Hugging Face's logo

qualcomm
/
LiteHRNet

Keypoint Detection
PyTorch
TF Lite
ONNX
android
Model card Files Community
qaihm-bot commited on
Commit
d898146
·
verified ·
1 Parent(s): e551ad7

Upload README.md with huggingface_hub

Browse files
Files changed (1) hide show
  1. README.md +18 -16
README.md CHANGED
@@ -1,9 +1,9 @@
1
  ---
2
  library_name: pytorch
3
  license: apache-2.0
4
- pipeline_tag: keypoint-detection
5
  tags:
6
  - android
 
7
 
8
  ---
9
 
@@ -33,20 +33,22 @@ More details on model performance across various devices, can be found
33
 
34
  | Model | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
35
  |---|---|---|---|---|---|---|---|---|
36
- | LiteHRNet | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 7.85 ms | 0 - 16 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
37
- | LiteHRNet | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 7.38 ms | 0 - 24 MB | FP16 | NPU | [LiteHRNet.onnx](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.onnx) |
38
- | LiteHRNet | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 4.775 ms | 0 - 36 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
39
- | LiteHRNet | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 4.507 ms | 0 - 48 MB | FP16 | NPU | [LiteHRNet.onnx](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.onnx) |
40
- | LiteHRNet | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 5.265 ms | 0 - 37 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
41
- | LiteHRNet | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 4.116 ms | 1 - 45 MB | FP16 | NPU | [LiteHRNet.onnx](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.onnx) |
42
- | LiteHRNet | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 7.849 ms | 0 - 15 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
43
- | LiteHRNet | SA7255P ADP | SA7255P | TFLITE | 28.427 ms | 0 - 30 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
44
- | LiteHRNet | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 7.847 ms | 0 - 16 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
45
- | LiteHRNet | SA8295P ADP | SA8295P | TFLITE | 9.954 ms | 0 - 33 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
46
- | LiteHRNet | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 7.871 ms | 0 - 16 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
47
- | LiteHRNet | SA8775P ADP | SA8775P | TFLITE | 10.701 ms | 0 - 30 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
48
- | LiteHRNet | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 8.497 ms | 0 - 31 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
49
- | LiteHRNet | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 8.206 ms | 6 - 6 MB | FP16 | NPU | [LiteHRNet.onnx](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.onnx) |
 
 
50
 
51
 
52
 
@@ -56,7 +58,7 @@ More details on model performance across various devices, can be found
56
 
57
  Install the package via pip:
58
  ```bash
59
- pip install "qai-hub-models[litehrnet]"
60
  ```
61
 
62
 
 
1
  ---
2
  library_name: pytorch
3
  license: apache-2.0
 
4
  tags:
5
  - android
6
+ pipeline_tag: keypoint-detection
7
 
8
  ---
9
 
 
33
 
34
  | Model | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
35
  |---|---|---|---|---|---|---|---|---|
36
+ | LiteHRNet | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 7.847 ms | 0 - 16 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
37
+ | LiteHRNet | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 7.249 ms | 0 - 22 MB | FP16 | NPU | [LiteHRNet.onnx](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.onnx) |
38
+ | LiteHRNet | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 4.778 ms | 0 - 41 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
39
+ | LiteHRNet | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 4.575 ms | 1 - 49 MB | FP16 | NPU | [LiteHRNet.onnx](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.onnx) |
40
+ | LiteHRNet | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 4.307 ms | 0 - 40 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
41
+ | LiteHRNet | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 4.012 ms | 1 - 44 MB | FP16 | NPU | [LiteHRNet.onnx](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.onnx) |
42
+ | LiteHRNet | SA7255P ADP | SA7255P | TFLITE | 28.578 ms | 0 - 29 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
43
+ | LiteHRNet | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 7.852 ms | 0 - 16 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
44
+ | LiteHRNet | SA8295P ADP | SA8295P | TFLITE | 9.859 ms | 0 - 27 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
45
+ | LiteHRNet | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 7.846 ms | 0 - 15 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
46
+ | LiteHRNet | SA8775P ADP | SA8775P | TFLITE | 10.762 ms | 0 - 29 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
47
+ | LiteHRNet | QCS8275 (Proxy) | QCS8275 Proxy | TFLITE | 28.578 ms | 0 - 29 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
48
+ | LiteHRNet | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 7.854 ms | 0 - 14 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
49
+ | LiteHRNet | QCS9075 (Proxy) | QCS9075 Proxy | TFLITE | 10.762 ms | 0 - 29 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
50
+ | LiteHRNet | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 8.504 ms | 0 - 34 MB | FP16 | NPU | [LiteHRNet.tflite](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.tflite) |
51
+ | LiteHRNet | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 8.177 ms | 6 - 6 MB | FP16 | NPU | [LiteHRNet.onnx](https://huggingface.co/qualcomm/LiteHRNet/blob/main/LiteHRNet.onnx) |
52
 
53
 
54
 
 
58
 
59
  Install the package via pip:
60
  ```bash
61
+ pip install "qai-hub-models[litehrnet]" torch==2.4.1 -f https://download.openmmlab.com/mmcv/dist/cpu/torch2.4/index.html -f https://qaihub-public-python-wheels.s3.us-west-2.amazonaws.com/index.html
62
  ```
63
 
64