From 462146b34ea65861c94b290c1554effa97d96ab2 Mon Sep 17 00:00:00 2001
From: Onuralp SEZER <thunderbirdtr@gmail.com>
Date: Wed, 16 Jul 2025 02:30:12 +0200
Subject: [PATCH] =?UTF-8?q?docs:=20=F0=9F=93=9D=20add=20prompt=20engineeri?=
 =?UTF-8?q?ng=20tips=20for=20Qwen2.5-VL=20and=20Moondream=20models=20for?=
 =?UTF-8?q?=20from=5Flmm?=
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---
 supervision/detection/core.py | 64 +++++++++++++++++++++++++++++++++++
 1 file changed, 64 insertions(+)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index c8f2664b..efaa366a 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -867,6 +867,53 @@ class Detections:
             ```
 
         !!! example "Qwen2.5-VL"
+
+            ??? tip "Prompt engineering"
+
+                To get the best results from Qwen2.5-VL, use clear and descriptive prompts
+                that specify exactly what you want to detect.
+
+                **For general object detection, use this comprehensive prompt:**
+
+                ```
+                Detect all objects in the image and return their locations and labels.
+                ```
+
+                **For specific object detection with detailed descriptions:**
+
+                ```
+                Detect the red object that is leading in this image and return its location and label.
+                ```
+
+                **For simple, targeted detection:**
+
+                ```
+                leading blue truck
+                ```
+
+                **Additional effective prompts:**
+
+                ```
+                Find all people and vehicles in this scene
+                ```
+
+                ```
+                Locate all animals in the image
+                ```
+
+                ```
+                Identify traffic signs and their positions
+                ```
+
+                **Tips for better results:**
+
+                - Use descriptive language that clearly specifies what to look for
+                - Include color, size, or position descriptors when targeting specific objects
+                - Be specific about the type of objects you want to detect
+                - The model responds well to both detailed instructions and concise phrases
+                - Results are returned in JSON format with `bbox_2d` coordinates and `label` fields
+
+
             ```python
             import supervision as sv
 
@@ -1023,6 +1070,23 @@ class Detections:
             ```
 
         !!! example "Moondream"
+
+
+            ??? tip "Prompt engineering"
+
+                To get the best results from Moondream, use optimized prompts that leverage
+                its object detection capabilities effectively.
+
+                **For general object detection, use this simple prompt:**
+
+                ```
+                objects
+                ```
+
+                This single-word prompt instructs Moondream to detect all visible objects
+                and return them in the proper JSON format with normalized coordinates.
+
+
             ```python
             import supervision as sv