| # Board Environment Dependencies |
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| This demo is intended to run on the AidLux board environment where the AidLite QNN240 runtime is available. A normal development container can run `--dry_run`, but cannot execute the QNN contexts unless `import aidlite` succeeds. |
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| ## Verified Board Environment |
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| The current board used for validation reports: |
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| ```text |
| Python 3.10.12 |
| aidlite import: OK |
| numpy 1.26.4 |
| opencv-python / cv2 4.13.0 |
| Pillow / PIL 10.4.0 |
| ``` |
|
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| ## Required Runtime Components |
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| - AidLux / AidLite Python runtime with `aidlite` module. |
| - AidLite QNN240 plugin/runtime for `FrameworkType.TYPE_QNN240`. |
| - Qualcomm HTP/DSP runtime and valid board license. |
| - Board-side QNN context execution support for QCS8550 / HTP v73. |
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| The Python code checks the AidLite enum contract at startup: |
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| ```text |
| FrameworkType.TYPE_QNN240 = 109 |
| ImplementType.TYPE_LOCAL = 3 |
| AccelerateType.TYPE_DSP = 3 |
| ``` |
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| ## Required Python Packages |
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| The demo imports these Python packages at runtime: |
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| ```text |
| numpy |
| cv2 |
| PIL |
| aidlite |
| ``` |
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| Package usage: |
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| - `aidlite`: loads and invokes the four QNN240 encrypted context `.bin.aidem` files. |
| - `numpy`: tensor loading, dtype conversion, BEVFormer postprocess, NPZ output. |
| - `cv2`: board-side six-camera JPG preprocessing. |
| - `PIL`: camera-grid PNG/GIF visualization. |
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| ## Model/Data Files Required By Default Run |
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| Default command: |
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| ```bash |
| python3 code/python/run_test.py --invoke_nums 4 --output_dir outputs/final_sample4 |
| ``` |
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| Required model files: |
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| ```text |
| models/QCS8550/FP16/backbone_context.bin.aidem |
| models/QCS8550/FP16/scene_start_encoder_context.bin.aidem |
| models/QCS8550/FP16/temporal_encoder_context.bin.aidem |
| models/QCS8550/FP16/decoder_context.bin.aidem |
| ``` |
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| Required config files: |
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| ```text |
| code/python/configs/demo_config.json |
| code/python/configs/nms_runtime_contract.json |
| ``` |
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| Required sample data: |
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| ```text |
| code/python/datasets/sample4/asset_manifest.json |
| code/python/datasets/sample4/frames/sample_000..sample_003/ |
| ``` |
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| Each sample frame contains six raw camera JPGs plus the small auxiliary tensors required by the deployed contexts. |
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| ## Quick Environment Check |
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| Run on the board: |
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| ```bash |
| cd /home/aidlux/bevformer_delivery_demo_2026_07_08 |
| python3 -c "import aidlite, numpy, cv2; from PIL import Image; print('board env ok')" |
| python3 code/python/run_test.py --dry_run --check_raw_assets |
| ``` |
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| The dry-run checks paths, model SHA, sample assets, and scene-start/temporal routing. It does not invoke AidLite/DSP. |
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| ## Notes |
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| - Do not expect real inference to work in a host/container environment without AidLite. |
| - `configs/qnn_htp_configs/` is not required by runtime; it was only an optional encryption/audit supplement and is not included in the runtime demo package. |
| - Full inference timing and visualization are printed by the default command without adding extra timing flags. |
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