], "ReleaseDate": "2024-12-10", "ReleaseNotes": "Updated to use CodeProject.AI SDK" },
          { "ModuleVersion": "1.9.1", "ServerVersionRange": [ "2.8.0", ""       ], "ReleaseDate": "2024-12-10", "ReleaseNotes": "Corrected requirements.txt" }
        ]
      },

      "ModelRequirements" : [{
          "Task": "Object Detection",
          "Architecture": "YOLOv5",
          "Format": "RKNN"
      }],

      "UIElements" : {
        "Menus": [
        {
          "Label": "Model Size",
          "Options": [
              { "Label": "Tiny",   "Setting": "MODEL_SIZE", "Value": "tiny"   },
              { "Label": "Small",  "Setting": "MODEL_SIZE", "Value": "small"  },
              { "Label": "Medium", "Setting": "MODEL_SIZE", "Value": "medium" },
              { "Label": "Large",  "Setting": "MODEL_SIZE", "Value": "large"  }
          ]
        }]
      },

      "RouteMaps": [
        {
          "Name": "Object Detector (YOLOv5 RKNN)",
          "Route": "vision/detection",
          "Method": "POST",
          "Command": "detect",
          "Description": "Detects multiple objects in an image.",
          "Inputs": [
            {
              "Name": "image",
              "Type": "File",
              "Description": "The HTTP file object (image) to be analyzed."
            },
            {
              "Name": "min_confidence",
              "Type": "Float",
              "Description": "The minimum confidence level for an object will be detected. In the range 0.0 to 1.0. Default 0.3.",
              "DefaultValue": 0.30,
              "MinValue": 0.0,
              "MaxValue": 1.0
            }
          ],
          "Outputs": [
            {
              "Name": "success",
              "Type": "Boolean",
              "Description": "True if successful."
            },
            {
              "Name": "message",
              "Type": "String",
              "Description": "A summary of the inference operation."
            },
            {
              "Name": "error",
              "Type": "String",
              "Description": "(Optional) An description of the error if success was false."
            },
            {
              "Name": "predictions",
              "Type": "Object",
              "Description": "An array of objects with the x_max, x_min, max, y_min, label and confidence."
            },
            {
              "Name": "inferenceMs",
              "Type": "Integer",
              "Description": "The time (ms) to perform the AI inference."
            },
            {
              "Name": "processMs",
              "Type": "Integer",
              "Description": "The time (ms) to process the image (includes inference and image manipulation operations)."
            }
          ]
        },

        {
          "Name": "Custom Object Detector  (YOLOv5 RKNN)",
          "Route": "vision/custom",
          "Method": "POST",
          "Command": "custom",
          "Description": "Detects objects based on YOLO PyTorch models. Models are stored as .rknn files in the /ObjectDetectionYoloRKNN/custom-models directory, and to make a call to a specific model use /vision/custom/model-name, where 'model-name' is the name of the model's .rknn file",
          "Inputs": [
            {
              "Name": "image",
              "Type": "File",
              "Description": "The HTTP file object (image) to be analyzed."
            },
            {
              "Name": "min_confidence",
              "Type": "Float",
              "Description": "The minimum confidence level for an object will be detected. In the range 0.0 to 1.0. Default 0.4."
            }
          ],
          "Outputs": [
            {
              "Name": "success",
              "Type": "Boolean",
              "Description": "True if successful."
            },
            {
              "Name": "message",
              "Type": "String",
              "Description": "A summary of the inference operation."
            },
            {
              "Name": "error",
              "Type": "String",
              "Description": "(Optional) An description of the error if success was false."
            },
            {
              "Name": "predictions",
              "Type": "Object[]",
              "Description": "An array of objects with the x_max, x_min, max, y_min, label and confidence."
            },
            {
              "Name": "inferenceMs",
              "Type": "Integer",
              "Description": "The time (ms) to perform the AI inference."
            },
            {
              "Name": "processMs",
              "Type": "Integer",
              "Description": "The time (ms) to process the image (includes inference and image manipulation operations)."
            }
          ]
        },

        {
          "Name": "Object Detector List Custom Models (YOLOv5 RKNN)",
          "Route": "vision/custom/list",
          "Method": "POST",
          "Command": "list-custom",
          "Description": "Returns a list of models available.",
          "Inputs": [],
          "Outputs": [
            {
              "Name": "success",
              "Type": "Boolean",
              "Description": "True if successful."
            },
            {
              "Name": "models",
              "Type": "String",
              "Description": "An array of strings containing the names of the models installed."
            }
          ]
        }
      ]      
    }    
  }
}