Update README.md

README.md

@@ -36,15 +36,15 @@ import numpy as np
 from PIL import Image
 from transformers import AutoImageProcessor, AutoModelForImageClassification
 
-# Load the model and image processor
+#Load the model and image processor
 processor = AutoImageProcessor.from_pretrained("beingamit99/car_damage_detection")
 model = AutoModelForImageClassification.from_pretrained("beingamit99/car_damage_detection")
 
-# Load and process the image
+#Load and process the image
 image = Image.open(IMAGE)
 inputs = processor(images=image, return_tensors="pt")
 
-# Make predictions
+#Make predictions
 outputs = model(**inputs)
 logits = outputs.logits.detach().cpu().numpy()
 predicted_class_id = np.argmax(logits)
@@ -52,7 +52,7 @@ predicted_proba = np.max(logits)
 label_map = model.config.id2label
 predicted_class_name = label_map[predicted_class_id]
 
-# Print the results
+#Print the results
 print(f"Predicted class: {predicted_class_name} (probability: {predicted_proba:.4f})")
 </code>
 
@@ -60,7 +60,7 @@ print(f"Predicted class: {predicted_class_name} (probability: {predicted_proba:.
 <code>
 from transformers import pipeline
 
-# Create a classification pipeline
+#Create a classification pipeline
 pipe = pipeline("image-classification", model="beingamit99/car_damage_detection")
 pipe(IMAGE)
 </code>