feat: add initial inference endpoint

Sources/App/RecognitionController.swift

@@ -0,0 +1,95 @@
+import Vapor
+import AVFoundation
+import CoreImage
+import Vision
+
+class RecognitionController: RouteCollection {
+    
+    private var modelsPath: String
+    
+    init(modelsPath: String) {
+        self.modelsPath = modelsPath
+    }
+    
+    var classes:[String] = []
+    
+    var yoloRequest:VNCoreMLRequest?
+    
+    func loadModel() throws {
+        let modelURL = URL(fileURLWithPath: modelsPath).appendingPathComponent("yolov8m-oiv7.mlmodelc")
+        let model = try MLModel(contentsOf: modelURL, configuration: MLModelConfiguration())
+        guard let classes = model.modelDescription.classLabels as? [String] else {
+            fatalError()
+        }
+        self.classes = classes
+        let vnModel = try VNCoreMLModel(for: model)
+        yoloRequest = VNCoreMLRequest(model: vnModel)
+    }
+    
+    func boot(routes: RoutesBuilder) throws {
+       routes.on(.POST,
+                 "recognize",
+                 body: .collect(maxSize: ByteCount(value: 2000*1024)),
+                 use: recognize
+       )
+   }
+   
+   func recognize(req: Request) async throws -> BboxResponse {
+       guard yoloRequest != nil else {
+           throw ModelError.notLoaded
+       }
+       let request = try req.content.decode(String.self)
+       
+       guard let dataDecoded : Data = Data(base64Encoded: request, options: .ignoreUnknownCharacters) else {
+           return BboxResponse(detections: [])
+       }
+       let ciImage = CIImage(data: dataDecoded)!
+       var pixelBuffer: CVPixelBuffer?
+       let attrs = [kCVPixelBufferCGImageCompatibilityKey: kCFBooleanTrue,
+                    kCVPixelBufferCGBitmapContextCompatibilityKey: kCFBooleanTrue] as CFDictionary
+       let width:Int = Int(ciImage.extent.width)
+       let height:Int = Int(ciImage.extent.height)
+       CVPixelBufferCreate(kCFAllocatorDefault,
+                           width,
+                           height,
+                           kCVPixelFormatType_32BGRA,
+                           attrs,
+                           &pixelBuffer)
+               let context = CIContext()
+       context.render(ciImage, to: pixelBuffer!)
+       
+       
+       let handler = VNImageRequestHandler(cvPixelBuffer: pixelBuffer!)
+       try handler.perform([yoloRequest!])
+       guard let results = yoloRequest!.results as? [VNRecognizedObjectObservation] else {
+           return BboxResponse(detections: [])
+       }
+       var detections:[Detection] = []
+       for result in results {
+           guard let label = result.labels.first?.identifier as? String else {
+               return BboxResponse(detections: [])
+           }
+           let detection = Detection(prob: result.confidence, category: label, x: Float(result.boundingBox.minX * ciImage.extent.width), y: Float((1 - result.boundingBox.maxY) * ciImage.extent.height), w: Float(result.boundingBox.width * ciImage.extent.width), h: Float(result.boundingBox.height * ciImage.extent.height))
+           detections.append(detection)
+       }
+       
+       return BboxResponse(detections: detections)
+   }
+}
+
+struct BboxResponse: Content {
+    let detections: [Detection]
+}
+
+struct Detection: Codable {
+    let prob:Float
+    let category:String?
+    let x: Float
+    let y : Float
+    let w: Float
+    let h: Float
+}
+
+public enum ModelError: Error {
+    case notLoaded
+}

Sources/App/routes.swift

@@ -1,11 +1,7 @@
 import Vapor
 
 func routes(_ app: Application) throws {
-    app.get { req async in
-        "It works!"
-    }
-
-    app.get("hello") { req async -> String in
-        "Hello, world!"
-    }
+    let recoController = RecognitionController(modelsPath: "")
+    try app.register(collection: recoController)
+    try recoController.loadModel()
 }