| from transformers import AutoModelForImageClassification, AutoFeatureExtractor | |
| import gradio as gr | |
| import torch | |
| def classify_image(image): | |
| device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') | |
| model = AutoModelForImageClassification.from_pretrained('glopez/cifar-10').to(device) | |
| feature_extractor = AutoFeatureExtractor.from_pretrained('glopez/cifar-10') | |
| inp = feature_extractor(image, return_tensors='pt').to(device) | |
| outp = model(**inp) | |
| pred = torch.argmax(outp.logits, dim=1).item() | |
| return model.config.id2label[pred] | |
| interface = gr.Interface(fn=classify_image, inputs=gr.Image(shape=(224, 224)), outputs="text").launch(debug=True) | |