| import torch | |
| from PIL import Image | |
| import gradio as gr | |
| from transformers import AutoImageProcessor, AutoModelForImageClassification | |
| model_id = "prithivMLmods/Food-101-93M" | |
| processor = AutoImageProcessor.from_pretrained(model_id) | |
| model = AutoModelForImageClassification.from_pretrained(model_id) | |
| def predict_food(image: Image.Image): | |
| inputs = processor(images=image, return_tensors="pt") | |
| with torch.no_grad(): | |
| outputs = model(**inputs) | |
| probs = torch.nn.functional.softmax(outputs.logits, dim=1)[0] | |
| topk = torch.topk(probs, k=5) | |
| labels = [model.config.id2label[i.item()] for i in topk.indices] | |
| scores = [round((p * 100).item(), 2) for p in topk.values] | |
| return "\n".join(f"{lbl}: {sc}%" for lbl, sc in zip(labels, scores)) | |
| gr.Interface( | |
| fn=predict_food, | |
| inputs=gr.Image(type="pil"), | |
| outputs="text", | |
| title="🍽️ Food‑101 Food Classifier", | |
| description="Upload food image, outputs the top 5 dish categories." | |
| ).launch() |