DeepLabXception / README.md

v0.45.0

b9ebe80 verified 16 days ago

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	---
	library_name: pytorch
	license: other
	tags:
	- bu_auto
	- android
	pipeline_tag: image-segmentation

	---

	![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/deeplab_xception/web-assets/model_demo.png)

	# DeepLabXception: Optimized for Mobile Deployment
	## Deep Convolutional Neural Network model for semantic segmentation


	DeepLabXception is a semantic segmentation model supporting multiple backbones like ResNet-101 and Xception, with flexible dataset compatibility including COCO, VOC, and Cityscapes.

	This model is an implementation of DeepLabXception found [here](https://github.com/LikeLy-Journey/SegmenTron).


	This repository provides scripts to run DeepLabXception on Qualcomm® devices.
	More details on model performance across various devices, can be found
	[here](https://aihub.qualcomm.com/models/deeplab_xception).



	### Model Details

	- Model Type: Model_use_case.semantic_segmentation
	- Model Stats:
	- Model checkpoint: COCO_WITH_VOC_LABELS_V1
	- Input resolution: 480x520
	- Number of output classes: 21
	- Number of parameters: 41.26M
	- Model size (float): 158 MB

	\| Model \| Precision \| Device \| Chipset \| Target Runtime \| Inference Time (ms) \| Peak Memory Range (MB) \| Primary Compute Unit \| Target Model
	\|---\|---\|---\|---\|---\|---\|---\|---\|---\|
	\| DeepLabXception \| float \| QCS8275 (Proxy) \| Qualcomm® QCS8275 (Proxy) \| TFLITE \| 113.083 ms \| 0 - 317 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.tflite) \|
	\| DeepLabXception \| float \| QCS8275 (Proxy) \| Qualcomm® QCS8275 (Proxy) \| QNN_DLC \| 113.025 ms \| 3 - 212 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.dlc) \|
	\| DeepLabXception \| float \| QCS8450 (Proxy) \| Qualcomm® QCS8450 (Proxy) \| TFLITE \| 46.39 ms \| 0 - 434 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.tflite) \|
	\| DeepLabXception \| float \| QCS8450 (Proxy) \| Qualcomm® QCS8450 (Proxy) \| QNN_DLC \| 50.98 ms \| 3 - 329 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.dlc) \|
	\| DeepLabXception \| float \| QCS8550 (Proxy) \| Qualcomm® QCS8550 (Proxy) \| TFLITE \| 21.884 ms \| 0 - 3 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.tflite) \|
	\| DeepLabXception \| float \| QCS8550 (Proxy) \| Qualcomm® QCS8550 (Proxy) \| QNN_DLC \| 21.772 ms \| 3 - 5 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.dlc) \|
	\| DeepLabXception \| float \| QCS8550 (Proxy) \| Qualcomm® QCS8550 (Proxy) \| ONNX \| 21.042 ms \| 0 - 96 MB \| NPU \| [DeepLabXception.onnx.zip](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.onnx.zip) \|
	\| DeepLabXception \| float \| QCS9075 (Proxy) \| Qualcomm® QCS9075 (Proxy) \| TFLITE \| 30.499 ms \| 0 - 319 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.tflite) \|
	\| DeepLabXception \| float \| QCS9075 (Proxy) \| Qualcomm® QCS9075 (Proxy) \| QNN_DLC \| 30.466 ms \| 0 - 209 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.dlc) \|
	\| DeepLabXception \| float \| SA7255P ADP \| Qualcomm® SA7255P \| TFLITE \| 113.083 ms \| 0 - 317 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.tflite) \|
