Create Simple Image Classification

Simple Image Classification

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+# Import necessary libraries
+from transformers import ViTFeatureExtractor, ViTForImageClassification
+from PIL import Image
+import requests
+import torch
+import matplotlib.pyplot as plt
+
+# Load pre-trained feature extractor and model
+feature_extractor = ViTFeatureExtractor.from_pretrained('google/vit-base-patch16-224')
+model = ViTForImageClassification.from_pretrained('google/vit-base-patch16-224')
+
+# Load and display the image
+url = "URL_of_the_image"
+image = Image.open(requests.get(url, stream=True).raw)
+plt.imshow(image)
+plt.show()
+
+# Extract features from the image
+inputs = feature_extractor(images=image, return_tensors="pt")
+
+# Make predictions
+outputs = model(**inputs)
+logits = outputs.logits
+predicted_class_idx = logits.argmax(-1).item()
+
+# Get and print the predicted class name
+predicted_class = model.config.id2label[predicted_class_idx]
+print(f'Predicted class: {predicted_class}')