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FCN-ResNet50

Image Segmentation
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android
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@@ -35,39 +35,39 @@ 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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- | FCN-ResNet50 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 48.565 ms | 0 - 18 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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- | FCN-ResNet50 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 48.547 ms | 3 - 20 MB | FP16 | NPU | [FCN-ResNet50.so](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.so) |
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- | FCN-ResNet50 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 43.543 ms | 1 - 196 MB | FP16 | NPU | [FCN-ResNet50.onnx](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.onnx) |
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- | FCN-ResNet50 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 36.093 ms | 0 - 92 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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- | FCN-ResNet50 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 35.619 ms | 3 - 94 MB | FP16 | NPU | [FCN-ResNet50.so](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.so) |
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- | FCN-ResNet50 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 34.185 ms | 3 - 116 MB | FP16 | NPU | [FCN-ResNet50.onnx](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.onnx) |
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- | FCN-ResNet50 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 34.929 ms | 0 - 89 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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- | FCN-ResNet50 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 35.05 ms | 3 - 92 MB | FP16 | NPU | Use Export Script |
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- | FCN-ResNet50 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 32.154 ms | 3 - 108 MB | FP16 | NPU | [FCN-ResNet50.onnx](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.onnx) |
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- | FCN-ResNet50 | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 48.004 ms | 0 - 18 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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- | FCN-ResNet50 | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 43.596 ms | 3 - 7 MB | FP16 | NPU | Use Export Script |
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- | FCN-ResNet50 | SA7255P ADP | SA7255P | TFLITE | 2068.636 ms | 0 - 87 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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- | FCN-ResNet50 | SA7255P ADP | SA7255P | QNN | 2061.011 ms | 3 - 12 MB | FP16 | NPU | Use Export Script |
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- | FCN-ResNet50 | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 48.249 ms | 0 - 18 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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- | FCN-ResNet50 | SA8255 (Proxy) | SA8255P Proxy | QNN | 43.602 ms | 3 - 5 MB | FP16 | NPU | Use Export Script |
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- | FCN-ResNet50 | SA8295P ADP | SA8295P | TFLITE | 84.786 ms | 0 - 40 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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- | FCN-ResNet50 | SA8295P ADP | SA8295P | QNN | 81.193 ms | 0 - 15 MB | FP16 | NPU | Use Export Script |
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- | FCN-ResNet50 | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 48.485 ms | 0 - 18 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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- | FCN-ResNet50 | SA8650 (Proxy) | SA8650P Proxy | QNN | 44.428 ms | 3 - 5 MB | FP16 | NPU | Use Export Script |
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- | FCN-ResNet50 | SA8775P ADP | SA8775P | TFLITE | 95.26 ms | 0 - 86 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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- | FCN-ResNet50 | SA8775P ADP | SA8775P | QNN | 89.481 ms | 2 - 12 MB | FP16 | NPU | Use Export Script |
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- | FCN-ResNet50 | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 75.648 ms | 0 - 43 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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- | FCN-ResNet50 | QCS8450 (Proxy) | QCS8450 Proxy | QNN | 75.073 ms | 3 - 44 MB | FP16 | NPU | Use Export Script |
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- | FCN-ResNet50 | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 44.203 ms | 3 - 3 MB | FP16 | NPU | Use Export Script |
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- | FCN-ResNet50 | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 45.16 ms | 65 - 65 MB | FP16 | NPU | [FCN-ResNet50.onnx](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.onnx) |
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  ## Installation
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- This model can be installed as a Python package via pip.
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  ```bash
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  pip install qai-hub-models
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  ```
@@ -123,8 +123,8 @@ Profiling Results
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  FCN-ResNet50
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  Device : Samsung Galaxy S23 (13)
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  Runtime : TFLITE
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- Estimated inference time (ms) : 48.6
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- Estimated peak memory usage (MB): [0, 18]
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  Total # Ops : 88
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  Compute Unit(s) : NPU (88 ops)
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  ```
@@ -151,7 +151,7 @@ from qai_hub_models.models.fcn_resnet50 import 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()
@@ -243,7 +243,8 @@ Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/)
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  ## License
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- * The license for the original implementation of FCN-ResNet50 can be found [here](https://github.com/pytorch/vision/blob/main/LICENSE).
 
