SudeepM27/apple-leaf-disease-detection

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<!-- Provide a quick summary of what the model is/does. --> MobileVITV2 based Image Classification model to classify apple leaf diseases

Model Details

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• —Developed by: Sudeep Mungara

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Uses

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How to Get Started with the Model

from PIL import Image
import torch
from transformers import AutoImageProcessor, AutoModelForImageClassification

processor = AutoImageProcessor.from_pretrained("SudeepM27/apple-leaf-disease-detection")
model = AutoModelForImageClassification.from_pretrained("SudeepM27/apple-leaf-disease-detection")

model.eval()
image_path = "path to image"  # Replace with your test image path
image = Image.open(image_path)
inputs = processor(images=image, return_tensors="pt")

# Perform inference
with torch.no_grad():
    outputs = model(**inputs)

# Get the predicted class
logits = outputs.logits
predicted_class_idx = logits.argmax(-1).item()
predicted_label = model.config.id2label[predicted_class_idx]

print(f"Predicted class index: {predicted_class_idx}")
print(f"Predicted label: {predicted_label}")

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