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PointNet

Image Segmentation
PyTorch
bu_auto
android
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v0.61.0

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See https://github.com/qualcomm/ai-hub-models/releases/v0.61.0 for changelog.

Files changed (2) hide show
  1. README.md +42 -42
  2. release_assets.json +4 -4
README.md CHANGED
@@ -1,6 +1,6 @@
1
  ---
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  library_name: pytorch
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- license: other
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  tags:
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  - bu_auto
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  - android
@@ -14,7 +14,7 @@ pipeline_tag: image-segmentation
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  PointNet is a pioneering neural network architecture designed to directly consume unordered point cloud data for tasks such as classification and segmentation. It learns spatial features from raw 3D points without requiring voxelization or image projections.
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- 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/v0.60.0/src/qai_hub_models/models/pointnet) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
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  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.
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@@ -27,23 +27,23 @@ Below are pre-exported model assets ready for deployment.
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  | Runtime | Precision | Chipset | SDK Versions | Download |
29
  |---|---|---|---|---|
30
- | ONNX | float | Universal | QAIRT 2.45, ONNX Runtime 1.27.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pointnet/releases/v0.60.0/pointnet-onnx-float.zip)
31
- | QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pointnet/releases/v0.60.0/pointnet-qnn_dlc-float.zip)
32
- | TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pointnet/releases/v0.60.0/pointnet-tflite-float.zip)
33
 
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  For more device-specific assets and performance metrics, visit **[PointNet on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/pointnet)**.
35
 
36
 
37
  ### Option 2: Export with Custom Configurations
38
 
39
- Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.60.0/src/qai_hub_models/models/pointnet) Python library to compile and export the model with your own:
40
  - Custom weights (e.g., fine-tuned checkpoints)
41
  - Custom input shapes
42
  - Target device and runtime configurations
43
 
44
  This option is ideal if you need to customize the model beyond the default configuration provided here.
45
 
46
- See our repository for [PointNet on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.60.0/src/qai_hub_models/models/pointnet) for usage instructions.
47
 
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  ## Model Details
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@@ -57,51 +57,51 @@ See our repository for [PointNet on GitHub](https://github.com/qualcomm/ai-hub-m
57
  ## Performance Summary
58
  | Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
59
  |---|---|---|---|---|---|---
60
- | PointNet | ONNX | float | Snapdragon® X2 Elite | 0.303 ms | 1 - 1 MB | NPU
61
  | PointNet | ONNX | float | Snapdragon® X Elite | 0.661 ms | 7 - 7 MB | NPU
62
- | PointNet | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 0.403 ms | 0 - 42 MB | NPU
63
- | PointNet | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 0.865 ms | 0 - 47 MB | NPU
64
- | PointNet | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 0.737 ms | 0 - 3 MB | NPU
65
- | PointNet | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 0.644 ms | 0 - 9 MB | NPU
66
- | PointNet | ONNX | float | Qualcomm® QCS8450 | 0.865 ms | 0 - 47 MB | NPU
67
- | PointNet | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 0.806 ms | 0 - 3 MB | NPU
68
  | PointNet | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 0.661 ms | 7 - 7 MB | NPU
69
  | PointNet | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 0.42 ms | 0 - 28 MB | NPU
70
  | PointNet | ONNX | float | Snapdragon® 8 Elite Mobile | 0.42 ms | 0 - 28 MB | NPU
71
- | PointNet | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.325 ms | 0 - 23 MB | NPU
72
- | PointNet | QNN_DLC | float | Snapdragon® X2 Elite | 0.408 ms | 0 - 0 MB | NPU
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- | PointNet | QNN_DLC | float | Snapdragon® X Elite | 0.771 ms | 1 - 1 MB | NPU
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- | PointNet | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 0.41 ms | 0 - 42 MB | NPU
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- | PointNet | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 0.864 ms | 0 - 47 MB | NPU
76
- | PointNet | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 0.738 ms | 0 - 2 MB | NPU
77
- | PointNet | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 1.866 ms | 0 - 24 MB | NPU
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- | PointNet | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 0.659 ms | 0 - 3 MB | NPU
79
  | PointNet | QNN_DLC | float | Qualcomm® SA8775P | 0.916 ms | 0 - 25 MB | NPU
80
  | PointNet | QNN_DLC | float | Qualcomm® SA8650P | 0.916 ms | 0 - 25 MB | NPU
81
  | PointNet | QNN_DLC | float | Qualcomm® SA8255P | 0.916 ms | 0 - 25 MB | NPU
82
- | PointNet | QNN_DLC | float | Qualcomm® QCS8450 | 0.864 ms | 0 - 47 MB | NPU
83
- | PointNet | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 0.815 ms | 2 - 4 MB | NPU
84
- | PointNet | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 0.771 ms | 1 - 1 MB | NPU
85
- | PointNet | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 0.481 ms | 0 - 23 MB | NPU
86
- | PointNet | QNN_DLC | float | Qualcomm® SA7255P | 1.866 ms | 0 - 24 MB | NPU
87
- | PointNet | QNN_DLC | float | Qualcomm® SA8295P | 1.107 ms | 0 - 21 MB | NPU
88
- | PointNet | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 0.481 ms | 0 - 23 MB | NPU
89
- | PointNet | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.325 ms | 0 - 24 MB | NPU
90
- | PointNet | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 0.41 ms | 0 - 41 MB | NPU
91
- | PointNet | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 0.861 ms | 0 - 47 MB | NPU
92
- | PointNet | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 0.743 ms | 0 - 9 MB | NPU
93
- | PointNet | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 1.871 ms | 0 - 25 MB | NPU
94
- | PointNet | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 0.65 ms | 0 - 1 MB | NPU
95
- | PointNet | TFLITE | float | Qualcomm® SA8775P | 0.921 ms | 0 - 25 MB | NPU
96
- | PointNet | TFLITE | float | Qualcomm® SA8650P | 0.921 ms | 0 - 25 MB | NPU
97
- | PointNet | TFLITE | float | Qualcomm® SA8255P | 0.921 ms | 0 - 25 MB | NPU
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- | PointNet | TFLITE | float | Qualcomm® QCS8450 | 0.861 ms | 0 - 47 MB | NPU
99
- | PointNet | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 0.825 ms | 0 - 8 MB | NPU
100
  | PointNet | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 0.483 ms | 0 - 28 MB | NPU
101
- | PointNet | TFLITE | float | Qualcomm® SA7255P | 1.871 ms | 0 - 25 MB | NPU
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  | PointNet | TFLITE | float | Qualcomm® SA8295P | 1.138 ms | 0 - 22 MB | NPU
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  | PointNet | TFLITE | float | Snapdragon® 8 Elite Mobile | 0.483 ms | 0 - 28 MB | NPU
104
- | PointNet | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.32 ms | 0 - 25 MB | NPU
105
 
