Upload 15 files

.gitattributes

@@ -33,3 +33,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+model_farm_litehrnet_qcs6490_qnn2.31_int8_aidlite/python/test.jpg filter=lfs diff=lfs merge=lfs -text
+model_farm_litehrnet_qcs6490_qnn2.31_w8a16_aidlite/python/test.jpg filter=lfs diff=lfs merge=lfs -text
+model_farm_litehrnet_qcs8550_qnn2.31_fp16_aidlite/python/test.jpg filter=lfs diff=lfs merge=lfs -text
+model_farm_litehrnet_qcs8550_qnn2.31_int8_aidlite/python/test.jpg filter=lfs diff=lfs merge=lfs -text
+model_farm_litehrnet_qcs8550_qnn2.31_w8a16_aidlite/python/test.jpg filter=lfs diff=lfs merge=lfs -text

model_farm_litehrnet_qcs6490_qnn2.31_int8_aidlite/README.md

@@ -0,0 +1,40 @@
+## Model Information
+
+### Source model
+- Input shape: [1x3x256x192]
+- Number of parameters: 1.08M
+- Model size: 13.82M
+- Output shape: [[17x2],[17],[17x64x48]]
+
+Source model repository: [Lite-HRNet](https://github.com/HRNet/Lite-HRNet)
+
+### Converted model
+
+- Precision: INT8
+- Backend: QNN2.31
+- Target Device: FV01 QCS6490
+
+## Inference with AidLite SDK
+
+### SDK installation
+Model Farm uses AidLite SDK as the model inference SDK. For details, please refer to the [AidLite Developer Documentation](https://v2.docs.aidlux.com/en/sdk-api/aidlite-sdk/)
+
+- Install AidLite SDK
+
+```bash
+# Install the appropriate version of the aidlite sdk
+sudo aid-pkg update
+sudo aid-pkg install aidlite-sdk
+# Download the qnn version that matches the above backend. Eg Install QNN2.23 Aidlite: sudo aid-pkg install aidlite-qnn223
+sudo aid-pkg install aidlite-{QNN VERSION}
+```
+
+- Verify AidLite SDK
+
+```bash
+# aidlite sdk c++ check
+python3 -c "import aidlite ; print(aidlite.get_library_version())"
+
+# aidlite sdk python check
+python3 -c "import aidlite ; print(aidlite.get_py_library_version())"
+```

model_farm_litehrnet_qcs6490_qnn2.31_int8_aidlite/models/cutoff_lite_hrnet_w8a8.qnn231.ctx.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:394920f2097603bcd32108c75b134951cb644b54c1ed084b34cdbd0492ee439f
+size 3379592

model_farm_litehrnet_qcs6490_qnn2.31_w8a16_aidlite/README.md

@@ -0,0 +1,40 @@
+## Model Information
+
+### Source model
+- Input shape: [1x3x256x192]
+- Number of parameters: 1.08M
+- Model size: 13.82M
+- Output shape: [[17x2],[17],[17x64x48]]
+
+Source model repository: [Lite-HRNet](https://github.com/HRNet/Lite-HRNet)
+
+### Converted model
+
+- Precision: W8A16
+- Backend: QNN2.31
+- Target Device: FV01 QCS6490
+
+## Inference with AidLite SDK
+
+### SDK installation
+Model Farm uses AidLite SDK as the model inference SDK. For details, please refer to the [AidLite Developer Documentation](https://v2.docs.aidlux.com/en/sdk-api/aidlite-sdk/)
+
+- Install AidLite SDK
+
+```bash
+# Install the appropriate version of the aidlite sdk
+sudo aid-pkg update
+sudo aid-pkg install aidlite-sdk
+# Download the qnn version that matches the above backend. Eg Install QNN2.23 Aidlite: sudo aid-pkg install aidlite-qnn223
+sudo aid-pkg install aidlite-{QNN VERSION}
+```
+
+- Verify AidLite SDK
+
+```bash
+# aidlite sdk c++ check
+python3 -c "import aidlite ; print(aidlite.get_library_version())"
+
+# aidlite sdk python check
+python3 -c "import aidlite ; print(aidlite.get_py_library_version())"
+```

model_farm_litehrnet_qcs6490_qnn2.31_w8a16_aidlite/models/cutoff_lite_hrnet_w8a16.qnn231.ctx.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c374d612fad566414d13297b29f5bf85a28af0e777db248d3dde5bc20f04857a
+size 3539336

