| 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) | |