--- library_name: pytorch license: other tags: - bu_auto - android pipeline_tag: object-detection --- ![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/detr_resnet50/web-assets/model_demo.png) # DETR-ResNet50: Optimized for Qualcomm Devices DETR is a machine learning model that can detect objects (trained on COCO dataset). This is based on the implementation of DETR-ResNet50 found [here](https://github.com/facebookresearch/detr). 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/blob/main/src/qai_hub_models/models/detr_resnet50) 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.com) 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 1.25.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/detr_resnet50/releases/v0.56.0/detr_resnet50-onnx-float.zip) | ONNX | w8a16_mixed_fp16 | Universal | QAIRT 2.45, ONNX Runtime 1.25.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/detr_resnet50/releases/v0.56.0/detr_resnet50-onnx-w8a16_mixed_fp16.zip) | QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/detr_resnet50/releases/v0.56.0/detr_resnet50-qnn_dlc-float.zip) | TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/detr_resnet50/releases/v0.56.0/detr_resnet50-tflite-float.zip) For more device-specific assets and performance metrics, visit **[DETR-ResNet50 on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/detr_resnet50)**. ### Option 2: Export with Custom Configurations Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/main/src/qai_hub_models/models/detr_resnet50) 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 [DETR-ResNet50 on GitHub](https://github.com/qualcomm/ai-hub-models/blob/main/src/qai_hub_models/models/detr_resnet50) for usage instructions. ## Model Details **Model Type:** Model_use_case.object_detection **Model Stats:** - Model checkpoint: ResNet50 - Input resolution: 480x480 - Number of parameters: 41.4M - Model size (float): 158 MB ## Performance Summary | Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |---|---|---|---|---|---|--- | DETR-ResNet50 | ONNX | float | Snapdragon® X2 Elite | 8.217 ms | 176 - 176 MB | NPU | DETR-ResNet50 | ONNX | float | Snapdragon® X Elite | 17.83 ms | 144 - 144 MB | NPU | DETR-ResNet50 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 13.328 ms | 3 - 363 MB | NPU | DETR-ResNet50 | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 36.104 ms | 5 - 313 MB | NPU | DETR-ResNet50 | ONNX | float | Qualcomm® QCS8550 (Proxy) | 17.902 ms | 0 - 142 MB | NPU | DETR-ResNet50 | ONNX | float | Qualcomm® QCS8450 | 36.104 ms | 5 - 313 MB | NPU | DETR-ResNet50 | ONNX | float | Snapdragon® 8 Elite Mobile | 9.951 ms | 2 - 271 MB | NPU | DETR-ResNet50 | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 7.374 ms | 3 - 311 MB | NPU | DETR-ResNet50 | ONNX | float | Qualcomm® QCS9075 | 27.505 ms | 5 - 50 MB | NPU | DETR-ResNet50 | ONNX | float | Qualcomm® QCS8750 | 9.951 ms | 2 - 271 MB | NPU | DETR-ResNet50 | ONNX | float | Qualcomm® QCS7181 | 17.83 ms | 144 - 144 MB | NPU | DETR-ResNet50 | ONNX | w8a16_mixed_fp16 | Snapdragon® 8 Gen 3 Mobile | 52.062 ms | 88 - 502 MB | NPU | DETR-ResNet50 | ONNX | w8a16_mixed_fp16 | Qualcomm® QCS8550 (Proxy) | 67.981 ms | 0 - 60 MB | NPU | DETR-ResNet50 | ONNX | w8a16_mixed_fp16 | Snapdragon® 8 Elite Mobile | 41.988 ms | 20 - 368 