app.py

import gradio as gr
import timm

model = timm.create_model("MobileOne_s2", pretrained = False)
model.head.fc = nn.Linear(model.head.fc.in_features,3)
model.load_state_dict(torch.load("olive_classifier.pth", weights_only=True))
model.eval()

categories = ("Aculus Olearius", "Healthy", "Peacock Spot")


def classify_health(input_img):
    probs = model(input_img)
    idx = probs.argmax()
    return dict(zip(categories, map(float, probs)))


labels = gr.Label()
examples = [
    "examples/healthy.jpg",
    "examples/aculus_2.jpg",
    "examples/peacock_3.jpeg",
]
demo = gr.Interface(
    classify_health,
    inputs=gr.Image(height=224, width=224),
    outputs=labels,
    examples=examples,
)
demo.launch(inline=False)