--- title: DDColor canonical_url: "https://www.modelscope.cn/models/Qualcomm-AI-Hub/DDColor" md_url: "https://www.modelscope.cn/models/Qualcomm-AI-Hub/DDColor.md" repository: Qualcomm-AI-Hub/DDColor last_updated: 2026-10-16 license: apache-2.0 pipeline_tag: image-to-image tasks: - image-to-image downloads: 0 stars: 0 tags: - android --- # DDColor > DDColor - Qualcomm-AI-Hub 在 ModelScope 开源的模型。DDColor: Optimized for Qualcomm Devices Qualcomm-AI-Hub/DDColor 是 ModelScope 魔搭社区上的image-to-image模型，采用 apache-2.0 许可。 - **Repository**: Qualcomm-AI-Hub/DDColor - **License**: apache-2.0 - **Tasks**: image-to-image - **Tags**: android - **Downloads**: 0 - **Stars**: 0 - **Last updated**: 2026-10-16 Source: https://www.modelscope.cn/models/Qualcomm-AI-Hub/DDColor --- ![](https://china-qaihub-public-assets.s3.cn-northwest-1.amazonaws.com.cn/qai-hub-models/models/ddcolor/web-assets/model_demo.png) # DDColor: Optimized for Qualcomm Devices DDColor is a coloring algorithm that produces natural, vivid color results from incoming black and white images. This is based on the implementation of DDColor found [here](https://github.com/piddnad/DDColor/). 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/ddcolor) 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/ddcolor/releases/v0.62.1/ddcolor-onnx-float.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/ddcolor/releases/v0.62.1/ddcolor-qnn_dlc-float.zip) | TFLITE | float | Universal | QAIRT 2.45 | [Download](https://china-qaihub-public-assets.s3.cn-northwest-1.amazonaws.com.cn/qai-hub-models/models/ddcolor/releases/v0.62.1/ddcolor-tflite-float.zip) For more device-specific assets and performance metrics, visit **[DDColor on Qualcomm® AI Hub](https://aihub.qualcomm.cn/models/ddcolor)**. ### 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/ddcolor) 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 [DDColor on GitHub](https://github.com/qualcomm/ai-hub-models-cn/blob/main/src/qai_hub_models/models/ddcolor) for usage instructions. ## Model Details **Model Type:** Model_use_case.image_editing **Model Stats:** - Input resolution: 224x224 - Model checkpoint: ddcolor_paper_tiny.pth - Model size (float): 215 MB - Model size (w8a8): 54.8 MB - Number of parameters: 56.3M ## Performance Summary | Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |---|---|---|---|---|---|--- | DDColor | ONNX | float | Snapdragon® X2 Elite | 28.205 ms | 2 - 2 MB | NPU | DDColor | ONNX | float | Snapdragon® X Elite | 72.412 ms | 112 - 112 MB | NPU | DDColor | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 46.458 ms | 2 - 1484 MB | NPU | DDColor | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 85.859 ms | 2 - 637 MB | NPU | DDColor | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 63.169 ms | 1 - 5 MB | NPU | DDColor | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 73.064 ms | 0 - 130 MB | NPU | DDColor | ONNX | float | Qualcomm® QCS8450 | 85.859 ms | 2 - 637 MB | NPU | DDColor | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 81.613 ms | 1 - 4 MB | NPU | DDColor | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 72.412 ms | 112 - 112 MB | NPU | DDColor | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 35.256 ms | 1 - 798 MB | NPU | DDColor | ONNX | float | Snapdragon® 8 Elite Mobile | 35.256 ms | 1 - 798 MB | NPU | DDColor | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 27.415 ms | 2 - 739 MB | NPU | DDColor | QNN_DLC | float | Snapdragon® X2 Elite | 27.758 ms | 1 - 1 MB | NPU | DDColor | QNN_DLC | float | Snapdragon® X Elite | 62.449 ms | 1 - 1 MB | NPU | DDColor | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 41.563 ms | 1 - 560 MB | NPU | DDColor | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 73.31 ms | 0 - 462 MB | NPU | DDColor | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 59.598 ms | 1 - 4 MB | NPU | DDColor | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 62.498 ms | 1 - 11 MB | NPU | DDColor | QNN_DLC | float | Qualcomm® SA8775P | 65.734 ms | 1 - 452 MB | NPU | DDColor | QNN_DLC | float | Qualcomm® SA8650P | 65.734 ms | 1 - 452 MB | NPU | DDColor | QNN_DLC | float | Qualcomm® SA8255P | 65.734 ms | 1 - 452 MB | NPU | DDColor | QNN_DLC | float | Qualcomm® QCS8450 | 73.31 ms | 0 - 462 MB | NPU | DDColor | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 66.518 ms | 1 - 4 MB | NPU | DDColor | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 62.449 ms | 1 - 1 MB | NPU | DDColor | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 31.624 ms | 0 - 615 MB | NPU | DDColor | QNN_DLC | float | Qualcomm® SA7255P | 129.606 ms | 1 - 453 MB | NPU | DDColor | QNN_DLC | float | Qualcomm® SA8295P | 69.507 ms | 0 - 330 MB | NPU | DDColor | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 31.624 ms | 0 - 615 MB | NPU | DDColor | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 27.375 ms | 0 - 634 MB | NPU | DDColor | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 43.13 ms | 1 - 1422 MB | NPU | DDColor | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 80.963 ms | 1 - 550 MB | NPU | DDColor | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 58.147 ms | 1 - 117 MB | NPU | DDColor | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 67.849 ms | 1 - 4 MB | NPU | DDColor | TFLITE | float | Qualcomm® SA8775P | 72.46 ms | 1 - 852 MB | NPU | DDColor | TFLITE | float | Qualcomm® SA8650P | 72.46 ms | 1 - 852 MB | NPU | DDColor | TFLITE | float | Qualcomm® SA8255P | 72.46 ms | 1 - 852 MB | NPU | DDColor | TFLITE | float | Qualcomm® QCS8450 | 80.963 ms | 1 - 550 MB | NPU | DDColor | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 71.896 ms | 1 - 116 MB | NPU | DDColor | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 33.823 ms | 1 - 979 MB | NPU | DDColor | TFLITE | float | Qualcomm® SA7255P | 124.44 ms | 1 - 801 MB | NPU | DDColor | TFLITE | float | Qualcomm® SA8295P | 73.57 ms | 1 - 378 MB | NPU | DDColor | TFLITE | float | Snapdragon® 8 Elite Mobile | 33.823 ms | 1 - 979 MB | NPU | DDColor | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 27.512 ms | 1 - 1037 MB | NPU ## License * The license for the original implementation of DDColor can be found [here](https://github.com/piddnad/DDColor/blob/master/LICENSE). ## References * [DDColor: Towards Photo-Realistic Image Colorization via Dual Decoders](https://arxiv.org/abs/2201.03545) * [Source Model Implementation](https://github.com/piddnad/DDColor/) ## Community * For questions or feedback, chat with our engineers in [Qualcomm® AI Hub Workbench](https://workbench.aihub.qualcomm.cn).