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  * The license for the compiled assets for on-device deployment can be found [here](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf)
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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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+ | FCN-ResNet50 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 48.69 ms | 0 - 20 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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+ | FCN-ResNet50 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 48.641 ms | 3 - 22 MB | FP16 | NPU | [FCN-ResNet50.so](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.so) |
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+ | FCN-ResNet50 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 43.701 ms | 1 - 154 MB | FP16 | NPU | [FCN-ResNet50.onnx](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.onnx) |
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+ | FCN-ResNet50 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 36.054 ms | 0 - 93 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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+ | FCN-ResNet50 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 35.793 ms | 3 - 93 MB | FP16 | NPU | [FCN-ResNet50.so](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.so) |
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+ | FCN-ResNet50 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 34.257 ms | 3 - 118 MB | FP16 | NPU | [FCN-ResNet50.onnx](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.onnx) |
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+ | FCN-ResNet50 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 35.074 ms | 0 - 90 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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+ | FCN-ResNet50 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 35.037 ms | 3 - 92 MB | FP16 | NPU | Use Export Script |
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+ | FCN-ResNet50 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 27.844 ms | 3 - 109 MB | FP16 | NPU | [FCN-ResNet50.onnx](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.onnx) |
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+ | FCN-ResNet50 | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 48.588 ms | 0 - 17 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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+ | FCN-ResNet50 | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 43.966 ms | 3 - 5 MB | FP16 | NPU | Use Export Script |
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+ | FCN-ResNet50 | SA7255P ADP | SA7255P | TFLITE | 2068.807 ms | 0 - 86 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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+ | FCN-ResNet50 | SA7255P ADP | SA7255P | QNN | 2060.91 ms | 1 - 12 MB | FP16 | NPU | Use Export Script |
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+ | FCN-ResNet50 | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 48.441 ms | 0 - 19 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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+ | FCN-ResNet50 | SA8255 (Proxy) | SA8255P Proxy | QNN | 44.634 ms | 3 - 6 MB | FP16 | NPU | Use Export Script |
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+ | FCN-ResNet50 | SA8295P ADP | SA8295P | TFLITE | 84.791 ms | 0 - 40 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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+ | FCN-ResNet50 | SA8295P ADP | SA8295P | QNN | 81.173 ms | 0 - 14 MB | FP16 | NPU | Use Export Script |
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+ | FCN-ResNet50 | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 48.899 ms | 0 - 19 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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+ | FCN-ResNet50 | SA8650 (Proxy) | SA8650P Proxy | QNN | 44.315 ms | 3 - 6 MB | FP16 | NPU | Use Export Script |
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+ | FCN-ResNet50 | SA8775P ADP | SA8775P | TFLITE | 95.302 ms | 0 - 87 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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+ | FCN-ResNet50 | SA8775P ADP | SA8775P | QNN | 89.464 ms | 2 - 12 MB | FP16 | NPU | Use Export Script |
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+ | FCN-ResNet50 | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 75.644 ms | 0 - 43 MB | FP16 | NPU | [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) |
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+ | FCN-ResNet50 | QCS8450 (Proxy) | QCS8450 Proxy | QNN | 75.737 ms | 3 - 50 MB | FP16 | NPU | Use Export Script |
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+ | FCN-ResNet50 | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 44.149 ms | 3 - 3 MB | FP16 | NPU | Use Export Script |
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+ | FCN-ResNet50 | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 45.19 ms | 64 - 64 MB | FP16 | NPU | [FCN-ResNet50.onnx](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.onnx) |
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  ## Installation
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+ Install the package via pip:
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  ```bash
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  pip install qai-hub-models
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  ```
 
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  FCN-ResNet50
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  Device : Samsung Galaxy S23 (13)
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  Runtime : TFLITE
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+ Estimated inference time (ms) : 48.7
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+ Estimated peak memory usage (MB): [0, 20]
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  Total # Ops : 88
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  Compute Unit(s) : NPU (88 ops)
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  ```
 
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  torch_model = Model.from_pretrained()
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  # Device
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+ device = hub.Device("Samsung Galaxy S24")
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  # Trace model
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  input_shape = torch_model.get_input_spec()
 
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  ## License
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+ * The license for the original implementation of FCN-ResNet50 can be found
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+ [here](https://github.com/pytorch/vision/blob/main/LICENSE).
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  * The license for the compiled assets for on-device deployment can be found [here](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf)
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