106
  ## License
107
  * The license for the original implementation of PointNet can be found
 
1
  ---
2
  library_name: pytorch
3
+ license: apache-2.0
4
  tags:
5
  - bu_auto
6
  - android
 
14
 
15
  PointNet is a pioneering neural network architecture designed to directly consume unordered point cloud data for tasks such as classification and segmentation. It learns spatial features from raw 3D points without requiring voxelization or image projections.
16
 
17
+ 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/v0.61.0/src/qai_hub_models/models/pointnet) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
18
 
19
  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.
20
 
 
27
 
28
  | Runtime | Precision | Chipset | SDK Versions | Download |
29
  |---|---|---|---|---|
30
+ | ONNX | float | Universal | QAIRT 2.45, ONNX Runtime 1.27.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pointnet/releases/v0.61.0/pointnet-onnx-float.zip)
31
+ | QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pointnet/releases/v0.61.0/pointnet-qnn_dlc-float.zip)
32
+ | TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pointnet/releases/v0.61.0/pointnet-tflite-float.zip)
33
 
34
  For more device-specific assets and performance metrics, visit **[PointNet on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/pointnet)**.
35
 
36
 
37
  ### Option 2: Export with Custom Configurations
38
 
39
+ Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.61.0/src/qai_hub_models/models/pointnet) Python library to compile and export the model with your own:
40
  - Custom weights (e.g., fine-tuned checkpoints)
41
  - Custom input shapes
42
  - Target device and runtime configurations
43
 
44
  This option is ideal if you need to customize the model beyond the default configuration provided here.
45
 
46
+ See our repository for [PointNet on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.61.0/src/qai_hub_models/models/pointnet) for usage instructions.
47
 
