feat: add manual & auto batch counting modes, dual-port operator and monitoring dashboards, and historical batch data corrections

export_model.py

@@ -0,0 +1,46 @@
+from ultralytics import YOLO
+import torch
+import os
+
+def main():
+    model_path = "karung-dimuat-detection-di-feedmill-yolo26n-seg-200e.pt"
+    if not os.path.exists(model_path):
+        print(f"Error: {model_path} tidak ditemukan di folder ini!")
+        return
+
+    print("=" * 60)
+    print("--- PROSES EKSPOR MODEL KE TENSORRT (.engine) ---")
+    print("=" * 60)
+    print(f"CUDA Terdeteksi: {torch.cuda.is_available()}")
+    if torch.cuda.is_available():
+        print(f"GPU Device Name: {torch.cuda.get_device_name(0)}")
+    
+    print("\nLoading model ke memori...")
+    model = YOLO(model_path)
+    
+    print("\nMengekspor model ke format TensorRT (FP16)...")
+    try:
+        # Eksport ke TensorRT (.engine)
+        # half=True mengaktifkan kuantisasi FP16 (sangat cepat di GPU Jetson)
+        engine_path = model.export(format="engine", device=0, half=True)
+        print(f"\n[SUKSES] Model berhasil diekspor ke: {engine_path}")
+        print("\nSelanjutnya:")
+        print("1. Ganti MODEL_FILE di predict.py menjadi nama file .engine yang baru dibuat.")
+        print("2. Jalankan kembali predict.py untuk performa GPU maksimal!")
+    except Exception as e:
+        print(f"\n[Gagal ekspor langsung ke Engine]: {e}")
+        print("\nMencoba metode alternatif: Ekspor ke ONNX terlebih dahulu...")
+        try:
+            onnx_path = model.export(format="onnx", half=True, dynamic=False, opset=12)
+            print(f"[SUKSES] Model berhasil diekspor ke ONNX: {onnx_path}")
+            
+            onnx_file = os.path.basename(onnx_path)
+            engine_file = onnx_file.replace(".onnx", ".engine")
+            print("\nAnda bisa mengompilasi file ONNX tersebut ke Engine secara manual di Jetson dengan menjalankan:")
+            print(f"  /usr/src/tensorrt/bin/trtexec --onnx={onnx_file} --saveEngine={engine_file} --fp16")
+            print("\nSetelah kompilasi manual selesai, ganti MODEL_FILE di predict.py dengan file .engine hasil kompilasi tersebut.")
+        except Exception as ex:
+            print(f"[Gagal ekspor ke ONNX]: {ex}")
+
+if __name__ == "__main__":
+    main()