Create app.py

app.py

@@ -0,0 +1,42 @@
+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()