Create app.py

app.py

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+import gradio as gr
+from transformers import ViTForImageClassification, ViTImageProcessor
+import torch
+
+# Define the pretrained model
+model_name = "Treelar/vit-b16-plant_village"
+
+# Load the ViT model and the image processor
+model = ViTForImageClassification.from_pretrained(model_name)
+image_processor = ViTImageProcessor.from_pretrained(model_name)
+
+def predict(image):
+    # Convert the image into the model's required format
+    inputs = image_processor(images=image, return_tensors="pt")
+
+    # Disable gradient calculation to make the process efficient
+    with torch.no_grad():
+        outputs = model(**inputs)  # Gets the model's output for the image
+        logits = outputs.logits   # Output scores from the model
+
+    # Convert the logits to a probability using the softmax function
+    probability = torch.nn.functional.softmax(logits, dim=1)
+    top_probability, top_index = probability.max(1)  # Gets the highest probability with its respective index
+
+    # Gets the disease label from the model using the probability's index
+    label_index = top_index.item()
+    label = model.config.id2label[label_index]
+
+    # Split the label into leaf category and disease name
+    label_parts = label.split("___")
+    leaf_category = label_parts[0]
+    disease_name = label_parts[1]
+
+    # Calculate the percentage breakdown of predicted diseases
+    percentage_breakdown = {disease: round(float(probability[0, index]) * 100, 2) for index, disease in enumerate(model.config.label2id)}
+
+    return leaf_category.capitalize(), disease_name.replace('_', ' ').capitalize(), percentage_breakdown
+
+# Gradio interface setup with separate boxes for Leaf Type, Identified Disease, and Percentage Breakdown
+interface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(label="Upload the Image"),
+    outputs=[
+        gr.Textbox(label="Leaf Type:"),
+        gr.Textbox(label="Identified Disease:"),
+        gr.JSON(label="Percentage Breakdown:")
+    ],
+    title="Plant Disease Identifier",
+    description="Once the image has been uploaded and submitted, the disease of the plant will be determined. The percentage breakdown shows the probability of each disease."
+)
+
+interface.launch(debug=True)  # Start server and launch the UI