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README.md

@@ -20,6 +20,10 @@ tags:
 
 # LLVIP: Visible-Infrared Paired Low-light Vision Dataset (No Data Mirror -- Adapter Only)
 
+<p align="center">
+  <img src="llvip_banner.jpg" alt="LLVIP Dataset Banner"/>
+</p>
+
 ![Task](https://img.shields.io/badge/Task-Object%20Detection-blue?style=flat-square)
 ![Dataset](https://img.shields.io/badge/Dataset-LLVIP-0aa1a7?style=flat-square)
 ![Classes](https://img.shields.io/badge/Classes-1-success?style=flat-square)
@@ -37,7 +41,8 @@ LLVIP was created by Xinyu Jia, Chuang Zhu, Minzhen Li, Wenqi Tang, and Wenli Zh
 What this repository provides instead:
 
 1. A [DetectionBench dataset adapter](https://github.com/dronefreak/DetectionBench/blob/main/src/detectionbench/datasets/llvip.py) that converts an official LLVIP download into DetectionBench's canonical training layout, once you have obtained the data yourself.
-2. A helper command, `detectionbench-download-dataset --dataset llvip`, that prints the official download links (Google Drive and Baidu Netdisk) -- see [Getting the Data](#getting-the-data).
+2. A helper command, `detectionbench-download-dataset --dataset llvip`, that prints the official download links (Google Drive and Baidu Netdisk) and can fetch the Google Drive copy automatically via `gdown` -- see [Getting the Data](#getting-the-data).
+3. This banner, generated locally from an LLVIP copy already converted through the adapter, purely to illustrate the dataset's domain and annotation style.
 
 ---
 
@@ -71,7 +76,7 @@ detectionbench-convert-coco-to-yolo --input-dir <coco_out> --output-dir <yolo_ou
 
 LLVIP ships with no official validation split; the adapter carves a seeded 15% slice out of train.
 
-**Note:** the adapter expects `infrared/{train,test}/*.jpg` + `Annotations/*.xml` under the raw directory, matching the official README's documented layout. If your specific download uses different folder names, a one-line edit to `_SPLIT_DIRS` in the adapter source fixes it.
+**Note:** the adapter expects `infrared/{train,test}/*.jpg` + `Annotations/*.xml` under the raw directory, matching the official README's documented layout -- verified against a real download: 10,221 train / 1,804 valid (15% carve of the official 12,025 train images) / 3,463 test, 29,113 / 5,017 / 8,302 `person` boxes respectively.
 
 ### Classes (1)