SONAR-AI-Models

🔱 SONAR AI - Customs X-Ray Inspection Models

Dr. Abbas Fadel Jassim | 2026

AI-powered customs inspection system for X-ray cargo scanning

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📊 Models Performance Summary

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🔍 Model 1: Classification (43 cargo categories)

Task: Classify X-ray images into 43 different cargo types

Per-Class Performance (Swin-V2):

Training: 30 epochs, AdamW (lr=1e-4), CosineAnnealing, Albumentations augmentation

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🔍 Model 2: Concealment Detection (match vs no_match)

Task: Detect hidden/smuggled items in X-ray containers

Classes:

• match: Container contents match declaration (6,348 images)
• no_match: Concealed/smuggled items detected (702 images)

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⚠️ Model 3: Risk Assessment (5 levels)

Task: Assess risk level of container cargo

Risk Levels:

Note: Low and Critical levels have very few training samples.

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📁 Files

SONAR-AI-Models/
├── concealment/
│   ├── best_swinv2.pth      (110 MB, 98.4% F1)
│   ├── best_davit.pth       (110 MB, 98.4% F1)
│   ├── best_eva02.pth       (22 MB, 97.8% F1)
│   └── best_maxvit.pth      (122 MB, 96.8% F1)
├── classification/
│   ├── best_swinv2_43cls.pth (110 MB, 94.1% F1)
│   └── best_davit_43cls.pth  (110 MB, 94.1% F1)
├── risk/
│   ├── best_swinv2_risk.pth  (110 MB, 97.2% F1)
│   └── best_davit_risk.pth   (110 MB, 97.3% F1)
└── results/
    ├── classification_cm.png
    ├── classification_training.png
    ├── risk_cm.png
    └── risk_training.png

🛠️ Usage

import timm, torch
from torchvision import transforms
from PIL import Image

# Load model
model = timm.create_model('swinv2_tiny_window8_256', pretrained=False, num_classes=43)
ckpt = torch.load('classification/best_swinv2_43cls.pth', map_location='cpu')
model.load_state_dict(ckpt['model_state_dict'])
model.eval()

# Inference
tf = transforms.Compose([
    transforms.Resize((256, 256)),
    transforms.ToTensor(),
    transforms.Normalize([0.485,0.456,0.406], [0.229,0.224,0.225])
])
img = tf(Image.open('xray.jpg').convert('RGB')).unsqueeze(0)
with torch.no_grad():
    pred = model(img).argmax(1).item()

📜 License

Apache 2.0

👨‍💻 Author

Dr. Abbas Fadel Jassim - 2026