	\| DeepLabXception \| float \| SA7255P ADP \| Qualcomm® SA7255P \| QNN_DLC \| 113.025 ms \| 3 - 212 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.dlc) \|
	\| DeepLabXception \| float \| SA8295P ADP \| Qualcomm® SA8295P \| TFLITE \| 38.81 ms \| 0 - 315 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.tflite) \|
	\| DeepLabXception \| float \| SA8295P ADP \| Qualcomm® SA8295P \| QNN_DLC \| 38.868 ms \| 0 - 213 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.dlc) \|
	\| DeepLabXception \| float \| SA8775P ADP \| Qualcomm® SA8775P \| TFLITE \| 30.499 ms \| 0 - 319 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.tflite) \|
	\| DeepLabXception \| float \| SA8775P ADP \| Qualcomm® SA8775P \| QNN_DLC \| 30.466 ms \| 0 - 209 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.dlc) \|
	\| DeepLabXception \| float \| Samsung Galaxy S24 \| Snapdragon® 8 Gen 3 Mobile \| TFLITE \| 15.932 ms \| 0 - 440 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.tflite) \|
	\| DeepLabXception \| float \| Samsung Galaxy S24 \| Snapdragon® 8 Gen 3 Mobile \| QNN_DLC \| 15.952 ms \| 3 - 334 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.dlc) \|
	\| DeepLabXception \| float \| Samsung Galaxy S24 \| Snapdragon® 8 Gen 3 Mobile \| ONNX \| 15.679 ms \| 3 - 304 MB \| NPU \| [DeepLabXception.onnx.zip](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.onnx.zip) \|
	\| DeepLabXception \| float \| Samsung Galaxy S25 \| Snapdragon® 8 Elite For Galaxy Mobile \| TFLITE \| 12.31 ms \| 0 - 319 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.tflite) \|
	\| DeepLabXception \| float \| Samsung Galaxy S25 \| Snapdragon® 8 Elite For Galaxy Mobile \| QNN_DLC \| 12.284 ms \| 3 - 215 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.dlc) \|
	\| DeepLabXception \| float \| Samsung Galaxy S25 \| Snapdragon® 8 Elite For Galaxy Mobile \| ONNX \| 12.273 ms \| 3 - 184 MB \| NPU \| [DeepLabXception.onnx.zip](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.onnx.zip) \|
	\| DeepLabXception \| float \| Snapdragon 8 Elite Gen 5 QRD \| Snapdragon® 8 Elite Gen 5 Mobile \| TFLITE \| 9.179 ms \| 0 - 328 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.tflite) \|
	\| DeepLabXception \| float \| Snapdragon 8 Elite Gen 5 QRD \| Snapdragon® 8 Elite Gen 5 Mobile \| QNN_DLC \| 9.226 ms \| 3 - 236 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.dlc) \|
	\| DeepLabXception \| float \| Snapdragon 8 Elite Gen 5 QRD \| Snapdragon® 8 Elite Gen 5 Mobile \| ONNX \| 9.24 ms \| 3 - 200 MB \| NPU \| [DeepLabXception.onnx.zip](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.onnx.zip) \|
	\| DeepLabXception \| float \| Snapdragon X Elite CRD \| Snapdragon® X Elite \| QNN_DLC \| 22.62 ms \| 3 - 3 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.dlc) \|
	\| DeepLabXception \| float \| Snapdragon X Elite CRD \| Snapdragon® X Elite \| ONNX \| 21.775 ms \| 85 - 85 MB \| NPU \| [DeepLabXception.onnx.zip](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception.onnx.zip) \|
	\| DeepLabXception \| w8a8 \| Dragonwing Q-6690 MTP \| Qualcomm® QCM6690 \| TFLITE \| 89.688 ms \| 0 - 270 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.tflite) \|
