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Fine_tuned_Vit_trash_classification

Image Classification
Transformers
PyTorch
vit
vision
Model card Files
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@@ -44,12 +44,14 @@ from PIL import Image
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  import requests
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  url = 'https://www.estal.com/FitxersWeb/331958/estal_carroussel_wg_spirits_5.jpg'
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  image = Image.open(requests.get(url, stream=True).raw)
 
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  feature_extractor = AutoFeatureExtractor.from_pretrained("Aalaa/Fine_tuned_Vit_trash_classification")
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  model = AutoModelForImageClassification.from_pretrained("Aalaa/Fine_tuned_Vit_trash_classification")
 
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  inputs = feature_extractor(images=image, return_tensors="pt")
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  outputs = model(**inputs)
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  logits = outputs.logits
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- # model predicts one of the 1000 ImageNet classes
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  predicted_class_idx = logits.argmax(-1).item()
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  print("Predicted class:", model.config.id2label[predicted_class_idx])
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  ```
 
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  import requests
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  url = 'https://www.estal.com/FitxersWeb/331958/estal_carroussel_wg_spirits_5.jpg'
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  image = Image.open(requests.get(url, stream=True).raw)
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+
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  feature_extractor = AutoFeatureExtractor.from_pretrained("Aalaa/Fine_tuned_Vit_trash_classification")
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  model = AutoModelForImageClassification.from_pretrained("Aalaa/Fine_tuned_Vit_trash_classification")
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+
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  inputs = feature_extractor(images=image, return_tensors="pt")
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  outputs = model(**inputs)
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  logits = outputs.logits
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+
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  predicted_class_idx = logits.argmax(-1).item()
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  print("Predicted class:", model.config.id2label[predicted_class_idx])
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  ```