--- title: DDRNet23-Slim canonical_url: "https://www.modelscope.cn/models/Qualcomm-AI-Hub/DDRNet23-Slim" md_url: "https://www.modelscope.cn/models/Qualcomm-AI-Hub/DDRNet23-Slim.md" repository: Qualcomm-AI-Hub/DDRNet23-Slim last_updated: 2026-10-16 license: mit pipeline_tag: image-segmentation tasks: - image-segmentation downloads: 0 stars: 0 tags: - real_time - android --- # DDRNet23-Slim > DDRNet23-Slim - Qualcomm-AI-Hub 在 ModelScope 开源的模型。DDRNet23-Slim: Optimized for Qualcomm Devices Qualcomm-AI-Hub/DDRNet23-Slim 是 ModelScope 魔搭社区上的image-segmentation模型，采用 mit 许可。 - **Repository**: Qualcomm-AI-Hub/DDRNet23-Slim - **License**: mit - **Tasks**: image-segmentation - **Tags**: real_time, android - **Downloads**: 0 - **Stars**: 0 - **Last updated**: 2026-10-16 Source: https://www.modelscope.cn/models/Qualcomm-AI-Hub/DDRNet23-Slim --- ![](https://china-qaihub-public-assets.s3.cn-northwest-1.amazonaws.com.cn/qai-hub-models/models/ddrnet23_slim/web-assets/model_demo.png) # DDRNet23-Slim: Optimized for Qualcomm Devices DDRNet23Slim is a machine learning model that segments an image into semantic classes, specifically designed for road-based scenes. It is designed for the application of self-driving cars. This is based on the implementation of DDRNet23-Slim found [here](https://github.com/chenjun2hao/DDRNet.pytorch). This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models-cn/blob/main/src/qai_hub_models/models/ddrnet23_slim) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary). Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.cn) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device. ## Getting Started There are two ways to deploy this model on your device: ### Option 1: Download Pre-Exported Models Below are pre-exported model assets ready for deployment. | Runtime | Precision | Chipset | SDK Versions | Download | |---|---|---|---|---| | ONNX | float | Universal | QAIRT 2.45, ONNX Runtime 1.27.1 | [Download](https://china-qaihub-public-assets.s3.cn-northwest-1.amazonaws.com.cn/qai-hub-models/models/ddrnet23_slim/releases/v0.62.1/ddrnet23_slim-onnx-float.zip) | ONNX | w8a8 | Universal | QAIRT 2.45, ONNX Runtime 1.27.1 | [Download](https://china-qaihub-public-assets.s3.cn-northwest-1.amazonaws.com.cn/qai-hub-models/models/ddrnet23_slim/releases/v0.62.1/ddrnet23_slim-onnx-w8a8.zip) | QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://china-qaihub-public-assets.s3.cn-northwest-1.amazonaws.com.cn/qai-hub-models/models/ddrnet23_slim/releases/v0.62.1/ddrnet23_slim-qnn_dlc-float.zip) | QNN_DLC | w8a8 | Universal | QAIRT 2.45 | [Download](https://china-qaihub-public-assets.s3.cn-northwest-1.amazonaws.com.cn/qai-hub-models/models/ddrnet23_slim/releases/v0.62.1/ddrnet23_slim-qnn_dlc-w8a8.zip) | TFLITE | float | Universal | QAIRT 2.45 | [Download](https://china-qaihub-public-assets.s3.cn-northwest-1.amazonaws.com.cn/qai-hub-models/models/ddrnet23_slim/releases/v0.62.1/ddrnet23_slim-tflite-float.zip) For more device-specific assets and performance metrics, visit **[DDRNet23-Slim on Qualcomm® AI Hub](https://aihub.qualcomm.cn/models/ddrnet23_slim)**. ### Option 2: Export with Custom Configurations Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models-cn/blob/main/src/qai_hub_models/models/ddrnet23_slim) Python library to compile and export the model with your own: - Custom weights (e.g., fine-tuned checkpoints) - Custom input shapes - Target device and runtime configurations This option is ideal if you need to customize the model beyond the default configuration provided here. See our repository for [DDRNet23-Slim on GitHub](https://github.com/qualcomm/ai-hub-models-cn/blob/main/src/qai_hub_models/models/ddrnet23_slim) for usage instructions. ## Model Details **Model Type:** Model_use_case.semantic_segmentation **Model Stats:** - Inference latency: RealTime - Input resolution: 2048x1024 - Model checkpoint: DDRNet23s_imagenet.pth - Model size (float): 21.7 MB - Model size (w8a8): 6.11 MB - Number of output classes: 19 - Number of parameters: 6.13M ## Performance Summary | Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |---|---|---|---|---|---|--- | DDRNet23-Slim | ONNX | float | Snapdragon® X2 Elite | 11.668 ms | 24 - 24 MB | NPU | DDRNet23-Slim | ONNX | float | Snapdragon® X Elite | 27.666 ms | 24 - 24 MB | NPU | DDRNet23-Slim | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 19.683 ms | 29 - 298 MB | NPU | DDRNet23-Slim | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 46.211 ms | 24 - 296 MB | NPU | DDRNet23-Slim | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 34.437 ms | 24 - 51 MB | NPU | DDRNet23-Slim | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 28.647 ms | 24 - 40 MB | NPU | DDRNet23-Slim | ONNX | float | Qualcomm® QCS8450 | 46.211 ms | 24 - 296 MB | NPU | DDRNet23-Slim | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 35.036 ms | 24 - 51 MB | NPU | DDRNet23-Slim | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 27.666 ms | 24 - 24 MB | NPU | DDRNet23-Slim | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 14.884 ms | 6 - 193 MB | NPU | DDRNet23-Slim | ONNX | float | Snapdragon® 8 Elite Mobile | 14.884 ms | 6 - 193 MB | NPU | DDRNet23-Slim | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 11.388 ms | 5 - 218 MB | NPU | DDRNet23-Slim | ONNX | w8a8 | Snapdragon® X2 Elite | 43.858 ms | 7 - 7 MB | NPU | DDRNet23-Slim | ONNX | w8a8 | Snapdragon® X Elite | 56.063 ms | 7 - 7 MB | NPU | DDRNet23-Slim | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 39.61 ms | 7 - 252 MB | NPU | DDRNet23-Slim | ONNX | w8a8 | Snapdragon® 8 Gen 1 Mobile | 55.145 ms | 8 - 252 MB | NPU | DDRNet23-Slim | ONNX | w8a8 | Qualcomm® Dragonwing™ QCS6490 | 152.56 ms | 6 - 9 MB | NPU | DDRNet23-Slim | ONNX | w8a8 | Qualcomm® Dragonwing™ IQ-8275 | 49.577 ms | 6 - 10 MB | NPU | DDRNet23-Slim | ONNX | w8a8 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 53.38 ms | 6 - 16 MB | NPU | DDRNet23-Slim | ONNX | w8a8 | Qualcomm® QCS8450 | 55.145 ms | 8 - 252 MB | NPU | DDRNet23-Slim | ONNX | w8a8 | Qualcomm® Dragonwing™ IQ-9075 | 52.62 ms | 6 - 9 MB | NPU | DDRNet23-Slim | ONNX | w8a8 | Qualcomm® Dragonwing™ IQ-X7181 | 56.063 ms | 7 - 7 MB | NPU | DDRNet23-Slim | ONNX | w8a8 | Qualcomm® Dragonwing™ Q-6690 | 194.289 ms | 5 - 205 MB | NPU | DDRNet23-Slim | ONNX | w8a8 | Qualcomm® Dragonwing™ Q-7790 | 53.742 ms | 6 - 207 MB | NPU | DDRNet23-Slim | ONNX | w8a8 | Qualcomm® Dragonwing™ Q-8750 | 41.02 ms | 2 - 201 MB | NPU | DDRNet23-Slim | ONNX | w8a8 | Snapdragon® 8 Elite Mobile | 41.02 ms | 2 - 201 MB | NPU | DDRNet23-Slim | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 43.371 ms | 1 - 202 MB | NPU | DDRNet23-Slim | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 53.742 ms | 6 - 207 MB | NPU | DDRNet23-Slim | QNN_DLC | float | Snapdragon® X2 Elite | 11.829 ms | 24 - 24 MB | NPU | DDRNet23-Slim | QNN_DLC | float | Snapdragon® X Elite | 33.886 ms | 24 - 24 MB | NPU | DDRNet23-Slim | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 22.399 ms | 17 - 290 MB | NPU | DDRNet23-Slim | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 66.58 ms | 25 - 301 MB | NPU | DDRNet23-Slim | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 38.336 ms | 24 - 53 MB | NPU | DDRNet23-Slim | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 32.796 ms | 24 - 27 MB | NPU | DDRNet23-Slim | QNN_DLC | float | Qualcomm® SA8775P | 40.464 ms | 24 - 222 MB | NPU | DDRNet23-Slim | QNN_DLC | float | Qualcomm® SA8650P | 40.464 ms | 24 - 222 MB | NPU | DDRNet23-Slim | QNN_DLC | float | Qualcomm® SA8255P | 40.464 ms | 24 - 222 MB | NPU | DDRNet23-Slim | QNN_DLC | float | Qualcomm® QCS8450 | 66.58 ms | 25 - 301 MB | NPU | DDRNet23-Slim | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 41.359 ms | 24 - 52 MB | NPU | DDRNet23-Slim | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 33.886 ms | 24 - 24 MB | NPU | DDRNet23-Slim | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 15.467 ms | 17 - 237 MB | NPU | DDRNet23-Slim | QNN_DLC | float | Qualcomm® SA7255P | 98.441 ms | 24 - 221 MB | NPU | DDRNet23-Slim | QNN_DLC | float | Qualcomm® SA8295P | 43.476 ms | 24 - 230 MB | NPU | DDRNet23-Slim | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 15.467 ms | 17 - 237 MB | NPU | DDRNet23-Slim | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 10.526 ms | 20 - 257 MB | NPU | DDRNet23-Slim | QNN_DLC | w8a8 | Snapdragon® X2 Elite | 29.67 ms | 6 - 6 MB | NPU | DDRNet23-Slim | QNN_DLC | w8a8 | Snapdragon® X Elite | 58.866 ms | 6 - 6 MB | NPU | DDRNet23-Slim | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 42.002 ms | 6 - 251 MB | NPU | DDRNet23-Slim | QNN_DLC | w8a8 | Snapdragon® 8 Gen 1 Mobile | 80.248 ms | 7 - 254 MB | NPU | DDRNet23-Slim | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ IQ-8275 | 54.958 ms | 6 - 15 MB | NPU | DDRNet23-Slim | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 56.106 ms | 6 - 8 MB | NPU | DDRNet23-Slim | QNN_DLC | w8a8 | Qualcomm® SA8775P | 56.921 ms | 6 - 206 MB | NPU | DDRNet23-Slim | QNN_DLC | w8a8 | Qualcomm® SA8650P | 56.921 ms | 6 - 206 MB | NPU | DDRNet23-Slim | QNN_DLC | w8a8 | Qualcomm® SA8255P | 56.921 ms | 6 - 206 MB | NPU | DDRNet23-Slim | QNN_DLC | w8a8 | Qualcomm® QCS8450 | 80.248 ms | 7 - 254 MB | NPU | DDRNet23-Slim | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ IQ-9075 | 57.234 ms | 6 - 14 MB | NPU | DDRNet23-Slim | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ IQ-X7181 | 58.866 ms | 6 - 6 MB | NPU | DDRNet23-Slim | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ Q-8750 | 39.597 ms | 6 - 222 MB | NPU | DDRNet23-Slim | QNN_DLC | w8a8 | Qualcomm® SA7255P | 107.866 ms | 6 - 205 MB | NPU | DDRNet23-Slim | QNN_DLC | w8a8 | Qualcomm® SA8295P | 66.523 ms | 6 - 207 MB | NPU | DDRNet23-Slim | QNN_DLC | w8a8 | Snapdragon® 8 Elite Mobile | 39.597 ms | 6 - 222 MB | NPU | DDRNet23-Slim | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 28.762 ms | 6 - 240 MB | NPU | DDRNet23-Slim | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 22.488 ms | 2 - 283 MB | NPU | DDRNet23-Slim | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 66.628 ms | 2 - 287 MB | NPU | DDRNet23-Slim | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 38.304 ms | 0 - 42 MB | NPU | DDRNet23-Slim | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 33.183 ms | 2 - 6 MB | NPU | DDRNet23-Slim | TFLITE | float | Qualcomm® SA8775P | 40.407 ms | 3 - 205 MB | NPU | DDRNet23-Slim | TFLITE | float | Qualcomm® SA8650P | 40.407 ms | 3 - 205 MB | NPU | DDRNet23-Slim | TFLITE | float | Qualcomm® SA8255P | 40.407 ms | 3 - 205 MB | NPU | DDRNet23-Slim | TFLITE | float | Qualcomm® QCS8450 | 66.628 ms | 2 - 287 MB | NPU | DDRNet23-Slim | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 41.017 ms | 0 - 41 MB | NPU | DDRNet23-Slim | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 15.674 ms | 2 - 229 MB | NPU | DDRNet23-Slim | TFLITE | float | Qualcomm® SA7255P | 98.325 ms | 3 - 205 MB | NPU | DDRNet23-Slim | TFLITE | float | Qualcomm® SA8295P | 43.493 ms | 2 - 214 MB | NPU | DDRNet23-Slim | TFLITE | float | Snapdragon® 8 Elite Mobile | 15.674 ms | 2 - 229 MB | NPU | DDRNet23-Slim | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 10.458 ms | 2 - 242 MB | NPU ## License * The license for the original implementation of DDRNet23-Slim can be found [here](https://github.com/chenjun2hao/DDRNet.pytorch/blob/main/LICENSE). ## References * [Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes](https://arxiv.org/abs/2101.06085) * [Source Model Implementation](https://github.com/chenjun2hao/DDRNet.pytorch) ## Community * For questions or feedback, chat with our engineers in [Qualcomm® AI Hub Workbench](https://workbench.aihub.qualcomm.cn).