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LiteHRNet

Keypoint Detection
PyTorch
TF Lite
ONNX
android
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@@ -33,19 +33,20 @@ 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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  |---|---|---|---|---|---|---|---|---|
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- | LiteHRNet | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 7.964 ms | 0 - 2 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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- | LiteHRNet | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 7.174 ms | 0 - 160 MB | FP16 | NPU | [LiteHRNet.onnx](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.onnx) |
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- | LiteHRNet | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 4.917 ms | 0 - 97 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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- | LiteHRNet | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 4.418 ms | 1 - 109 MB | FP16 | NPU | [LiteHRNet.onnx](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.onnx) |
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- | LiteHRNet | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 5.295 ms | 0 - 68 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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- | LiteHRNet | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 4.829 ms | 1 - 79 MB | FP16 | NPU | [LiteHRNet.onnx](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.onnx) |
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- | LiteHRNet | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 7.939 ms | 0 - 151 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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- | LiteHRNet | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 7.958 ms | 0 - 2 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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- | LiteHRNet | SA8775 (Proxy) | SA8775P Proxy | TFLITE | 7.942 ms | 0 - 3 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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- | LiteHRNet | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 7.921 ms | 0 - 2 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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- | LiteHRNet | SA8295P ADP | SA8295P | TFLITE | 9.944 ms | 0 - 61 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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- | LiteHRNet | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 8.569 ms | 0 - 85 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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- | LiteHRNet | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 8.124 ms | 6 - 6 MB | FP16 | NPU | [LiteHRNet.onnx](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.onnx) |
 
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@@ -110,8 +111,8 @@ Profiling Results
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  LiteHRNet
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  Device : Samsung Galaxy S23 (13)
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  Runtime : TFLITE
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- Estimated inference time (ms) : 8.0
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- Estimated peak memory usage (MB): [0, 2]
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  Total # Ops : 1235
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  Compute Unit(s) : NPU (1233 ops) CPU (2 ops)
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  ```
@@ -132,13 +133,29 @@ in memory using the `jit.trace` and then call the `submit_compile_job` API.
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  import torch
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  import qai_hub as hub
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- from qai_hub_models.models.litehrnet 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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  |---|---|---|---|---|---|---|---|---|
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+ | LiteHRNet | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 7.877 ms | 0 - 15 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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+ | LiteHRNet | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 7.308 ms | 0 - 6 MB | FP16 | NPU | [LiteHRNet.onnx](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.onnx) |
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+ | LiteHRNet | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 4.774 ms | 0 - 38 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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+ | LiteHRNet | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 4.737 ms | 1 - 111 MB | FP16 | NPU | [LiteHRNet.onnx](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.onnx) |
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+ | LiteHRNet | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 4.296 ms | 0 - 31 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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+ | LiteHRNet | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 4.942 ms | 1 - 79 MB | FP16 | NPU | [LiteHRNet.onnx](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.onnx) |
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+ | LiteHRNet | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 7.832 ms | 0 - 18 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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+ | LiteHRNet | SA7255P ADP | SA7255P | TFLITE | 28.622 ms | 0 - 30 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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+ | LiteHRNet | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 7.875 ms | 0 - 15 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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+ | LiteHRNet | SA8295P ADP | SA8295P | TFLITE | 9.858 ms | 0 - 26 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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+ | LiteHRNet | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 7.892 ms | 0 - 14 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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+ | LiteHRNet | SA8775P ADP | SA8775P | TFLITE | 10.712 ms | 0 - 30 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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+ | LiteHRNet | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 8.527 ms | 0 - 32 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
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+ | LiteHRNet | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 8.163 ms | 4 - 4 MB | FP16 | NPU | [LiteHRNet.onnx](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.onnx) |
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  LiteHRNet
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  Device : Samsung Galaxy S23 (13)
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  Runtime : TFLITE
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+ Estimated inference time (ms) : 7.9
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+ Estimated peak memory usage (MB): [0, 15]
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  Total # Ops : 1235
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  Compute Unit(s) : NPU (1233 ops) CPU (2 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.litehrnet 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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+
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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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+
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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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+
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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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