| 55 | self.assertTrue(np.all(scaled_boxes <= max(img0_shape))) |
| 56 | |
| 57 | def test_predict(self): |
| 58 | # Mock model inference output |
| 59 | mock_output = np.random.random((1, 300, 6)) |
| 60 | self.model.model.run.return_value = [mock_output] |
| 61 | |
| 62 | # Create a dummy image |
| 63 | image = np.ones((500, 300, 3), dtype=np.uint8) |
| 64 | |
| 65 | results = self.model.predict(image) |
| 66 | |
| 67 | # Validate predictions |
| 68 | self.assertEqual(len(results), 1) |
| 69 | self.assertIsInstance(results[0], YoloResult) |
| 70 | self.assertGreater(len(results[0].boxes), 0) |
| 71 | self.assertIsInstance(results[0].boxes[0], YoloBox) |
| 72 | |
| 73 | |
| 74 | class TestYoloResult(unittest.TestCase): |