LuxonisML - v0.4.0 (#38)

.github/workflows/modelconverter_test.yaml

@@ -53,6 +53,18 @@ jobs:
         credentials_json: ${{ secrets.GCP_CREDENTIALS }}
         token_format: access_token
 
+    - name: Set up Cloud SDK
+      uses: google-github-actions/setup-gcloud@v1
+
+    - name: Download file from GCS
+      run: |
+        cd docker/extra_packages
+        if [ "$PACKAGE" = "rvc4" ]; then
+            gsutil cp gs://luxonis-test-bucket/modelconverter/build-artifacts/snpe.zip .
+        elif [ "$PACKAGE" = "rvc2" ] || [ "$PACKAGE" = "rvc3" ]; then
+            gsutil cp gs://luxonis-test-bucket/modelconverter/build-artifacts/openvino_2022_3_vpux_drop_patched.tar.gz .
+        fi
+
     - name: Run Tests
       run: |
         pytest -s --verbose "tests/test_packages/test_$PACKAGE.py"

.github/workflows/publish.yaml

@@ -108,9 +108,9 @@ jobs:
       run: |
         cd docker/extra_packages
         if [ "$PACKAGE" = "rvc4" ]; then
-            gsutil cp gs://luxonis-test-bucket/modelconverter/build-artifacts/snpe.zip snpe.zip
+            gsutil cp gs://luxonis-test-bucket/modelconverter/build-artifacts/snpe.zip .
         elif [ "$PACKAGE" = "rvc2" ] || [ "$PACKAGE" = "rvc3" ]; then
-            gsutil cp gs://luxonis-test-bucket/modelconverter/build-artifacts/openvino_2022_3_vpux_drop_patched.tar.gz openvino_2022_3_vpux_drop_patched.tar.gz
+            gsutil cp gs://luxonis-test-bucket/modelconverter/build-artifacts/openvino_2022_3_vpux_drop_patched.tar.gz .
         fi
 
     - name: Publish

modelconverter/packages/base_exporter.py

@@ -76,32 +76,8 @@ def __init__(
             logger.warning("Calibration has been disabled.")
             logger.warning("The quantization step will be skipped.")
 
-        for name, inp in self.inputs.items():
-            calib = inp.calibration
-            if calib is None:
-                continue
-            if not isinstance(calib, RandomCalibrationConfig):
-                continue
-            logger.warning(
-                f"Random calibration is being used for input '{name}'."
-            )
-            dest = self.intermediate_outputs_dir / "random" / name
-            dest.mkdir(parents=True)
-            if inp.shape is None:
-                exit_with(
-                    ValueError(
-                        f"Random calibration requires shape to be specified for input '{name}'."
-                    )
-                )
-
-            for i in range(calib.max_images):
-                arr = np.random.normal(calib.mean, calib.std, inp.shape)
-                arr = np.clip(arr, calib.min_value, calib.max_value)
-
-                arr = arr.astype(calib.data_type.as_numpy_dtype())
-                np.save(dest / f"{i}.npy", arr)
-
-            self.inputs[name].calibration = ImageCalibrationConfig(path=dest)
+        if self.target != Target.RVC2:
+            self._prepare_random_calibration_data()
 
     @property
     def inference_model_path(self) -> Path:
@@ -180,6 +156,34 @@ def read_img_dir(self, path: Path, max_images: int) -> List[Path]:
             imgs = imgs[:max_images]
         return imgs
 
+    def _prepare_random_calibration_data(self) -> None:
+        for name, inp in self.inputs.items():
+            calib = inp.calibration
+            if calib is None:
+                continue
+            if not isinstance(calib, RandomCalibrationConfig):
+                continue
+            logger.warning(
+                f"Random calibration is being used for input '{name}'."
+            )
+            dest = self.intermediate_outputs_dir / "random" / name
+            dest.mkdir(parents=True)
+            if inp.shape is None:
+                exit_with(
+                    ValueError(
+                        f"Random calibration requires shape to be specified for input '{name}'."
+                    )
+                )
+
+            for i in range(calib.max_images):
+                arr = np.random.normal(calib.mean, calib.std, inp.shape)
+                arr = np.clip(arr, calib.min_value, calib.max_value)
+
+                arr = arr.astype(calib.data_type.as_numpy_dtype())
+                np.save(dest / f"{i}.npy", arr)
+
+            self.inputs[name].calibration = ImageCalibrationConfig(path=dest)
+
     @staticmethod
     def _attach_suffix(path: Union[Path, str], suffix: str) -> Path:
         return Path(str(Path(path).with_suffix("")) + f"-{suffix.lstrip('-')}")

modelconverter/packages/rvc2/exporter.py

@@ -1,6 +1,7 @@
 import subprocess
 import tempfile
 from functools import partial
+from importlib.metadata import version
 from logging import getLogger
 from multiprocessing import Pool, cpu_count
 from os import environ as env

modelconverter/utils/__init__.py

@@ -22,10 +22,10 @@
 from .layout import guess_new_layout, make_default_layout
 from .metadata import Metadata, get_metadata
 from .nn_archive import (
+    archive_from_model,
     get_archive_input,
     modelconverter_config_to_nn,
     process_nn_archive,
-    archive_from_model,
 )
 from .onnx_tools import onnx_attach_normalization_to_inputs
 from .subprocess import subprocess_run
@@ -56,5 +56,5 @@
     "make_default_layout",
     "Metadata",
     "get_metadata",
-    "archive_from_model"
+    "archive_from_model",
 ]

modelconverter/utils/nn_archive.py

@@ -3,6 +3,7 @@
 from pathlib import Path
 from typing import Any, Dict, Optional, Tuple
 
+from luxonis_ml.nn_archive.config import CONFIG_VERSION
 from luxonis_ml.nn_archive.config import Config as NNArchiveConfig
 from luxonis_ml.nn_archive.config_building_blocks import (
     Input as NNArchiveInput,
@@ -133,7 +134,7 @@ def modelconverter_config_to_nn(
     cfg = config.stages[main_stage_key]
 
     archive_cfg = {
-        "config_version": "1.0",
+        "config_version": CONFIG_VERSION.__args__[-1],  # type: ignore
         "model": {
             "metadata": {
                 "name": model_name.stem,

requirements.txt

@@ -1,9 +1,8 @@
 Pillow
 PyYAML
 gcsfs
-# luxonis-ml[data,nn_archive] >= 0.2.3
-luxonis-ml[data,nn_archive] @ git+https://github.com/luxonis/luxonis-ml.git@dev
-onnx
+luxonis-ml[data,nn_archive] >= 0.4.0
+onnx<1.17.0
 onnxruntime
 onnxsim
 s3fs