| from transformers import ViTFeatureExtractor, ViTForImageClassification |
| from PIL import Image |
| import torch |
|
|
| model_name = "saved_model" |
|
|
| model = ViTForImageClassification.from_pretrained(model_name) |
| feature_extractor = ViTFeatureExtractor.from_pretrained(model_name) |
|
|
| model.eval() |
|
|
| image_path = '/path/' |
| image = Image.open(image_path).convert('RGB') |
|
|
| inputs = feature_extractor(images=image, return_tensors="pt") |
|
|
| with torch.no_grad(): |
| outputs = model(**inputs) |
| logits = outputs.logits |
|
|
| predicted_class_idx = logits.argmax(-1).item() |
|
|
| classes = model.config.id2label |
|
|
| print(f"Predicted class: {classes[predicted_class_idx]}") |
