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StereoNet

Depth Estimation
PyTorch
android
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v0.63.0

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See https://github.com/qualcomm/ai-hub-models/releases/v0.63.0 for changelog.

Files changed (2) hide show
  1. README.md +34 -33
  2. release_assets.json +7 -7
README.md CHANGED
@@ -14,7 +14,7 @@ pipeline_tag: depth-estimation
14
  StereoNet is an end-to-end deep architecture for real-time stereo matching that produces high-quality, edge-preserved disparity maps from a rectified stereo image pair.
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  This is based on the implementation of StereoNet found [here](https://github.com/andrewlstewart/StereoNet_PyTorch).
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/v0.62.2/src/qai_hub_models/models/stereonet) 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 |
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  |---|---|---|---|---|
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- | 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/stereonet/releases/v0.62.2/stereonet-onnx-float.zip)
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- | QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/stereonet/releases/v0.62.2/stereonet-qnn_dlc-float.zip)
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- | TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/stereonet/releases/v0.62.2/stereonet-tflite-float.zip)
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  For more device-specific assets and performance metrics, visit **[StereoNet on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/stereonet)**.
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  ### Option 2: Export with Custom Configurations
38
 
39
- Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.62.2/src/qai_hub_models/models/stereonet) 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 [StereoNet on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.62.2/src/qai_hub_models/models/stereonet) for usage instructions.
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  ## Model Details
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@@ -58,35 +58,36 @@ See our repository for [StereoNet on GitHub](https://github.com/qualcomm/ai-hub-
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  ## Performance Summary
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  | Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
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  |---|---|---|---|---|---|---
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- | StereoNet | ONNX | float | Snapdragon® X2 Elite | 207.049 ms | 5 - 5 MB | NPU
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- | StereoNet | ONNX | float | Snapdragon® X Elite | 378.219 ms | 44 - 44 MB | NPU
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- | StereoNet | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 296.95 ms | 6 - 4395 MB | NPU
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- | StereoNet | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 495.508 ms | 3 - 9 MB | NPU
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- | StereoNet | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 429.401 ms | 3 - 52 MB | NPU
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- | StereoNet | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 464.01 ms | 3 - 9 MB | NPU
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- | StereoNet | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 378.219 ms | 44 - 44 MB | NPU
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- | StereoNet | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 250.438 ms | 3 - 3236 MB | NPU
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- | StereoNet | ONNX | float | Snapdragon® 8 Elite Mobile | 250.438 ms | 3 - 3236 MB | NPU
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- | StereoNet | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 199.162 ms | 3 - 3303 MB | NPU
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- | StereoNet | QNN_DLC | float | Snapdragon® X2 Elite | 193.328 ms | 3 - 3 MB | NPU
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- | StereoNet | QNN_DLC | float | Snapdragon® X Elite | 365.661 ms | 3 - 3 MB | NPU
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- | StereoNet | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 285.047 ms | 3 - 4451 MB | NPU
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- | StereoNet | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 482.907 ms | 3 - 10 MB | NPU
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- | StereoNet | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 473.14 ms | 3 - 8 MB | NPU
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- | StereoNet | QNN_DLC | float | Qualcomm® SA8775P | 461.966 ms | 1 - 3260 MB | NPU
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  | StereoNet | QNN_DLC | float | Qualcomm® SA8650P | 461.966 ms | 1 - 3260 MB | NPU
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  | StereoNet | QNN_DLC | float | Qualcomm® SA8255P | 461.966 ms | 1 - 3260 MB | NPU
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- | StereoNet | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 450.574 ms | 3 - 9 MB | NPU
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- | StereoNet | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 365.661 ms | 3 - 3 MB | NPU
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- | StereoNet | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 237.798 ms | 0 - 3238 MB | NPU
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- | StereoNet | QNN_DLC | float | Qualcomm® SA7255P | 1293.634 ms | 1 - 3259 MB | NPU
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- | StereoNet | QNN_DLC | float | Qualcomm® SA8295P | 516.242 ms | 0 - 3366 MB | NPU
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- | StereoNet | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 237.798 ms | 0 - 3238 MB | NPU
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- | StereoNet | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 187.254 ms | 3 - 3301 MB | NPU
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- | StereoNet | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 551.746 ms | 74 - 78 MB | NPU
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- | StereoNet | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 276.155 ms | 73 - 3773 MB | NPU
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- | StereoNet | TFLITE | float | Snapdragon® 8 Elite Mobile | 276.155 ms | 73 - 3773 MB | NPU
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- | StereoNet | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 288.841 ms | 74 - 3864 MB | NPU
 
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91
  ## License
92
  * The license for the original implementation of StereoNet can be found
 
14
  StereoNet is an end-to-end deep architecture for real-time stereo matching that produces high-quality, edge-preserved disparity maps from a rectified stereo image pair.
15
 
