| from transformers import ViTFeatureExtractor, ViTForImageClassification |
| from PIL import Image |
| import requests |
|
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| |
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|
| url = 'https://cdn-s-www.leprogres.fr/images/E86C9616-1371-4B3A-9CF8-05A2D891D0A3/NW_detail_M/comme-on-peut-le-voir-le-multipla-de-premiere-generation-est-la-copie-conforme-du-multipla-concept-deux-phares-sont-loges-dans-le-bandeau-sous-le-parebrise-photo-fiat-1664781478.jpg' |
| image = Image.open(requests.get(url, stream=True).raw) |
|
|
| |
| image.show() |
| feature_extractor = ViTFeatureExtractor.from_pretrained( |
| 'google/vit-base-patch16-224') |
| model = ViTForImageClassification.from_pretrained( |
| 'google/vit-base-patch16-224') |
|
|
| inputs = feature_extractor(images=image, return_tensors="pt") |
| outputs = model(**inputs) |
| logits = outputs.logits |
|
|
| predicted_class_idx = logits.argmax(-1).item() |
| print("Predicted class:", model.config.id2label[predicted_class_idx]) |
|
|