MB | NPU | DETR-ResNet50 | ONNX | w8a16_mixed_fp16 | Snapdragon® 8 Elite Gen 5 Mobile | 33.05 ms | 21 - 387 MB | NPU | DETR-ResNet50 | ONNX | w8a16_mixed_fp16 | Qualcomm® QCS9075 | 101.433 ms | 22 - 65 MB | NPU | DETR-ResNet50 | ONNX | w8a16_mixed_fp16 | Qualcomm® QCS8750 | 41.988 ms | 20 - 368 MB | NPU | DETR-ResNet50 | QNN_DLC | float | Snapdragon® X2 Elite | 9.014 ms | 5 - 5 MB | NPU | DETR-ResNet50 | QNN_DLC | float | Snapdragon® X Elite | 19.532 ms | 5 - 5 MB | NPU | DETR-ResNet50 | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 13.634 ms | 0 - 351 MB | NPU | DETR-ResNet50 | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 42.016 ms | 5 - 304 MB | NPU | DETR-ResNet50 | QNN_DLC | float | Qualcomm® QCS8275 | 86.004 ms | 1 - 268 MB | NPU | DETR-ResNet50 | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 19.308 ms | 5 - 12 MB | NPU | DETR-ResNet50 | QNN_DLC | float | Qualcomm® QCS8450 | 42.016 ms | 5 - 304 MB | NPU | DETR-ResNet50 | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 10.436 ms | 0 - 273 MB | NPU | DETR-ResNet50 | QNN_DLC | float | Qualcomm® SA8295P | 31.193 ms | 0 - 221 MB | NPU | DETR-ResNet50 | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 7.84 ms | 5 - 289 MB | NPU | DETR-ResNet50 | QNN_DLC | float | Qualcomm® SA7255P | 86.004 ms | 1 - 268 MB | NPU | DETR-ResNet50 | QNN_DLC | float | Qualcomm® QCS9075 | 31.038 ms | 5 - 11 MB | NPU | DETR-ResNet50 | QNN_DLC | float | Qualcomm® QCS8750 | 10.436 ms | 0 - 273 MB | NPU | DETR-ResNet50 | QNN_DLC | float | Qualcomm® QCS7181 | 19.532 ms | 5 - 5 MB | NPU | DETR-ResNet50 | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 13.625 ms | 0 - 386 MB | NPU | DETR-ResNet50 | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 41.35 ms | 0 - 329 MB | NPU | DETR-ResNet50 | TFLITE | float | Qualcomm® QCS8275 | 86.031 ms | 0 - 293 MB | NPU | DETR-ResNet50 | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 19.121 ms | 0 - 3 MB | NPU | DETR-ResNet50 | TFLITE | float | Qualcomm® SA8775P | 601.937 ms | 0 - 12 MB | CPU | DETR-ResNet50 | TFLITE | float | Qualcomm® SA8650P | 601.937 ms | 0 - 12 MB | CPU | DETR-ResNet50 | TFLITE | float | Qualcomm® SA8255P | 601.937 ms | 0 - 12 MB | CPU | DETR-ResNet50 | TFLITE | float | Qualcomm® QCS8450 | 41.35 ms | 0 - 329 MB | NPU | DETR-ResNet50 | TFLITE | float | Snapdragon® 8 Elite Mobile | 10.52 ms | 0 - 306 MB | NPU | DETR-ResNet50 | TFLITE | float | Qualcomm® SA8295P | 31.09 ms | 0 - 247 MB | NPU | DETR-ResNet50 | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 7.993 ms | 0 - 310 MB | NPU | DETR-ResNet50 | TFLITE | float | Qualcomm® SA7255P | 86.031 ms | 0 - 293 MB | NPU | DETR-ResNet50 | TFLITE | float | Qualcomm® QCS9075 | 30.4 ms | 0 - 88 MB | NPU | DETR-ResNet50 | TFLITE | float | Qualcomm® QCS8750 | 10.52 ms | 0 - 306 MB | NPU ## License * The license for the original implementation of DETR-ResNet50 can be found [here](https://github.com/facebookresearch/detr/blob/main/LICENSE). ## References * [End-to-End Object Detection with Transformers](https://arxiv.org/abs/2005.12872) * [Source Model Implementation](https://github.com/facebookresearch/detr) ## Community * Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI. * For questions or feedback please [reach out to us](mailto:ai-hub-support@qti.qualcomm.com).