	\| DeepLabXception \| w8a8 \| Dragonwing Q-6690 MTP \| Qualcomm® QCM6690 \| QNN_DLC \| 112.359 ms \| 1 - 278 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.dlc) \|
	\| DeepLabXception \| w8a8 \| Dragonwing Q-6690 MTP \| Qualcomm® QCM6690 \| ONNX \| 240.789 ms \| 88 - 106 MB \| CPU \| [DeepLabXception.onnx.zip](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.onnx.zip) \|
	\| DeepLabXception \| w8a8 \| Dragonwing RB3 Gen 2 Vision Kit \| Qualcomm® QCS6490 \| TFLITE \| 28.818 ms \| 0 - 58 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.tflite) \|
	\| DeepLabXception \| w8a8 \| Dragonwing RB3 Gen 2 Vision Kit \| Qualcomm® QCS6490 \| QNN_DLC \| 30.262 ms \| 1 - 3 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.dlc) \|
	\| DeepLabXception \| w8a8 \| Dragonwing RB3 Gen 2 Vision Kit \| Qualcomm® QCS6490 \| ONNX \| 310.37 ms \| 90 - 118 MB \| CPU \| [DeepLabXception.onnx.zip](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.onnx.zip) \|
	\| DeepLabXception \| w8a8 \| QCS8275 (Proxy) \| Qualcomm® QCS8275 (Proxy) \| TFLITE \| 18.973 ms \| 0 - 257 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.tflite) \|
	\| DeepLabXception \| w8a8 \| QCS8275 (Proxy) \| Qualcomm® QCS8275 (Proxy) \| QNN_DLC \| 20.382 ms \| 1 - 261 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.dlc) \|
	\| DeepLabXception \| w8a8 \| QCS8450 (Proxy) \| Qualcomm® QCS8450 (Proxy) \| TFLITE \| 11.81 ms \| 0 - 338 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.tflite) \|
	\| DeepLabXception \| w8a8 \| QCS8450 (Proxy) \| Qualcomm® QCS8450 (Proxy) \| QNN_DLC \| 14.937 ms \| 1 - 342 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.dlc) \|
	\| DeepLabXception \| w8a8 \| QCS8550 (Proxy) \| Qualcomm® QCS8550 (Proxy) \| TFLITE \| 6.783 ms \| 0 - 3 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.tflite) \|
	\| DeepLabXception \| w8a8 \| QCS8550 (Proxy) \| Qualcomm® QCS8550 (Proxy) \| QNN_DLC \| 8.067 ms \| 1 - 3 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.dlc) \|
	\| DeepLabXception \| w8a8 \| QCS8550 (Proxy) \| Qualcomm® QCS8550 (Proxy) \| ONNX \| 7.651 ms \| 0 - 51 MB \| NPU \| [DeepLabXception.onnx.zip](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.onnx.zip) \|
	\| DeepLabXception \| w8a8 \| QCS9075 (Proxy) \| Qualcomm® QCS9075 (Proxy) \| TFLITE \| 7.358 ms \| 0 - 255 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.tflite) \|
	\| DeepLabXception \| w8a8 \| QCS9075 (Proxy) \| Qualcomm® QCS9075 (Proxy) \| QNN_DLC \| 8.13 ms \| 1 - 258 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.dlc) \|
	\| DeepLabXception \| w8a8 \| SA7255P ADP \| Qualcomm® SA7255P \| TFLITE \| 18.973 ms \| 0 - 257 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.tflite) \|
	\| DeepLabXception \| w8a8 \| SA7255P ADP \| Qualcomm® SA7255P \| QNN_DLC \| 20.382 ms \| 1 - 261 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.dlc) \|
	\| DeepLabXception \| w8a8 \| SA8295P ADP \| Qualcomm® SA8295P \| TFLITE \| 11.583 ms \| 0 - 245 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.tflite) \|
	\| DeepLabXception \| w8a8 \| SA8295P ADP \| Qualcomm® SA8295P \| QNN_DLC \| 12.597 ms \| 1 - 251 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.dlc) \|
