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README.md
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@@ -36,28 +36,30 @@ More details on model performance across various devices, can be found
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| Model | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
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| DeepLabV3-Plus-MobileNet-Quantized | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 4.
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| DeepLabV3-Plus-MobileNet-Quantized | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 4.
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| DeepLabV3-Plus-MobileNet-Quantized | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 2.
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| DeepLabV3-Plus-MobileNet-Quantized | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 3.
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| DeepLabV3-Plus-MobileNet-Quantized | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 2.
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| DeepLabV3-Plus-MobileNet-Quantized | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 3.
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| DeepLabV3-Plus-MobileNet-Quantized | RB3 Gen 2 (Proxy) | QCS6490 Proxy | TFLITE |
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| DeepLabV3-Plus-MobileNet-Quantized | RB3 Gen 2 (Proxy) | QCS6490 Proxy | QNN | 19.
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| DeepLabV3-Plus-MobileNet-Quantized | RB5 (Proxy) | QCS8250 Proxy | TFLITE |
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| DeepLabV3-Plus-MobileNet-Quantized | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 4.
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| DeepLabV3-Plus-MobileNet-Quantized | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 3.
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| DeepLabV3-Plus-MobileNet-Quantized |
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| DeepLabV3-Plus-MobileNet-Quantized |
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| DeepLabV3-Plus-MobileNet-Quantized |
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| DeepLabV3-Plus-MobileNet-Quantized |
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| DeepLabV3-Plus-MobileNet-Quantized |
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| DeepLabV3-Plus-MobileNet-Quantized |
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| DeepLabV3-Plus-MobileNet-Quantized |
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| DeepLabV3-Plus-MobileNet-Quantized |
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| DeepLabV3-Plus-MobileNet-Quantized |
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| DeepLabV3-Plus-MobileNet-Quantized |
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| DeepLabV3-Plus-MobileNet-Quantized |
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@@ -123,7 +125,7 @@ DeepLabV3-Plus-MobileNet-Quantized
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Device : Samsung Galaxy S23 (13)
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Runtime : TFLITE
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Estimated inference time (ms) : 4.2
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Estimated peak memory usage (MB): [0,
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Total # Ops : 136
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Compute Unit(s) : NPU (136 ops)
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```
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import torch
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import qai_hub as hub
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from qai_hub_models.models.deeplabv3_plus_mobilenet_quantized import
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# Load the model
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# Device
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device = hub.Device("Samsung Galaxy S23")
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```
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| Model | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
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| DeepLabV3-Plus-MobileNet-Quantized | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 4.171 ms | 0 - 6 MB | INT8 | NPU | [DeepLabV3-Plus-MobileNet-Quantized.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.tflite) |
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| DeepLabV3-Plus-MobileNet-Quantized | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 4.745 ms | 0 - 11 MB | INT8 | NPU | [DeepLabV3-Plus-MobileNet-Quantized.so](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.so) |
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| DeepLabV3-Plus-MobileNet-Quantized | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 2.986 ms | 0 - 37 MB | INT8 | NPU | [DeepLabV3-Plus-MobileNet-Quantized.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.tflite) |
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| DeepLabV3-Plus-MobileNet-Quantized | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 3.448 ms | 1 - 33 MB | INT8 | NPU | [DeepLabV3-Plus-MobileNet-Quantized.so](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.so) |
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| DeepLabV3-Plus-MobileNet-Quantized | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 2.785 ms | 0 - 31 MB | INT8 | NPU | [DeepLabV3-Plus-MobileNet-Quantized.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.tflite) |
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| DeepLabV3-Plus-MobileNet-Quantized | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 3.447 ms | 22 - 51 MB | INT8 | NPU | Use Export Script |
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| DeepLabV3-Plus-MobileNet-Quantized | RB3 Gen 2 (Proxy) | QCS6490 Proxy | TFLITE | 17.946 ms | 0 - 41 MB | INT8 | NPU | [DeepLabV3-Plus-MobileNet-Quantized.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.tflite) |
