Object Detection
PyTorch
foundation
android
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See https://github.com/qualcomm/ai-hub-models/releases/v0.65.0 for changelog.

Files changed (2) hide show
  1. README.md +6 -36
  2. release_assets.json +4 -21
README.md CHANGED
@@ -15,7 +15,7 @@ pipeline_tag: object-detection
15
  OWL-ViT (Open-World Localization with Vision Transformers) is an open-vocabulary object detector that uses a CLIP-based ViT-B/32 backbone. Given an image and one or more free-form text queries, the model predicts bounding boxes and confidence scores for each query.
16
 
17
  This is based on the implementation of OWL-ViT found [here](https://github.com/google-research/scenic/tree/main/scenic/projects/owl_vit).
18
- 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/v0.64.0/src/qai_hub_models/models/owl_vit) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
19
 
20
  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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@@ -28,25 +28,23 @@ Below are pre-exported model assets ready for deployment.
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  | Runtime | Precision | Chipset | SDK Versions | Download |
30
  |---|---|---|---|---|
31
- | ONNX | float | Universal | QAIRT 2.50, ONNX Runtime 1.30.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/owl_vit/releases/v0.64.0/owl_vit-onnx-float.zip)
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- | ONNX | w8a16 | Universal | QAIRT 2.50, ONNX Runtime 1.27.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/owl_vit/releases/v0.64.0/owl_vit-onnx-w8a16.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/owl_vit/releases/v0.64.0/owl_vit-qnn_dlc-float.zip)
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- | QNN_DLC | w8a16 | Universal | QAIRT 2.50 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/owl_vit/releases/v0.64.0/owl_vit-qnn_dlc-w8a16.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/owl_vit/releases/v0.64.0/owl_vit-tflite-float.zip)
36
 
37
  For more device-specific assets and performance metrics, visit **[OWL-ViT on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/owl_vit)**.
38
 
39
 
40
  ### Option 2: Export with Custom Configurations
41
 
42
- Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.64.0/src/qai_hub_models/models/owl_vit) Python library to compile and export the model with your own:
43
  - Custom weights (e.g., fine-tuned checkpoints)
44
  - Custom input shapes
45
  - Target device and runtime configurations
46
 
47
  This option is ideal if you need to customize the model beyond the default configuration provided here.
48
 
49
- See our repository for [OWL-ViT on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.64.0/src/qai_hub_models/models/owl_vit) for usage instructions.
50
 