	\| DeepLabXception \| w8a8 \| SA8775P ADP \| Qualcomm® SA8775P \| TFLITE \| 7.358 ms \| 0 - 255 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.tflite) \|
	\| DeepLabXception \| w8a8 \| SA8775P ADP \| Qualcomm® SA8775P \| QNN_DLC \| 8.13 ms \| 1 - 258 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.dlc) \|
	\| DeepLabXception \| w8a8 \| Samsung Galaxy S24 \| Snapdragon® 8 Gen 3 Mobile \| TFLITE \| 4.997 ms \| 0 - 343 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.tflite) \|
	\| DeepLabXception \| w8a8 \| Samsung Galaxy S24 \| Snapdragon® 8 Gen 3 Mobile \| QNN_DLC \| 5.562 ms \| 1 - 349 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.dlc) \|
	\| DeepLabXception \| w8a8 \| Samsung Galaxy S24 \| Snapdragon® 8 Gen 3 Mobile \| ONNX \| 5.295 ms \| 1 - 337 MB \| NPU \| [DeepLabXception.onnx.zip](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.onnx.zip) \|
	\| DeepLabXception \| w8a8 \| Samsung Galaxy S25 \| Snapdragon® 8 Elite For Galaxy Mobile \| TFLITE \| 3.918 ms \| 0 - 240 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.tflite) \|
	\| DeepLabXception \| w8a8 \| Samsung Galaxy S25 \| Snapdragon® 8 Elite For Galaxy Mobile \| QNN_DLC \| 4.362 ms \| 1 - 259 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.dlc) \|
	\| DeepLabXception \| w8a8 \| Samsung Galaxy S25 \| Snapdragon® 8 Elite For Galaxy Mobile \| ONNX \| 4.332 ms \| 1 - 230 MB \| NPU \| [DeepLabXception.onnx.zip](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.onnx.zip) \|
	\| DeepLabXception \| w8a8 \| Snapdragon 7 Gen 4 QRD \| Snapdragon® 7 Gen 4 Mobile \| TFLITE \| 11.013 ms \| 0 - 242 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.tflite) \|
	\| DeepLabXception \| w8a8 \| Snapdragon 7 Gen 4 QRD \| Snapdragon® 7 Gen 4 Mobile \| QNN_DLC \| 12.18 ms \| 1 - 250 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.dlc) \|
	\| DeepLabXception \| w8a8 \| Snapdragon 7 Gen 4 QRD \| Snapdragon® 7 Gen 4 Mobile \| ONNX \| 227.149 ms \| 92 - 111 MB \| CPU \| [DeepLabXception.onnx.zip](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.onnx.zip) \|
	\| DeepLabXception \| w8a8 \| Snapdragon 8 Elite Gen 5 QRD \| Snapdragon® 8 Elite Gen 5 Mobile \| TFLITE \| 2.886 ms \| 0 - 247 MB \| NPU \| [DeepLabXception.tflite](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.tflite) \|
	\| DeepLabXception \| w8a8 \| Snapdragon 8 Elite Gen 5 QRD \| Snapdragon® 8 Elite Gen 5 Mobile \| QNN_DLC \| 3.234 ms \| 1 - 256 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.dlc) \|
	\| DeepLabXception \| w8a8 \| Snapdragon 8 Elite Gen 5 QRD \| Snapdragon® 8 Elite Gen 5 Mobile \| ONNX \| 3.33 ms \| 0 - 235 MB \| NPU \| [DeepLabXception.onnx.zip](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.onnx.zip) \|
	\| DeepLabXception \| w8a8 \| Snapdragon X Elite CRD \| Snapdragon® X Elite \| QNN_DLC \| 8.697 ms \| 1 - 1 MB \| NPU \| [DeepLabXception.dlc](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.dlc) \|
	\| DeepLabXception \| w8a8 \| Snapdragon X Elite CRD \| Snapdragon® X Elite \| ONNX \| 8.042 ms \| 44 - 44 MB \| NPU \| [DeepLabXception.onnx.zip](https://huggingface.co/qualcomm/DeepLabXception/blob/main/DeepLabXception_w8a8.onnx.zip) \|




