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Upload folder using huggingface_hub

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.gitattributes CHANGED
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ qaihub/LibreYOLOXs_fp32.dlc filter=lfs diff=lfs merge=lfs -text
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+ qaihub/LibreYOLOXs_int8.dlc filter=lfs diff=lfs merge=lfs -text
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+ qairt/LibreYOLOXs_fp32.dlc filter=lfs diff=lfs merge=lfs -text
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+ qairt/LibreYOLOXs_int8.dlc filter=lfs diff=lfs merge=lfs -text
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+ snpe/LibreYOLOXs_fp32.dlc filter=lfs diff=lfs merge=lfs -text
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+ snpe/LibreYOLOXs_int8.dlc filter=lfs diff=lfs merge=lfs -text
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README.md CHANGED
@@ -1,3 +1,158 @@
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  ---
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  license: mit
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: mit
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+ language:
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+ - en
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+ pipeline_tag: object-detection
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+ tags:
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+ - object-detection
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+ - yolox
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+ - onnx
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+ - dlc
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+ - qualcomm
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+ - snapdragon
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+ - qairt
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+ - snpe
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+ - qai-hub
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+ - edge-inference
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+ base_model: LibreYOLO/LibreYOLOXs
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+ datasets:
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+ - merve/coco
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  ---
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+
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+ # LibreYOLOXs Qualcomm-Optimized Model Artifacts
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+
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+ This directory is the shared artifact location for the notebooks in
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+ [`../notebooks/`](../notebooks/). The repository tracks the documentation and
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+ ignore rules here; model binaries are downloaded or generated locally when you
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+ run the workflows.
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+
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+ The same source model is used for three deployment paths:
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+
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+ - **QAIRT** local conversion and quantization
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+ - **SNPE** local conversion and quantization
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+ - **QAI Hub** cloud compilation, quantization, and profiling
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+
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+ ---
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+
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+ ## Model overview
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+
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+ | Property | Value |
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+ |---|---|
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+ | Architecture | YOLOX-Small (LibreYOLOXs) |
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+ | Framework | [LibreYOLO](https://github.com/LibreYOLO/libreyolo) |
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+ | Task | Object detection |
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+ | Base checkpoint | [LibreYOLO/LibreYOLOXs](https://huggingface.co/LibreYOLO/LibreYOLOXs) |
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+ | Input tensor | `images` |
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+ | Input shape | `1 x 3 x 640 x 640` |
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+ | Input format | BGR `float32`, NCHW, values in `0-255` |
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+
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+ ---
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+
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+ ## Artifact flow
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+
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+ ```text
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+ LibreYOLOXs.pt
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+ |
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+ `---> LibreYOLOXs.onnx
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+ |\
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+ | `---> qairt/LibreYOLOXs_fp32.dlc
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+ | `---> qairt/LibreYOLOXs_int8.dlc
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+ |
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+ | `---> snpe/LibreYOLOXs_fp32.dlc
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+ | `---> snpe/LibreYOLOXs_int8.dlc
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+ |
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+ `---> qaihub/LibreYOLOXs_fp32.dlc
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+ `---> qaihub/LibreYOLOXs_int8.dlc
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+ ```
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+
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+ All three notebooks reuse the same exported ONNX model.
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+
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+ ---
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+
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+ ## Expected files
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+
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+ | Path | Produced by | Description |
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+ |---|---|---|
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+ | `LibreYOLOXs.pt` | All notebooks | Base PyTorch checkpoint, downloaded on demand |
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+ | `LibreYOLOXs.onnx` | All notebooks | Shared ONNX export used by all backend flows |
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+ | `qairt/LibreYOLOXs_fp32.dlc` | QAIRT notebook | FP32 DLC produced by `qairt-converter` |
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+ | `qairt/LibreYOLOXs_int8.dlc` | QAIRT notebook | INT8 DLC produced by `qairt-quantizer` |
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+ | `snpe/LibreYOLOXs_fp32.dlc` | SNPE notebook | FP32 DLC produced by `snpe-onnx-to-dlc` |
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+ | `snpe/LibreYOLOXs_int8.dlc` | SNPE notebook | INT8 DLC produced by `snpe-dlc-quantize` |
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+ | `qaihub/LibreYOLOXs_fp32.dlc` | QAI Hub notebook | FP32 DLC downloaded from a cloud compile job |
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+ | `qaihub/LibreYOLOXs_int8.dlc` | QAI Hub notebook | INT8 DLC downloaded from cloud quantize + compile jobs |
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+
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+ ---
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+
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+ ## Tensor contract
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+
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+ ### Input
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+
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+ | Property | Value |
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+ |---|---|
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+ | Name | `images` |
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+ | Shape | `1 x 3 x 640 x 640` |
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+ | Layout | NCHW |
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+ | Data type | `float32` |
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+ | Color order | BGR |
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+
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+ Preprocessing used by the notebooks:
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+
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+ 1. Letterbox-resize to `640 x 640`.
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+ 2. Pad with value `114`.
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+ 3. Keep BGR channel order.
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+ 4. Keep values in the `0-255` range.
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+ 5. Transpose from HWC to CHW before serialization / inference input assembly.
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+
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+ ### Outputs
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+
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+ The exported ONNX model is validated in each notebook before backend-specific
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+ compilation. The documentation in this directory assumes the shared decoded
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+ output layout used by the notebooks:
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+
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+ | Output | Shape | Description |
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+ |---|---|---|
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+ | `bboxes` | `1 x 8400 x 4` | Bounding-box coordinates |
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+ | `scores` | `1 x 8400 x 81` | Objectness plus 80 COCO class scores |
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+
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+ ---
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+
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+ ## Calibration data
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+
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+ INT8 flows use representative data prepared by the notebooks from COCO 2017
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+ validation images:
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+
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+ - source images are staged under `docker/notebooks/dataset/`
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+ - calibration tensors are written to `docker/notebooks/subset/calib/`
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+ - validation tensors and metadata are written to `docker/notebooks/subset/val/`
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+ - manifests are written to `subset/calib/filenames.txt` and `subset/val/filenames.txt`
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+
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+ The local QAIRT and SNPE quantizers read those manifests directly. The QAI Hub
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+ notebook loads the same `.raw` tensors into NumPy arrays and submits them to the
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+ cloud quantization job.
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+
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+ ---
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+
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+ ## Downloading published artifacts
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+
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+ Published files are hosted on Hugging Face:
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+
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+ - [fabricionarcizo/LibreYOLOXs](https://huggingface.co/fabricionarcizo/LibreYOLOXs)
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+
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+ Example download:
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+
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+ ```bash
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+ huggingface-cli download fabricionarcizo/LibreYOLOXs \
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+ --local-dir docker/models \
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+ --exclude "*.gitattributes" "README.md"
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+ ```
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+
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+ You can also generate the same artifact layout locally by running the notebooks
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+ in [`../notebooks/`](../notebooks/).
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+
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+ ---
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+
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+ ## Related documentation
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+
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+ - [`../README.md`](../README.md) - Docker environment and setup
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+ - [`../notebooks/README.md`](../notebooks/README.md) - notebook workflows and generated data layout
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