slalom/qai-cli
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

clean

Browse Source
This commit is contained in:
slalom
2026-06-09 12:21:25 -04:00
parent c6d4da66ae
commit 6c9f30d290
1 changed files with 6 additions and 13 deletions
Download Patch File Download Diff File Expand all files Collapse all files

19
examples/meter-detection/README.md
View File

@@ -189,8 +189,7 @@ aihub:
output_dir: build/qai-hub/meter-detection output_dir: build/qai-hub/meter-detection
``` ```
Use the same image size configured in `sagemaker.training.hyperparameters.imgsz`. For example, a smoke-test model Use the same image size configured in `sagemaker.training.hyperparameters.imgsz`. For example, a smoke-test model trained with `imgsz: 320` requires `images: [[1, 3, 320, 320], float32]`.
trained with `imgsz: 320` requires `images: [[1, 3, 320, 320], float32]`.
## 7. Prepare AI Hub Inputs ## 7. Prepare AI Hub Inputs
@@ -207,8 +206,7 @@ examples/meter-detection/data/aihub_calibration/*.npy
examples/meter-detection/data/inputs.npz examples/meter-detection/data/inputs.npz
``` ```
The script applies the preprocessing expected by the exported YOLO model: aspect-ratio-preserving letterboxing, The script applies the preprocessing expected by the exported YOLO model: aspect-ratio-preserving letterboxing, RGB channel order, channel-first layout, and pixel values normalized to `[0, 1]`.
RGB channel order, channel-first layout, and pixel values normalized to `[0, 1]`.
Set `--image-size` to the training `imgsz` value when it is not `640`. Set `--image-size` to the training `imgsz` value when it is not `640`.
@@ -223,15 +221,11 @@ qc-cli ai-hub upload \
--from-job qc-cli-YYYYMMDD-HHMMSS --from-job qc-cli-YYYYMMDD-HHMMSS
``` ```
The command downloads the job's `model.tar.gz`, finds `model.onnx`, uploads it to AI Hub, and runs quantization, The command downloads the job's `model.tar.gz`, finds `model.onnx`, uploads it to AI Hub, and runs quantization, compilation, validation, and profiling. The uploaded source model uses the configured `aihub.model_name`.
compilation, validation, and profiling. The uploaded source model uses the configured
`aihub.model_name`.
The training example sanitizes the Ultralytics ONNX export before saving `model.onnx`. This removes graph input or The training example sanitizes the Ultralytics ONNX export before saving `model.onnx`. This removes graph input or output names, such as `output0`, that are duplicated in the ONNX `value_info` metadata and rejected by AI Hub.
output names, such as `output0`, that are duplicated in the ONNX `value_info` metadata and rejected by AI Hub.
For a model already downloaded by a failed upload attempt, sanitize the extracted ONNX file and retry using the local For a model already downloaded by a failed upload attempt, sanitize the extracted ONNX file and retry using the local model. Replace the job name in both paths:
model. Replace the job name in both paths:
```bash ```bash
uv run --with onnx python examples/meter-detection/source/sanitize_onnx.py \ uv run --with onnx python examples/meter-detection/source/sanitize_onnx.py \
@@ -244,8 +238,7 @@ qc-cli ai-hub upload \
--onnx-path build/qai-hub/meter-detection/model.aihub.onnx --onnx-path build/qai-hub/meter-detection/model.aihub.onnx
``` ```
If the meter-detection job is still the last training job in `.qc-cli.json`, `--from-job` can be omitted. Keeping it If the meter-detection job is still the last training job in `.qc-cli.json`, `--from-job` can be omitted. Keeping it explicit prevents accidentally uploading an artifact from a different training run.
explicit prevents accidentally uploading an artifact from a different training run.
To resume after a completed step, use one of: To resume after a completed step, use one of: