import numpy as np
import torch
import datasets
from transformers import AutoFeatureExtractor, AutoModelForImageClassification


dataset = datasets.load_dataset('beans')

extractor = AutoFeatureExtractor.from_pretrained("saved_model_files")
model = AutoModelForImageClassification.from_pretrained("saved_model_files")

labels = dataset['train'].features['labels'].names

def classify(im):
  features = extractor(im, return_tensors='pt')
  logits = model(features["pixel_values"])[-1]
  probability = torch.nn.functional.softmax(logits, dim=-1)
  probs = probability[0].detach().numpy()
  confidences = {label: float(probs[i]) for i, label in enumerate(labels)} 
  return confidences

import gradio as gr

interface = gr.Interface(fn=classify, inputs="image", outputs="label", 
                         examples=[
                             ["https://images.unsplash.com/photo-1550147760-44c9966d6bc7?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxzZWFyY2h8Nnx8bGVhZnxlbnwwfHwwfHw%3D&auto=format&fit=crop&w=800&q=60"],
                             ["https://images.unsplash.com/photo-1525498128493-380d1990a112?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxzZWFyY2h8MTd8fGxlYWZ8ZW58MHx8MHx8&auto=format&fit=crop&w=800&q=60"],
                             ["https://apps.lucidcentral.org/pppw_v10/images/entities/bean_angular_leaf_spot_216/angularspot1.jpg"],
                             ["https://extension.umn.edu/sites/extension.umn.edu/files/beans-viral-diseases-2.jpg"],
                             ["http://1.bp.blogspot.com/-CcMICF_A1CI/UHKSvTV2k2I/AAAAAAAAHI0/TlFMGU8RpYQ/s1600/DSCF9698.JPG"],
                             ["https://www.garden.eco/wp-content/uploads/2017/12/bean-leaves.jpg"],
                             ["https://apps.lucidcentral.org/pppw_v10/images/entities/bean_angular_leaf_spot_216/angularspot1.jpg"]


                         ],
                         title="🍃 Bean Leaf Image Classification",
                         description="Based on a leaf image, the goal is to predict the disease type (Angular Leaf Spot and Bean Rust), if any.",)

interface.launch(debug=True)