48
  ## Model Details
49
 
 
57
  ## Performance Summary
58
  | Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
59
  |---|---|---|---|---|---|---
60
+ | PointNet | ONNX | float | Snapdragon® X2 Elite | 0.304 ms | 1 - 1 MB | NPU
61
  | PointNet | ONNX | float | Snapdragon® X Elite | 0.661 ms | 7 - 7 MB | NPU
62
+ | PointNet | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 0.406 ms | 0 - 42 MB | NPU
63
+ | PointNet | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 0.869 ms | 0 - 46 MB | NPU
64
+ | PointNet | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 0.74 ms | 0 - 3 MB | NPU
65
+ | PointNet | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 0.651 ms | 0 - 21 MB | NPU
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+ | PointNet | ONNX | float | Qualcomm® QCS8450 | 0.869 ms | 0 - 46 MB | NPU
67
+ | PointNet | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 0.807 ms | 0 - 3 MB | NPU
68
  | PointNet | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 0.661 ms | 7 - 7 MB | NPU
69
  | PointNet | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 0.42 ms | 0 - 28 MB | NPU
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  | PointNet | ONNX | float | Snapdragon® 8 Elite Mobile | 0.42 ms | 0 - 28 MB | NPU
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+ | PointNet | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.324 ms | 0 - 23 MB | NPU
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+ | PointNet | QNN_DLC | float | Snapdragon® X2 Elite | 0.409 ms | 1 - 1 MB | NPU
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+ | PointNet | QNN_DLC | float | Snapdragon® X Elite | 0.782 ms | 1 - 1 MB | NPU
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+ | PointNet | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 0.417 ms | 0 - 42 MB | NPU
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+ | PointNet | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 0.866 ms | 0 - 47 MB | NPU
76
+ | PointNet | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 0.731 ms | 0 - 2 MB | NPU
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+ | PointNet | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 1.847 ms | 0 - 24 MB | NPU
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+ | PointNet | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 0.666 ms | 0 - 2 MB | NPU
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  | PointNet | QNN_DLC | float | Qualcomm® SA8775P | 0.916 ms | 0 - 25 MB | NPU
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  | PointNet | QNN_DLC | float | Qualcomm® SA8650P | 0.916 ms | 0 - 25 MB | NPU
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  | PointNet | QNN_DLC | float | Qualcomm® SA8255P | 0.916 ms | 0 - 25 MB | NPU
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+ | PointNet | QNN_DLC | float | Qualcomm® QCS8450 | 0.866 ms | 0 - 47 MB | NPU
83
+ | PointNet | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 0.814 ms | 0 - 2 MB | NPU
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+ | PointNet | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 0.782 ms | 1 - 1 MB | NPU
85
+ | PointNet | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 0.48 ms | 0 - 27 MB | NPU
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+ | PointNet | QNN_DLC | float | Qualcomm® SA7255P | 1.847 ms | 0 - 24 MB | NPU
87
+ | PointNet | QNN_DLC | float | Qualcomm® SA8295P | 1.114 ms | 0 - 21 MB | NPU
88
+ | PointNet | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 0.48 ms | 0 - 27 MB | NPU
89
+ | PointNet | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.32 ms | 0 - 24 MB | NPU
90
+ | PointNet | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 0.411 ms | 0 - 41 MB | NPU
91
+ | PointNet | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 0.859 ms | 0 - 47 MB | NPU
92
+ | PointNet | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 0.754 ms | 0 - 9 MB | NPU
93
+ | PointNet | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 1.881 ms | 0 - 24 MB | NPU
94
+ | PointNet | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 0.664 ms | 0 - 17 MB | NPU
95
+ | PointNet | TFLITE | float | Qualcomm® SA8775P | 0.92 ms | 0 - 25 MB | NPU
96
+ | PointNet | TFLITE | float | Qualcomm® SA8650P | 0.92 ms | 0 - 25 MB | NPU
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+ | PointNet | TFLITE | float | Qualcomm® SA8255P | 0.92 ms | 0 - 25 MB | NPU
98
+ | PointNet | TFLITE | float | Qualcomm® QCS8450 | 0.859 ms | 0 - 47 MB | NPU
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+ | PointNet | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 0.812 ms | 0 - 8 MB | NPU
100
  | PointNet | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 0.483 ms | 0 - 28 MB | NPU
101
+ | PointNet | TFLITE | float | Qualcomm® SA7255P | 1.881 ms | 0 - 24 MB | NPU
102
  | PointNet | TFLITE | float | Qualcomm® SA8295P | 1.138 ms | 0 - 22 MB | NPU
103
  | PointNet | TFLITE | float | Snapdragon® 8 Elite Mobile | 0.483 ms | 0 - 28 MB | NPU
104
+ | PointNet | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.321 ms | 0 - 24 MB | NPU
105
 
106
  ## License
107
  * The license for the original implementation of PointNet can be found
release_assets.json CHANGED
@@ -1,5 +1,5 @@
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  {
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- "version": "0.60.0",
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  "precisions": {
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  "float": {
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  "universal_assets": {
@@ -8,19 +8,19 @@
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  "qairt": "2.45.0.260326154327",
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  "onnx_runtime": "1.27.1"
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  },
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- "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pointnet/releases/v0.60.0/pointnet-onnx-float.zip"
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  },
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  "qnn_dlc": {
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  "tool_versions": {
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  "qairt": "2.45.0.260326154327"
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  },
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- "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pointnet/releases/v0.60.0/pointnet-qnn_dlc-float.zip"
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  },
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  "tflite": {
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  "tool_versions": {
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  "qairt": "2.45.0.260326154327"
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  },
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- "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pointnet/releases/v0.60.0/pointnet-tflite-float.zip"
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  }
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  }
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  }
 
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  {
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+ "version": "0.61.0",
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  "precisions": {
4
  "float": {
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  "universal_assets": {
 
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  "qairt": "2.45.0.260326154327",
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  "onnx_runtime": "1.27.1"
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  },
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+ "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pointnet/releases/v0.61.0/pointnet-onnx-float.zip"
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  },
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  "qnn_dlc": {
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  "tool_versions": {
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  "qairt": "2.45.0.260326154327"
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  },
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+ "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pointnet/releases/v0.61.0/pointnet-qnn_dlc-float.zip"
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  },
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  "tflite": {
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  "tool_versions": {
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  "qairt": "2.45.0.260326154327"
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  },
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+ "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pointnet/releases/v0.61.0/pointnet-tflite-float.zip"
24
  }
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  }
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  }