Method test_specific_sample

ML/tests/test_model.py:100–116

(self, index)

        print(f"Accuracy: {accuracy:.1%} ({correct}/{num_samples})")
    
    def test_specific_sample(self, index):
        if index < 0 or index >= len(self.dataset):
            print(f"Error: Index must be between 0 and {len(self.dataset)-1}")
            return
        
        image, label = self.dataset[index]
        pred_class, confidence, top5_idx, top5_prob = self.predict_image(image)
        
        print(f"\nSample #{index}")
        print("-" * 60)
        print(f"True Label:      {self.classes[label]}")
        print(f"Predicted:       {self.classes[pred_class]}")
        print(f"Confidence:      {confidence:.2%}")
        print(f"Status:          {'✓ Correct' if pred_class == label else '✗ Wrong'}")
        print("\nTop-5 Predictions:")
        for i, (idx, prob) in enumerate(zip(top5_idx, top5_prob), 1):
            print(f"  {i}. {self.classes[idx]:15s} {prob:.2%}")
    
    def test_class_accuracy(self):
        print("\nCalculating per-class accuracy...")