app.py

import gradio as gr
from transformers import pipeline
from PIL import Image, ImageDraw

# Load object detection pipeline
model_pipeline = pipeline(
    task="object-detection", 
    model="bortle/autotrain-ap-obj-detector-1"
)

def predict(image):
    # Resize the image to width 1080, maintaining aspect ratio
    width = 1080
    ratio = width / image.width
    height = int(image.height * ratio)
    resized_image = image.resize((width, height))

    # Run object detection
    detections = model_pipeline(resized_image)

    # Draw detections on image
    draw = ImageDraw.Draw(resized_image)
    for det in detections:
        box = det["box"]
        label = f'{det["label"]}: {det["score"]:.2f}'
        draw.rectangle(
            [(box["xmin"], box["ymin"]), (box["xmax"], box["ymax"])],
            outline="red",
            width=3
        )
        draw.text((box["xmin"], box["ymin"] - 10), label, fill="red")

    return resized_image

# Gradio Interface
gr.Interface(
    fn=predict,
    inputs=gr.Image(type="pil", label="Upload Astrophotography Image"),
    outputs=gr.Image(type="pil", label="Detected Objects"),
    title="Astrophotography Object Detector",
    allow_flagging="manual",
).launch()