| #!/usr/bin/env python3 | |
| """MobileNetV3-Small classification example.""" | |
| import sys, numpy as np | |
| from PIL import Image | |
| from inference import MobileNetV3Classifier | |
| model_path = sys.argv[1] if len(sys.argv) > 1 else "../models/model.axmodel" | |
| image_path = sys.argv[2] if len(sys.argv) > 2 else "../demo/demo.jpg" | |
| img = Image.open(image_path).resize((224, 224)) | |
| data = np.array(img, dtype=np.float32).transpose(2, 0, 1)[np.newaxis] / 255.0 | |
| clf = MobileNetV3Classifier(model_path) | |
| out = clf.classify(data) | |
| top5 = np.argsort(-out[0])[:5] | |
| print(f"Top-5 classes: {top5}") | |
| print(f"Scores: {out[0][top5]}") | |