51
  ## Model Details
52
 
@@ -73,22 +71,6 @@ See our repository for [OWL-ViT on GitHub](https://github.com/qualcomm/ai-hub-mo
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  | OWL-ViT | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 51.137 ms | 6 - 16 MB | NPU
74
  | OWL-ViT | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 44.41 ms | 295 - 295 MB | NPU
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  | OWL-ViT | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 26.03 ms | 2 - 478 MB | NPU
76
- | OWL-ViT | ONNX | w8a16 | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 7.541 ms | 1 - 576 MB | NPU
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- | OWL-ViT | ONNX | w8a16 | Snapdragon® 8 Elite For Galaxy Mobile | 10.809 ms | 1 - 560 MB | NPU
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- | OWL-ViT | ONNX | w8a16 | Snapdragon® X2 Elite | 8.263 ms | 3 - 3 MB | NPU
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- | OWL-ViT | ONNX | w8a16 | Snapdragon® X Elite | 21.342 ms | 174 - 174 MB | NPU
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- | OWL-ViT | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 14.727 ms | 4 - 725 MB | NPU
81
- | OWL-ViT | ONNX | w8a16 | Snapdragon® 8 Gen 1 Mobile | 25.699 ms | 0 - 726 MB | NPU
82
- | OWL-ViT | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS6490 | 84.949 ms | 3 - 9 MB | NPU
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- | OWL-ViT | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-8275 | 19.894 ms | 1 - 8 MB | NPU
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- | OWL-ViT | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 20.74 ms | 0 - 192 MB | NPU
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- | OWL-ViT | ONNX | w8a16 | Qualcomm® QCS8450 | 25.699 ms | 0 - 726 MB | NPU
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- | OWL-ViT | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 20.865 ms | 0 - 7 MB | NPU
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- | OWL-ViT | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 21.342 ms | 174 - 174 MB | NPU
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- | OWL-ViT | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-6690 | 219.274 ms | 6 - 792 MB | NPU
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- | OWL-ViT | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-7790 | 34.032 ms | 6 - 594 MB | NPU
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- | OWL-ViT | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 10.809 ms | 1 - 560 MB | NPU
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- | OWL-ViT | ONNX | w8a16 | Snapdragon® 7 Gen 4 Mobile | 34.032 ms | 6 - 594 MB | NPU
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  | OWL-ViT | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 19.807 ms | 7 - 444 MB | NPU
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  | OWL-ViT | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 25.537 ms | 5 - 441 MB | NPU
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  | OWL-ViT | QNN_DLC | float | Snapdragon® X2 Elite | 19.282 ms | 7 - 7 MB | NPU
@@ -105,18 +87,6 @@ See our repository for [OWL-ViT on GitHub](https://github.com/qualcomm/ai-hub-mo
105
  | OWL-ViT | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 43.139 ms | 7 - 7 MB | NPU
106
  | OWL-ViT | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 25.537 ms | 5 - 441 MB | NPU
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  | OWL-ViT | QNN_DLC | float | Qualcomm® SA8295P | 53.656 ms | 0 - 407 MB | NPU
108
- | OWL-ViT | QNN_DLC | w8a16 | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 8.737 ms | 3 - 525 MB | NPU
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- | OWL-ViT | QNN_DLC | w8a16 | Snapdragon® 8 Elite For Galaxy Mobile | 11.535 ms | 3 - 504 MB | NPU
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- | OWL-ViT | QNN_DLC | w8a16 | Snapdragon® X2 Elite | 9.559 ms | 3 - 3 MB | NPU
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- | OWL-ViT | QNN_DLC | w8a16 | Snapdragon® X Elite | 23.241 ms | 3 - 3 MB | NPU
112
- | OWL-ViT | QNN_DLC | w8a16 | Snapdragon® 8 Gen 3 Mobile | 15.718 ms | 3 - 663 MB | NPU
113
- | OWL-ViT | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-8275 | 21.195 ms | 3 - 10 MB | NPU
114
- | OWL-ViT | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 22.447 ms | 4 - 7 MB | NPU
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- | OWL-ViT | QNN_DLC | w8a16 | Qualcomm® SA8650P | 95.803 ms | 0 - 747 MB | NPU
116
- | OWL-ViT | QNN_DLC | w8a16 | Qualcomm® SA8255P | 95.803 ms | 0 - 747 MB | NPU
117
- | OWL-ViT | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 22.099 ms | 5 - 11 MB | NPU
118
- | OWL-ViT | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 23.241 ms | 3 - 3 MB | NPU
119
- | OWL-ViT | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 11.535 ms | 3 - 504 MB | NPU
120
  | OWL-ViT | TFLITE | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 11.732 ms | 0 - 445 MB | NPU
121
  | OWL-ViT | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 17.129 ms | 0 - 446 MB | NPU
122
  | OWL-ViT | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 22.271 ms | 0 - 601 MB | NPU
 
15
  OWL-ViT (Open-World Localization with Vision Transformers) is an open-vocabulary object detector that uses a CLIP-based ViT-B/32 backbone. Given an image and one or more free-form text queries, the model predicts bounding boxes and confidence scores for each query.
16
 
17
  This is based on the implementation of OWL-ViT found [here](https://github.com/google-research/scenic/tree/main/scenic/projects/owl_vit).
18
+ 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/v0.65.0/src/qai_hub_models/models/owl_vit) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
19
 