	## Installation


	Install the package via pip:
	```bash
	pip install qai-hub-models
	```


	## Configure Qualcomm® AI Hub Workbench to run this model on a cloud-hosted device

	Sign-in to [Qualcomm® AI Hub Workbench](https://workbench.aihub.qualcomm.com/) with your
	Qualcomm® ID. Once signed in navigate to `Account -> Settings -> API Token`.

	With this API token, you can configure your client to run models on the cloud
	hosted devices.
	```bash
	qai-hub configure --api_token API_TOKEN
	```
	Navigate to [docs](https://workbench.aihub.qualcomm.com/docs/) for more information.



	## Demo off target

	The package contains a simple end-to-end demo that downloads pre-trained
	weights and runs this model on a sample input.

	```bash
	python -m qai_hub_models.models.deeplab_xception.demo
	```

	The above demo runs a reference implementation of pre-processing, model
	inference, and post processing.

	NOTE: If you want running in a Jupyter Notebook or Google Colab like
	environment, please add the following to your cell (instead of the above).
	```
	%run -m qai_hub_models.models.deeplab_xception.demo
	```


	### Run model on a cloud-hosted device

	In addition to the demo, you can also run the model on a cloud-hosted Qualcomm®
	device. This script does the following:
	* Performance check on-device on a cloud-hosted device
	* Downloads compiled assets that can be deployed on-device for Android.
	* Accuracy check between PyTorch and on-device outputs.

	```bash
	python -m qai_hub_models.models.deeplab_xception.export
	```



	## How does this work?

	This [export script](https://aihub.qualcomm.com/models/deeplab_xception/qai_hub_models/models/DeepLabXception/export.py)
	leverages [Qualcomm® AI Hub](https://aihub.qualcomm.com/) to optimize, validate, and deploy this model
	on-device. Lets go through each step below in detail:

	Step 1: Compile model for on-device deployment

	To compile a PyTorch model for on-device deployment, we first trace the model
	in memory using the `jit.trace` and then call the `submit_compile_job` API.

	```python
	import torch

	import qai_hub as hub
	from qai_hub_models.models.deeplab_xception import Model

	# Load the model
	torch_model = Model.from_pretrained()

	# Device
	device = hub.Device("Samsung Galaxy S25")

	# Trace model
	input_shape = torch_model.get_input_spec()
	sample_inputs = torch_model.sample_inputs()

	pt_model = torch.jit.trace(torch_model, [torch.tensor(data[0]) for _, data in sample_inputs.items()])

	# Compile model on a specific device
	compile_job = hub.submit_compile_job(
	model=pt_model,
	device=device,
	input_specs=torch_model.get_input_spec(),
	)

	# Get target model to run on-device
	target_model = compile_job.get_target_model()

	```


	Step 2: Performance profiling on cloud-hosted device

	After compiling models from step 1. Models can be profiled model on-device using the
	`target_model`. Note that this scripts runs the model on a device automatically
	provisioned in the cloud. Once the job is submitted, you can navigate to a
	provided job URL to view a variety of on-device performance metrics.
	```python
	profile_job = hub.submit_profile_job(
	model=target_model,
	device=device,
	)

	```

	Step 3: Verify on-device accuracy

	To verify the accuracy of the model on-device, you can run on-device inference
	on sample input data on the same cloud hosted device.
	```python
	input_data = torch_model.sample_inputs()
	inference_job = hub.submit_inference_job(
	model=target_model,
	device=device,
	inputs=input_data,
	)
	on_device_output = inference_job.download_output_data()

	```
	With the output of the model, you can compute like PSNR, relative errors or
	spot check the output with expected output.

	Note: This on-device profiling and inference requires access to Qualcomm®
	AI Hub Workbench. [Sign up for access](https://myaccount.qualcomm.com/signup).



	## Run demo on a cloud-hosted device

	You can also run the demo on-device.

	```bash
	python -m qai_hub_models.models.deeplab_xception.demo --eval-mode on-device
	```

	NOTE: If you want running in a Jupyter Notebook or Google Colab like
	environment, please add the following to your cell (instead of the above).
	```
	%run -m qai_hub_models.models.deeplab_xception.demo -- --eval-mode on-device
	```


	## Deploying compiled model to Android


	The models can be deployed using multiple runtimes:
	- TensorFlow Lite (`.tflite` export): [This
	tutorial](https://www.tensorflow.org/lite/android/quickstart) provides a
	guide to deploy the .tflite model in an Android application.


	- QNN (`.so` export ): This [sample
	app](https://docs.qualcomm.com/bundle/publicresource/topics/80-63442-50/sample_app.html)
	provides instructions on how to use the `.so` shared library in an Android application.


	## View on Qualcomm® AI Hub
	Get more details on DeepLabXception's performance across various devices [here](https://aihub.qualcomm.com/models/deeplab_xception).
	Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/)


	## License
	* The license for the original implementation of DeepLabXception can be found
	[here](https://github.com/pytorch/vision/blob/main/LICENSE).



	## References
	* [Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation](https://arxiv.org/abs/1802.02611)
	* [Source Model Implementation](https://github.com/LikeLy-Journey/SegmenTron)



	## 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).