jonathanfernandes/flowers

1import torch2from transformers import AutoModelForImageClassification, AutoFeatureExtractor3import gradio as gr4 5model_id = f'jonathanfernandes/vit-base-patch16-224-finetuned-flower'6labels = ['daisy', 'dandelion', 'roses', 'sunflowers', 'tulips']7 8def classify_image(image):9  model = AutoModelForImageClassification.from_pretrained(model_id)10  feature_extractor = AutoFeatureExtractor.from_pretrained(model_id)11  inp = feature_extractor(image, return_tensors='pt')12  outp = model(**inp)13  pred = torch.nn.functional.softmax(outp.logits, dim=-1)14  preds = pred[0].cpu().detach().numpy()15  confidence = {label: float(preds[i]) for i, label in enumerate(labels)}16  return confidence17 18interface = gr.Interface(fn=classify_image, 19                         inputs='image', 20                         examples=['flower-1.jpeg', 'flower-2.jpeg'],21                         outputs='label').launch()