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app.py

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+"""
+DEBRI-X Gradio Space Demo
+Drop this file + yolo_best.pt into a Hugging Face Space (SDK=gradio).
+requirements.txt: ultralytics opencv-python-headless huggingface_hub gradio
+"""
+import gradio as gr
+import numpy as np, cv2
+from PIL import Image
+
+MODEL_REPO = "Premchan369/debrex-space-debris-capture"
+try:
+    from huggingface_hub import hf_hub_download
+    from ultralytics import YOLO
+    wt   = hf_hub_download(MODEL_REPO, "yolo_best.pt")
+    yolo = YOLO(wt)
+    LOADED = True
+except Exception as e:
+    print(f"Model load failed: {e}")
+    LOADED = False
+
+def detect(image, conf=0.25):
+    if image is None:
+        return None, "Please upload an image."
+    img_bgr = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+    if not LOADED:
+        H, W = img_bgr.shape[:2]
+        cv2.rectangle(img_bgr, (W//4, H//4), (3*W//4, 3*H//4), (0,200,100), 2)
+        return Image.fromarray(cv2.cvtColor(img_bgr, cv2.COLOR_BGR2RGB)), "Demo mode."
+    yolo.conf = conf
+    res = yolo(img_bgr, verbose=False)
+    ann = res[0].plot()
+    n   = len(res[0].boxes)
+    cfs = [f"{c:.2f}" for c in res[0].boxes.conf.cpu().numpy()]
+    info = f"Objects: {n}\nConf: {', '.join(cfs) or 'none'}\nModel: YOLOv8n (DEBRI-X)"
+    return Image.fromarray(cv2.cvtColor(ann, cv2.COLOR_BGR2RGB)), info
+
+with gr.Blocks(title="DEBRI-X Debris Detection") as demo:
+    gr.Markdown("# 🛰️ DEBRI-X — Space Debris Detection")
+    with gr.Row():
+        with gr.Column():
+            inp  = gr.Image(type="pil", label="Input")
+            conf = gr.Slider(0.05, 0.95, 0.25, label="Confidence")
+            btn  = gr.Button("Detect", variant="primary")
+        with gr.Column():
+            out_img  = gr.Image(type="pil", label="Result")
+            out_info = gr.Textbox(label="Info", lines=4)
+    btn.click(detect, [inp, conf], [out_img, out_info])
+
+if __name__ == "__main__":
+    demo.launch()