Update app.py

app.py

@@ -145,6 +145,12 @@ def detect_and_draw(
     )
     return img_out
 
+# Create example list
+examples = [
+    ["examples/IMG_8920.jpeg", "bin. water bottle. hand. shoe.", 0.4, 0.3],
+    ["examples/IMG_9435.jpeg", "lettuce. orange slices (group). eggs (group). cheese (group). red cabbage. pear slices (group).", 0.4, 0.3],
+]
+
 # Create Gradio demo
 demo = gr.Interface(
     fn      = detect_and_draw,
@@ -158,11 +164,8 @@ demo = gr.Interface(
     outputs = gr.Image(type="pil", label="Detections"),
     title   = "LLMDet Demo: Open-Vocabulary Grounded Object Detection",
     description = f"""Upload an image, enter text queries, and adjust thresholds to see detections.
-
     Adapted from LLMDet GitHub repo [Hugging Face demo](https://github.com/iSEE-Laboratory/LLMDet/tree/main/hf_model).
-
     This space uses: {model_id}
-
     See original:
     * [LLMDet GitHub](https://github.com/iSEE-Laboratory/LLMDet/tree/main?tab=readme-ov-file)
     * [LLMDet Paper](https://arxiv.org/abs/2501.18954) - LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models
@@ -170,7 +173,9 @@ demo = gr.Interface(
         * [Tiny](https://huggingface.co/fushh7/llmdet_swin_tiny_hf) (173M params) 
         * [Base](https://huggingface.co/fushh7/llmdet_swin_base_hf) (233M params)
         * [Large](https://huggingface.co/fushh7/llmdet_swin_large_hf) (344M params)
-    """
+    """,
+    examples = examples,
+    cache_examples = True,
 )
 
 demo.launch()