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@@ -33,3 +33,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
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 *tfevents* filter=lfs diff=lfs merge=lfs -text
+model_farm_pidnet_qcs6490_qnn2.31_int8_aidlite/python/bus.jpg filter=lfs diff=lfs merge=lfs -text
+model_farm_pidnet_qcs6490_qnn2.31_w8a16_aidlite/python/bus.jpg filter=lfs diff=lfs merge=lfs -text
+model_farm_pidnet_qcs8550_qnn2.31_fp16_aidlite/python/bus.jpg filter=lfs diff=lfs merge=lfs -text
+model_farm_pidnet_qcs8550_qnn2.31_int8_aidlite/python/bus.jpg filter=lfs diff=lfs merge=lfs -text
+model_farm_pidnet_qcs8550_qnn2.31_w8a16_aidlite/python/bus.jpg filter=lfs diff=lfs merge=lfs -text

model_farm_pidnet_qcs6490_qnn2.31_int8_aidlite/README.md

@@ -0,0 +1,43 @@
+## Model Information
+
+### Source model
+- Input shape: [1,3,1024,2048]
+- Number of parameters: 7.62M
+- Model size: 29.14M
+- Output shape: [1,19,128,256]
+
+Source model repository: [PidNet](https://github.com/XuJiacong/PIDNet)
+
+### Converted model
+
+- Precision: INT8
+- Backend: QNN2.31
+- Target Device: FV01 QCS6490
+
+## Model Conversion Reference
+User can find model conversion reference at [aimo.aidlux.com](https://aimo.aidlux.com/#/public/dbeff4ef-3608-4769-8b3d-7736054750d6)
+
+## 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_pidnet_qcs6490_qnn2.31_int8_aidlite/models/PidNet_w8a8.qnn231.ctx.bin

@@ -0,0 +1,3 @@
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model_farm_pidnet_qcs6490_qnn2.31_w8a16_aidlite/README.md

@@ -0,0 +1,43 @@
+## Model Information
+
+### Source model
+- Input shape: [1,3,1024,2048]
+- Number of parameters: 7.62M
+- Model size: 29.14M
+- Output shape: [1,19,128,256]
+
+Source model repository: [PidNet](https://github.com/XuJiacong/PIDNet)
+
+### Converted model
+
+- Precision: W8A16
+- Backend: QNN2.31
+- Target Device: FV01 QCS6490
+
+## Model Conversion Reference
+User can find model conversion reference at [aimo.aidlux.com](https://aimo.aidlux.com/#/public/9bc8c6fe-2e52-4a61-bacb-a3b33565277b)
+
+## 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_pidnet_qcs6490_qnn2.31_w8a16_aidlite/models/PidNet_w8a16.qnn231.ctx.bin

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+size 9477176

model_farm_pidnet_qcs8550_qnn2.31_fp16_aidlite/README.md

@@ -0,0 +1,43 @@
+## Model Information
+
+### Source model
+- Input shape: [1,3,1024,2048]
+- Number of parameters: 7.62M
+- Model size: 29.14M
+- Output shape: [1,19,128,256]
+
+Source model repository: [PidNet](https://github.com/XuJiacong/PIDNet)
+
+### Converted model
+
+- Precision: FP16
+- Backend: QNN2.31
+- Target Device: SNM972 QCS8550
+
+## Model Conversion Reference
+User can find model conversion reference at [aimo.aidlux.com](https://aimo.aidlux.com/#/public/378c1dad-6220-457b-9576-c22c477f5d24)
+
+## 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_pidnet_qcs8550_qnn2.31_fp16_aidlite/models/PidNet_fp16.qnn231.ctx.bin

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model_farm_pidnet_qcs8550_qnn2.31_int8_aidlite/README.md

@@ -0,0 +1,43 @@
+## Model Information
+
+### Source model
+- Input shape: [1,3,1024,2048]
+- Number of parameters: 7.62M
+- Model size: 29.14M
+- Output shape: [1,19,128,256]
+
+Source model repository: [PidNet](https://github.com/XuJiacong/PIDNet)
+
+### Converted model
+
+- Precision: INT8
+- Backend: QNN2.31
+- Target Device: SNM972 QCS8550
+
+## Model Conversion Reference
+User can find model conversion reference at [aimo.aidlux.com](https://aimo.aidlux.com/#/public/cc7ce499-e0d4-4333-9c7b-0dd280ffa79f)
+
+## 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_pidnet_qcs8550_qnn2.31_int8_aidlite/models/PidNet_w8a8.qnn231.ctx.bin

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model_farm_pidnet_qcs8550_qnn2.31_int8_aidlite/models/htp_backend_extensions.json

@@ -0,0 +1 @@
+{"backend_extensions": {"shared_library_path": "/home/opt/qcom/aistack/qairt/2.31.0.250130/lib/x86_64-linux-clang/libQnnHtpNetRunExtensions.so", "config_file_path": "/data0/ai-transform-data/data/a828a485-b328-4bd6-a238-2b7145bd73f3/PidNet_save_path/htp_config.json"}}

model_farm_pidnet_qcs8550_qnn2.31_w8a16_aidlite/README.md

@@ -0,0 +1,43 @@
+## Model Information
+
+### Source model
+- Input shape: [1,3,1024,2048]
+- Number of parameters: 7.62M
+- Model size: 29.14M
+- Output shape: [1,19,128,256]
+
+Source model repository: [PidNet](https://github.com/XuJiacong/PIDNet)
+
+### Converted model
+
+- Precision: W8A16
+- Backend: QNN2.31
+- Target Device: SNM972 QCS8550
+
+## Model Conversion Reference
+User can find model conversion reference at [aimo.aidlux.com](https://aimo.aidlux.com/#/public/bd9876b1-0725-48f7-847b-af2d95648023)
+
+## 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_pidnet_qcs8550_qnn2.31_w8a16_aidlite/models/PidNet_w8a16.qnn231.ctx.bin

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