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| DeepLabV3-Plus-MobileNet-Quantized | RB3 Gen 2 (Proxy) | QCS6490 Proxy | QNN | 19.682 ms | 1 - 9 MB | INT8 | NPU | Use Export Script |
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| DeepLabV3-Plus-MobileNet-Quantized | RB5 (Proxy) | QCS8250 Proxy | TFLITE | 163.773 ms | 4 - 12 MB | INT8 | NPU | [DeepLabV3-Plus-MobileNet-Quantized.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.tflite) |
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| DeepLabV3-Plus-MobileNet-Quantized | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 4.168 ms | 0 - 16 MB | INT8 | NPU | [DeepLabV3-Plus-MobileNet-Quantized.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.tflite) |
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| DeepLabV3-Plus-MobileNet-Quantized | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 3.894 ms | 1 - 3 MB | INT8 | NPU | Use Export Script |
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| DeepLabV3-Plus-MobileNet-Quantized | SA7255P ADP | SA7255P | TFLITE | 54.915 ms | 0 - 30 MB | INT8 | NPU | [DeepLabV3-Plus-MobileNet-Quantized.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.tflite) |
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| DeepLabV3-Plus-MobileNet-Quantized | SA7255P ADP | SA7255P | QNN | 55.251 ms | 1 - 6 MB | INT8 | NPU | Use Export Script |
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| DeepLabV3-Plus-MobileNet-Quantized | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 4.182 ms | 0 - 13 MB | INT8 | NPU | [DeepLabV3-Plus-MobileNet-Quantized.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.tflite) |
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| DeepLabV3-Plus-MobileNet-Quantized | SA8255 (Proxy) | SA8255P Proxy | QNN | 3.91 ms | 1 - 2 MB | INT8 | NPU | Use Export Script |
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| DeepLabV3-Plus-MobileNet-Quantized | SA8295P ADP | SA8295P | TFLITE | 6.651 ms | 0 - 29 MB | INT8 | NPU | [DeepLabV3-Plus-MobileNet-Quantized.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.tflite) |
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| DeepLabV3-Plus-MobileNet-Quantized | SA8295P ADP | SA8295P | QNN | 6.453 ms | 1 - 6 MB | INT8 | NPU | Use Export Script |
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| DeepLabV3-Plus-MobileNet-Quantized | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 4.161 ms | 0 - 14 MB | INT8 | NPU | [DeepLabV3-Plus-MobileNet-Quantized.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.tflite) |
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| DeepLabV3-Plus-MobileNet-Quantized | SA8650 (Proxy) | SA8650P Proxy | QNN | 3.912 ms | 1 - 2 MB | INT8 | NPU | Use Export Script |
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| DeepLabV3-Plus-MobileNet-Quantized | SA8775P ADP | SA8775P | TFLITE | 5.729 ms | 0 - 30 MB | INT8 | NPU | [DeepLabV3-Plus-MobileNet-Quantized.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.tflite) |
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| DeepLabV3-Plus-MobileNet-Quantized | SA8775P ADP | SA8775P | QNN | 5.523 ms | 1 - 6 MB | INT8 | NPU | Use Export Script |
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| DeepLabV3-Plus-MobileNet-Quantized | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 4.831 ms | 0 - 37 MB | INT8 | NPU | [DeepLabV3-Plus-MobileNet-Quantized.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.tflite) |
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| DeepLabV3-Plus-MobileNet-Quantized | QCS8450 (Proxy) | QCS8450 Proxy | QNN | 5.602 ms | 1 - 34 MB | INT8 | NPU | Use Export Script |
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| DeepLabV3-Plus-MobileNet-Quantized | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 4.26 ms | 1 - 1 MB | INT8 | NPU | Use Export Script |
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Device : Samsung Galaxy S23 (13)
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Runtime : TFLITE
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Estimated inference time (ms) : 4.2
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Estimated peak memory usage (MB): [0, 6]
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Total # Ops : 136
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Compute Unit(s) : NPU (136 ops)
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```
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import torch
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import qai_hub as hub
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from qai_hub_models.models.deeplabv3_plus_mobilenet_quantized import Model
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# Load the model
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torch_model = Model.from_pretrained()
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# Device
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device = hub.Device("Samsung Galaxy S23")
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# Trace model
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input_shape = torch_model.get_input_spec()
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sample_inputs = torch_model.sample_inputs()
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pt_model = torch.jit.trace(torch_model, [torch.tensor(data[0]) for _, data in sample_inputs.items()])
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# Compile model on a specific device
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compile_job = hub.submit_compile_job(
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model=pt_model,
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device=device,
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input_specs=torch_model.get_input_spec(),
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)
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# Get target model to run on-device
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target_model = compile_job.get_target_model()
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```
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