| import gradio | |
| from pathlib import Path | |
| from fastai.vision.all import ( | |
| load_learner | |
| ) | |
| import gradio.interface | |
| CATEGORIES = ('Damaged', 'Whole') | |
| MODEL_PATH = Path('.') / 'models' | |
| TEST_IMAGES_PATH = Path('.') / 'test' | |
| LEARNER = load_learner(MODEL_PATH / 'car-damage-detection_v2.pkl') | |
| def categorize_image(image): | |
| prediction, index, probabilities = LEARNER.predict(image) | |
| return dict(zip(CATEGORIES, map(float, probabilities))) | |
| demo = gradio.Interface( | |
| categorize_image, | |
| inputs='image', | |
| outputs='label', | |
| examples=[str(image) for image in TEST_IMAGES_PATH.iterdir()] | |
| ) | |
| demo.launch() | |