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+# YOLOv11
+
+## Model Description
+
+Ultralytics YOLO11 is not just another object detection model; it's a versatile framework designed to cover the entire lifecycle of machine learning models—from data ingestion and model training to validation, deployment, and real-world tracking. Each mode serves a specific purpose and is engineered to offer you the flexibility and efficiency required for different tasks and use-cases.
+
+## Supported Environments
+
+| GPU    | [IXUCA SDK](https://gitee.com/deep-spark/deepspark#%E5%A4%A9%E6%95%B0%E6%99%BA%E7%AE%97%E8%BD%AF%E4%BB%B6%E6%A0%88-ixuca) | Release |
+|--------|-----------|---------|
+| BI-V150 | 4.2.0     |  25.03  |
+| BI-V100 | 3.0.0     |  23.06  |
+
+## Model Preparation
+
+### Prepare Resources
+
+Go to visit [COCO official website](https://cocodataset.org/#download), then select the COCO dataset you want to
+download.
+
+Take coco2017 dataset as an example, specify `/path/to/coco2017` to your COCO path in later training process, the
+unzipped dataset path structure sholud look like:
+
+```bash
+coco2017
+├── annotations
+│   ├── instances_train2017.json
+│   ├── instances_val2017.json
+│   └── ...
+├── train2017
+│   ├── 000000000009.jpg
+│   ├── 000000000025.jpg
+│   └── ...
+├── val2017
+│   ├── 000000000139.jpg
+│   ├── 000000000285.jpg
+│   └── ...
+├── train2017.txt
+├── val2017.txt
+└── ...
+```
+
+```bash
+mkdir -p <project_path>/datasets/
+ln -s /path/to/coco2017 <project_path>/datasets/
+```
+
+### Install Dependencies
+
+```bash
+# Install ultralytics
+pip3 install ultralytics
+```
+
+## Model Training
+
+```bash
+python3 train.py
+```
+
+## Model Results
+
+| Model  | GPU        | FP32     |
+|--------|------------|----------|
+| YOLOv11 | BI-V150 x8 | MAP=39.5 |
+
+## References
+
+- [ultralytics](https://github.com/ultralytics/ultralytics)
diff --git a/cv/detection/yolov11/pytorch/train.py b/cv/detection/yolov11/pytorch/train.py
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+# Copyright (c) 2023, Shanghai Iluvatar CoreX Semiconductor Co., Ltd.
+# All Rights Reserved.
+#
+#    Licensed under the Apache License, Version 2.0 (the "License"); you may
+#    not use this file except in compliance with the License. You may obtain
+#    a copy of the License at
+#
+#         http://www.apache.org/licenses/LICENSE-2.0
+#
+#    Unless required by applicable law or agreed to in writing, software
+#    distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
+#    WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
+#    License for the specific language governing permissions and limitations
+#    under the License.
+
+from ultralytics import YOLO
+
+# Load a model
+model = YOLO("yolov11n.yaml")  # build a new model from scratch
+# model = YOLO("yolov11n.pt")  # load a pretrained model (recommended for training)
+
+# Use the model
+model.train(data="coco.yaml",epochs=100, imgsz=640,batch=128,device="0,1,2,3,4,5,6,7")  # train the model