16
  This is based on the implementation of StereoNet found [here](https://github.com/andrewlstewart/StereoNet_PyTorch).
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/v0.63.0/src/qai_hub_models/models/stereonet) 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 2.50, ONNX Runtime 1.27.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/stereonet/releases/v0.63.0/stereonet-onnx-float.zip)
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+ | QNN_DLC | float | Universal | QAIRT 2.50 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/stereonet/releases/v0.63.0/stereonet-qnn_dlc-float.zip)
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+ | TFLITE | float | Universal | QAIRT 2.50 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/stereonet/releases/v0.63.0/stereonet-tflite-float.zip)
33
 
34
  For more device-specific assets and performance metrics, visit **[StereoNet on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/stereonet)**.
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/v0.63.0/src/qai_hub_models/models/stereonet) 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 [StereoNet on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.63.0/src/qai_hub_models/models/stereonet) for usage instructions.
47
 
48
  ## Model Details
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58
  ## Performance Summary
59
  | Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
60
  |---|---|---|---|---|---|---
61
+ | StereoNet | ONNX | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 203.063 ms | 5 - 2837 MB | NPU
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+ | StereoNet | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 243.626 ms | 3 - 2784 MB | NPU
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+ | StereoNet | ONNX | float | Snapdragon® X2 Elite | 208.952 ms | 3 - 3 MB | NPU
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+ | StereoNet | ONNX | float | Snapdragon® X Elite | 363.091 ms | 40 - 40 MB | NPU
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+ | StereoNet | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 474.054 ms | 3 - 10 MB | NPU
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+ | StereoNet | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 430.153 ms | 0 - 49 MB | NPU
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+ | StereoNet | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 443.394 ms | 3 - 9 MB | NPU
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+ | StereoNet | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 363.091 ms | 40 - 40 MB | NPU
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+ | StereoNet | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 243.626 ms | 3 - 2784 MB | NPU
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+ | StereoNet | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 186.254 ms | 3 - 2846 MB | NPU
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+ | StereoNet | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 230.332 ms | 0 - 2783 MB | NPU
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+ | StereoNet | QNN_DLC | float | Snapdragon® X2 Elite | 185.521 ms | 3 - 3 MB | NPU
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+ | StereoNet | QNN_DLC | float | Snapdragon® X Elite | 346.697 ms | 3 - 3 MB | NPU
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+ | StereoNet | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 266.448 ms | 3 - 3861 MB | NPU
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+ | StereoNet | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 457.901 ms | 3 - 10 MB | NPU
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+ | StereoNet | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 434.369 ms | 3 - 8 MB | NPU
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  | StereoNet | QNN_DLC | float | Qualcomm® SA8650P | 461.966 ms | 1 - 3260 MB | NPU
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  | StereoNet | QNN_DLC | float | Qualcomm® SA8255P | 461.966 ms | 1 - 3260 MB | NPU
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+ | StereoNet | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 424.793 ms | 5 - 11 MB | NPU
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+ | StereoNet | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 346.697 ms | 3 - 3 MB | NPU
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+ | StereoNet | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 230.332 ms | 0 - 2783 MB | NPU
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+ | StereoNet | QNN_DLC | float | Qualcomm® SA8295P | 506.741 ms | 0 - 2944 MB | NPU
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+ | StereoNet | TFLITE | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 267.481 ms | 25 - 3259 MB | NPU
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+ | StereoNet | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 282.473 ms | 73 - 3218 MB | NPU
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+ | StereoNet | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 350.839 ms | 72 - 4241 MB | NPU
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+ | StereoNet | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 576.12 ms | 74 - 199 MB | NPU
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+ | StereoNet | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 576.624 ms | 74 - 77 MB | NPU
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+ | StereoNet | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 557.185 ms | 72 - 196 MB | NPU
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+ | StereoNet | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 282.473 ms | 73 - 3218 MB | NPU
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+ | StereoNet | TFLITE | float | Qualcomm® SA8295P | 615.918 ms | 74 - 3210 MB | NPU
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92
  ## License
93
  * The license for the original implementation of StereoNet can be found
release_assets.json CHANGED
@@ -1,26 +1,26 @@
1
  {
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- "version": "0.62.2",
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  "precisions": {
4
  "float": {
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  "universal_assets": {
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  "onnx": {
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  "tool_versions": {
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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/stereonet/releases/v0.62.2/stereonet-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/stereonet/releases/v0.62.2/stereonet-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/stereonet/releases/v0.62.2/stereonet-tflite-float.zip"
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  }
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  }
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  }
 
1
  {
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+ "version": "0.63.0",
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  "precisions": {
4
  "float": {
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  "universal_assets": {
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  "onnx": {
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  "tool_versions": {
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+ "qairt": "2.50.0.260828221209",
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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/stereonet/releases/v0.63.0/stereonet-onnx-float.zip"
12
  },
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  "qnn_dlc": {
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  "tool_versions": {
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+ "qairt": "2.50.0.260828221209"
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  },
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+ "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/stereonet/releases/v0.63.0/stereonet-qnn_dlc-float.zip"
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  },
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  "tflite": {
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  "tool_versions": {
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+ "qairt": "2.50.0.260828221209"
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  },
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+ "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/stereonet/releases/v0.63.0/stereonet-tflite-float.zip"
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  }
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  }
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  }