Create README.md

README.md

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+import numpy as np
+from PIL import Image
+# Load model directly
+from transformers import AutoImageProcessor, AutoModelForImageClassification
+
+processor = AutoImageProcessor.from_pretrained("beingamit99/car_damage_detection")
+model = AutoModelForImageClassification.from_pretrained("beingamit99/car_damage_detection")
+image = Image.open(IMAGE)
+inputs = processor(images=image, return_tensors="pt")
+outputs = model(**inputs)
+logits = outputs.logits.detach().cpu().numpy()
+
+# Get the most likely class and its probability
+predicted_class_id = np.argmax(logits)
+predicted_proba = np.max(logits)
+
+# Get the class name from the model's label map
+label_map = model.config.id2label
+predicted_class_name = label_map[predicted_class_id]
+
+print(f"Predicted class: {predicted_class_name} (probability: {predicted_proba:.4f})")