| import gradio as gr | |
| from transformers import pipeline | |
| pipeline = pipeline(task="image-classification", model="bortle/astrophotography-object-classifier-alpha") | |
| def predict(image): | |
| predictions = pipeline(image) | |
| return {p["label"]: p["score"] for p in predictions} | |
| gr.Interface( | |
| predict, | |
| inputs=gr.Image(shape=(1080, None), type="pil", label="Upload Astrophotography image"), | |
| outputs=gr.Label(num_top_classes=5), | |
| title="Astrophotography Object Classifier", | |
| allow_flagging="manual", | |
| examples=["examples/Andromeda.jpg","examples/Heart.jpg","examples/Pleiades.jpg","examples/Rosette.jpg"], | |
| cache_examples=True | |
| ).launch() |