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library_name: pytorch
license: other
tags:
- android
pipeline_tag: object-detection
---
# Conditional-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 Conditional-DETR-ResNet50 found [here](https://github.com/huggingface/transformers/tree/main/src/transformers/models/conditional_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/qai_hub_models/models/conditional_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 2.42, ONNX Runtime 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/conditional_detr_resnet50/releases/v0.49.1/conditional_detr_resnet50-onnx-float.zip)
| ONNX | w8a16 | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/conditional_detr_resnet50/releases/v0.49.1/conditional_detr_resnet50-onnx-w8a16.zip)
| QNN_DLC | float | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/conditional_detr_resnet50/releases/v0.49.1/conditional_detr_resnet50-qnn_dlc-float.zip)
| QNN_DLC | w8a16 | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/conditional_detr_resnet50/releases/v0.49.1/conditional_detr_resnet50-qnn_dlc-w8a16.zip)
| TFLITE | float | Universal | QAIRT 2.43, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/conditional_detr_resnet50/releases/v0.49.1/conditional_detr_resnet50-tflite-float.zip)
For more device-specific assets and performance metrics, visit **[Conditional-DETR-ResNet50 on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/conditional_detr_resnet50)**.
### Option 2: Export with Custom Configurations
Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/main/qai_hub_models/models/conditional_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 [Conditional-DETR-ResNet50 on GitHub](https://github.com/qualcomm/ai-hub-models/blob/main/qai_hub_models/models/conditional_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: 43.6M
- Model size (float): 166 MB
## Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
|---|---|---|---|---|---|---
| Conditional-DETR-ResNet50 | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 8.357 ms | 5 - 406 MB | NPU
| Conditional-DETR-ResNet50 | ONNX | float | Snapdragon® X2 Elite | 8.912 ms | 82 - 82 MB | NPU
| Conditional-DETR-ResNet50 | ONNX | float | Snapdragon® X Elite | 19.876 ms | 81 - 81 MB | NPU
| Conditional-DETR-ResNet50 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 14.891 ms | 1 - 481 MB | NPU
| Conditional-DETR-ResNet50 | ONNX | float | Qualcomm® QCS8550 (Proxy) | 19.668 ms | 0 - 102 MB | NPU
| Conditional-DETR-ResNet50 | ONNX | float | Qualcomm® QCS9075 | 30.981 ms | 5 - 12 MB | NPU
| Conditional-DETR-ResNet50 | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 10.967 ms | 2 - 398 MB | NPU
| Conditional-DETR-ResNet50 | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 8.814 ms | 5 - 349 MB | NPU
| Conditional-DETR-ResNet50 | QNN_DLC | float | Snapdragon® X2 Elite | 10.415 ms | 5 - 5 MB | NPU
| Conditional-DETR-ResNet50 | QNN_DLC | float | Snapdragon® X Elite | 23.144 ms | 5 - 5 MB | NPU
| Conditional-DETR-ResNet50 | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 16.814 ms | 4 - 433 MB | NPU
| Conditional-DETR-ResNet50 | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 97.937 ms | 0 - 325 MB | NPU
| Conditional-DETR-ResNet50 | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 22.691 ms | 5 - 7 MB | NPU
| Conditional-DETR-ResNet50 | QNN_DLC | float | Qualcomm® SA8775P | 32.012 ms | 1 - 325 MB | NPU
| Conditional-DETR-ResNet50 | QNN_DLC | float | Qualcomm® QCS9075 | 33.443 ms | 5 - 11 MB | NPU
| Conditional-DETR-ResNet50 | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 46.136 ms | 4 - 373 MB | NPU
| Conditional-DETR-ResNet50 | QNN_DLC | float | Qualcomm® SA7255P | 97.937 ms | 0 - 325 MB | NPU
| Conditional-DETR-ResNet50 | QNN_DLC | float | Qualcomm® SA8295P | 34.259 ms | 0 - 281 MB | NPU
| Conditional-DETR-ResNet50 | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 11.561 ms | 5 - 341 MB | NPU
| Conditional-DETR-ResNet50 | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 9.293 ms | 0 - 379 MB | NPU
| Conditional-DETR-ResNet50 | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 16.896 ms | 0 - 464 MB | NPU
| Conditional-DETR-ResNet50 | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 92.822 ms | 0 - 364 MB | NPU
| Conditional-DETR-ResNet50 | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 22.434 ms | 0 - 3 MB | NPU
| Conditional-DETR-ResNet50 | TFLITE | float | Qualcomm® SA8775P | 30.179 ms | 0 - 422 MB | NPU
| Conditional-DETR-ResNet50 | TFLITE | float | Qualcomm® QCS9075 | 33.573 ms | 0 - 93 MB | NPU
| Conditional-DETR-ResNet50 | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 46.043 ms | 0 - 404 MB | NPU
| Conditional-DETR-ResNet50 | TFLITE | float | Qualcomm® SA7255P | 92.822 ms | 0 - 364 MB | NPU
| Conditional-DETR-ResNet50 | TFLITE | float | Qualcomm® SA8295P | 34.37 ms | 0 - 311 MB | NPU
| Conditional-DETR-ResNet50 | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 11.885 ms | 0 - 375 MB | NPU
## License
* The license for the original implementation of Conditional-DETR-ResNet50 can be found
[here](https://github.com/huggingface/transformers/blob/main/LICENSE).
## References
* [Conditional {DETR} for Fast Training Convergence](https://arxiv.org/abs/2108.06152)
* [Source Model Implementation](https://github.com/huggingface/transformers/tree/main/src/transformers/models/conditional_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).
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