model_farm_litehrnet_qcs8550_qnn2.31_fp16_aidlite/README.md

@@ -0,0 +1,40 @@
+## Model Information
+
+### Source model
+- Input shape: [1x3x256x192]
+- Number of parameters: 1.08M
+- Model size: 13.82M
+- Output shape: [[17x2],[17],[17x64x48]]
+
+Source model repository: [Lite-HRNet](https://github.com/HRNet/Lite-HRNet)
+
+### Converted model
+
+- Precision: FP16
+- Backend: QNN2.31
+- Target Device: SNM972 QCS8550
+
+## Inference with AidLite SDK
+
+### SDK installation
+Model Farm uses AidLite SDK as the model inference SDK. For details, please refer to the [AidLite Developer Documentation](https://v2.docs.aidlux.com/en/sdk-api/aidlite-sdk/)
+
+- Install AidLite SDK
+
+```bash
+# Install the appropriate version of the aidlite sdk
+sudo aid-pkg update
+sudo aid-pkg install aidlite-sdk
+# Download the qnn version that matches the above backend. Eg Install QNN2.23 Aidlite: sudo aid-pkg install aidlite-qnn223
+sudo aid-pkg install aidlite-{QNN VERSION}
+```
+
+- Verify AidLite SDK
+
+```bash
+# aidlite sdk c++ check
+python3 -c "import aidlite ; print(aidlite.get_library_version())"
+
+# aidlite sdk python check
+python3 -c "import aidlite ; print(aidlite.get_py_library_version())"
+```

model_farm_litehrnet_qcs8550_qnn2.31_fp16_aidlite/models/cutoff_lite_hrnet_fp16.qnn231.ctx.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:88503bf7ba419bd30fe9c29675415bbb9941fb9690588e28121cec0cb4e8b7f9
+size 5819520

model_farm_litehrnet_qcs8550_qnn2.31_int8_aidlite/README.md

@@ -0,0 +1,40 @@
+## Model Information
+
+### Source model
+- Input shape: [1x3x256x192]
+- Number of parameters: 1.08M
+- Model size: 13.82M
+- Output shape: [[17x2],[17],[17x64x48]]
+
+Source model repository: [Lite-HRNet](https://github.com/HRNet/Lite-HRNet)
+
+### Converted model
+
+- Precision: INT8
+- Backend: QNN2.31
+- Target Device: SNM972 QCS8550
+
+## Inference with AidLite SDK
+
+### SDK installation
+Model Farm uses AidLite SDK as the model inference SDK. For details, please refer to the [AidLite Developer Documentation](https://v2.docs.aidlux.com/en/sdk-api/aidlite-sdk/)
+
+- Install AidLite SDK
+
+```bash
+# Install the appropriate version of the aidlite sdk
+sudo aid-pkg update
+sudo aid-pkg install aidlite-sdk
+# Download the qnn version that matches the above backend. Eg Install QNN2.23 Aidlite: sudo aid-pkg install aidlite-qnn223
+sudo aid-pkg install aidlite-{QNN VERSION}
+```
+
+- Verify AidLite SDK
+
+```bash
+# aidlite sdk c++ check
+python3 -c "import aidlite ; print(aidlite.get_library_version())"
+
+# aidlite sdk python check
+python3 -c "import aidlite ; print(aidlite.get_py_library_version())"
+```

model_farm_litehrnet_qcs8550_qnn2.31_int8_aidlite/models/cutoff_lite_hrnet_w8a8.qnn231.ctx.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4b9780d7ff92343fe69c0c7d48e7f02766b44e3370e7633d49e54283b731c803
+size 2535752

model_farm_litehrnet_qcs8550_qnn2.31_w8a16_aidlite/README.md

@@ -0,0 +1,40 @@
+## Model Information
+
+### Source model
+- Input shape: [1x3x256x192]
+- Number of parameters: 1.08M
+- Model size: 13.82M
+- Output shape: [[17x2],[17],[17x64x48]]
+
+Source model repository: [Lite-HRNet](https://github.com/HRNet/Lite-HRNet)
+
+### Converted model
+
+- Precision: W8A16
+- Backend: QNN2.31
+- Target Device: SNM972 QCS8550
+
+## Inference with AidLite SDK
+
+### SDK installation
+Model Farm uses AidLite SDK as the model inference SDK. For details, please refer to the [AidLite Developer Documentation](https://v2.docs.aidlux.com/en/sdk-api/aidlite-sdk/)
+
+- Install AidLite SDK
+
+```bash
+# Install the appropriate version of the aidlite sdk
+sudo aid-pkg update
+sudo aid-pkg install aidlite-sdk
+# Download the qnn version that matches the above backend. Eg Install QNN2.23 Aidlite: sudo aid-pkg install aidlite-qnn223
+sudo aid-pkg install aidlite-{QNN VERSION}
+```
+
+- Verify AidLite SDK
+
+```bash
+# aidlite sdk c++ check
+python3 -c "import aidlite ; print(aidlite.get_library_version())"
+
+# aidlite sdk python check
+python3 -c "import aidlite ; print(aidlite.get_py_library_version())"
+```

model_farm_litehrnet_qcs8550_qnn2.31_w8a16_aidlite/models/cutoff_lite_hrnet_w8a16.qnn231.ctx.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0b59f98bc2ef9dc7943ee905f3b5d8eff03ad32737a7f63b7ec4d0a4ab68f0c4
+size 2834760