20
  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.
21
 
 
28
 
29
  | Runtime | Precision | Chipset | SDK Versions | Download |
30
  |---|---|---|---|---|
31
+ | ONNX | float | Universal | QAIRT 2.50, ONNX Runtime 1.30.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/owl_vit/releases/v0.65.0/owl_vit-onnx-float.zip)
32
+ | QNN_DLC | float | Universal | QAIRT 2.50 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/owl_vit/releases/v0.65.0/owl_vit-qnn_dlc-float.zip)
33
+ | TFLITE | float | Universal | QAIRT 2.50 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/owl_vit/releases/v0.65.0/owl_vit-tflite-float.zip)
 
 
34
 
35
  For more device-specific assets and performance metrics, visit **[OWL-ViT on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/owl_vit)**.
36
 
37
 
38
  ### Option 2: Export with Custom Configurations
39
 
40
+ Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.65.0/src/qai_hub_models/models/owl_vit) Python library to compile and export the model with your own:
41
  - Custom weights (e.g., fine-tuned checkpoints)
42
  - Custom input shapes
43
  - Target device and runtime configurations
44
 
45
  This option is ideal if you need to customize the model beyond the default configuration provided here.
46
 
47
+ See our repository for [OWL-ViT on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.65.0/src/qai_hub_models/models/owl_vit) for usage instructions.
48
 
49
  ## Model Details
50
 
 
71
  | OWL-ViT | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 51.137 ms | 6 - 16 MB | NPU
72
  | OWL-ViT | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 44.41 ms | 295 - 295 MB | NPU
73
  | OWL-ViT | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 26.03 ms | 2 - 478 MB | NPU
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
74
  | OWL-ViT | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 19.807 ms | 7 - 444 MB | NPU
75
  | OWL-ViT | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 25.537 ms | 5 - 441 MB | NPU
76
  | OWL-ViT | QNN_DLC | float | Snapdragon® X2 Elite | 19.282 ms | 7 - 7 MB | NPU
 
87
  | OWL-ViT | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 43.139 ms | 7 - 7 MB | NPU
88
  | OWL-ViT | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 25.537 ms | 5 - 441 MB | NPU
89
  | OWL-ViT | QNN_DLC | float | Qualcomm® SA8295P | 53.656 ms | 0 - 407 MB | NPU
 
 
 
 
 
 
 
 
 
 
 
 
90
  | OWL-ViT | TFLITE | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 11.732 ms | 0 - 445 MB | NPU
91
  | OWL-ViT | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 17.129 ms | 0 - 446 MB | NPU
92
  | OWL-ViT | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 22.271 ms | 0 - 601 MB | NPU
release_assets.json CHANGED
@@ -1,5 +1,5 @@
1
  {
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- "version": "0.64.0",
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  "precisions": {
4
  "float": {
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  "universal_assets": {
@@ -8,36 +8,19 @@
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  "qairt": "2.50.0.260828221209",
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  "onnx_runtime": "1.30.0"
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  },
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- "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/owl_vit/releases/v0.64.0/owl_vit-onnx-float.zip"
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  },
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  "qnn_dlc": {
14
  "tool_versions": {
15
  "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/owl_vit/releases/v0.64.0/owl_vit-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/owl_vit/releases/v0.64.0/owl_vit-tflite-float.zip"
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- }
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- }
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- },
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- "w8a16": {
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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/owl_vit/releases/v0.64.0/owl_vit-onnx-w8a16.zip"
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- },
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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/owl_vit/releases/v0.64.0/owl_vit-qnn_dlc-w8a16.zip"
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  }
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  }
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  }
 
1
  {
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+ "version": "0.65.0",
3
  "precisions": {
4
  "float": {
5
  "universal_assets": {
 
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  "qairt": "2.50.0.260828221209",
9
  "onnx_runtime": "1.30.0"
10
  },
11
+ "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/owl_vit/releases/v0.65.0/owl_vit-onnx-float.zip"
12
  },
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  "qnn_dlc": {
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  "tool_versions": {
15
  "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/owl_vit/releases/v0.65.0/owl_vit-qnn_dlc-float.zip"
18
  },
19
  "tflite": {
20
  "tool_versions": {
21
  "qairt": "2.50.0.260828221209"
22
  },
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+ "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/owl_vit/releases/v0.65.0/owl_vit-tflite-float.zip"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  }
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  }
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  }