| import gradio as gr | |
| from transformers import pipeline | |
| pipeline = pipeline(task="image-classification", model="pranavbup/aircraft-classification") | |
| def predict(image): | |
| predictions = pipeline(image) | |
| return {p["label"]: p["score"] for p in predictions} | |
| gr.Interface( | |
| predict, | |
| examples=["./b777.jpg","./atr72.jpeg","./c208.jpg"], | |
| inputs=gr.inputs.Image(label="Upload only commercial aircraft image here", type="filepath"), | |
| outputs=gr.outputs.Label(num_top_classes=5), | |
| title="Find which Aircraft it is ✈️", | |
| ).launch(inline=False) | |