Pre-docs cleanup: unify terminology and tighten the lint gate

.github/scripts/changed-platforms.sh

@@ -25,8 +25,9 @@ select_platforms() {
 while IFS= read -r file; do
   [ -n "${file}" ] || continue
   case "${file}" in
-    # Documentation and repository chores never reach an image.
-    *.md | LICENSE | .gitignore | .dockerignore | .pre-commit-config.yaml) ;;
+    # Documentation and repository chores never reach an image. `.dockerignore`
+    # is not in this group: it defines the build context of every image.
+    *.md | LICENSE | .gitignore | .pre-commit-config.yaml) ;;
 
     # The conversion tests are unaffected by the other test suites, and the
     # unit tests run on every pull request anyway.
@@ -40,10 +41,12 @@ while IFS= read -r file; do
       ;;
     .github/*) ;;
 
-    modelconverter/packages/rvc2/*) select_platforms rvc2 ;;
-    modelconverter/packages/rvc3/*) select_platforms rvc3 ;;
-    modelconverter/packages/rvc4/*) select_platforms rvc4 ;;
-    modelconverter/packages/hailo/*) select_platforms hailo ;;
+    # `RVC3Exporter` subclasses `RVC2Exporter`, and `RVC3Inferer` is an alias of
+    # `RVC2Inferer`, so a change to the RVC2 code can break RVC3.
+    modelconverter/platforms/rvc2/*) select_platforms rvc2 rvc3 ;;
+    modelconverter/platforms/rvc3/*) select_platforms rvc3 ;;
+    modelconverter/platforms/rvc4/*) select_platforms rvc4 ;;
+    modelconverter/platforms/hailo/*) select_platforms hailo ;;
 
     # RVC3's image is built on OpenVINO like RVC2's and reuses its entrypoint,
     # so the shared OpenVINO tooling and RVC2's docker directory affect both.

.github/workflows/ci.yaml

@@ -277,7 +277,7 @@ jobs:
               pip install \
               \"luxonis-ml[data,nn-archive] @ git+https://github.com/luxonis/luxonis-ml.git@${ML_REF}\" \
               --upgrade --force-reinstall && \
-              pip install -r /app/modelconverter/packages/${PACKAGE}/requirements.txt && \
+              pip install -r /app/modelconverter/platforms/${PACKAGE}/requirements.txt && \
               pip install -r /tmp/numpy-pin.txt &&"
           else
             ML_INSTALL_COMMAND=""

.pre-commit-config.yaml

@@ -1,6 +1,11 @@
 default_language_version:
   python: python3
 repos:
+  - repo: https://github.com/crate-ci/typos
+    rev: v1.47.2
+    hooks:
+      - id: typos
+
   - repo: https://github.com/astral-sh/ruff-pre-commit
     rev: v0.16.0
     hooks:
@@ -35,7 +40,6 @@ repos:
     hooks:
       - id: trailing-whitespace
       - id: check-docstring-first
-        exclude: luxonis_ml/typing.py
       - id: check-executables-have-shebangs
       - id: check-illegal-windows-names
       - id: check-shebang-scripts-are-executable

README.md

@@ -193,7 +193,7 @@ It is recommended to use Ubuntu OS for the best compatibility.
 On Windows or MacOS, it is recommended to install `docker` using the [Docker Desktop](https://www.docker.com/products/docker-desktop).
 Otherwise, follow the installation instructions for your OS from the [official website](https://docs.docker.com/engine/install/).
 
-In order for the images to be build successfully, you need to download additional packages depending on the selected target and the desired version of the underlying conversion tools.
+In order for the images to be built successfully, you need to download additional packages depending on the selected platform and the desired version of the underlying conversion tools.
 
 ##### RVC2
 
@@ -241,8 +241,8 @@ This section is optional if you are using the `modelconverter` CLI, as it will a
 In other cases, navigate to the root directory of the repository and run the following command:
 
 ```bash
-docker build -f docker/$TARGET/Dockerfile \
-             -t luxonis/modelconverter-$TARGET:<tool-version>-latest .
+docker build -f docker/$PLATFORM/Dockerfile \
+             -t luxonis/modelconverter-$PLATFORM:<tool-version>-latest .
 ```
 
 If you want to build the image with a different version of the underlying conversion tools than is the default one, you also need to pass the `--build-arg` flag with the desired version. For example, to build the `RVC2` image with `2021.4.0`, use:
@@ -254,7 +254,7 @@ docker build -f docker/rvc2/Dockerfile \
 ```
 
 > [!NOTE]
-> When the `--build-arg` flag is not provided, the Dockerfiles (`docker/<target>/Dockerfile`) fall back to their built-in default tool versions:
+> When the `--build-arg` flag is not provided, the Dockerfiles (`docker/<platform>/Dockerfile`) fall back to their built-in default tool versions:
 >
 > - RVC2: `2022.3.0`
 > - RVC4: `2.41.0`
@@ -349,6 +349,7 @@ output/
     ├── resnet18.dlc
     ├── modelconverter.log
     ├── config.yaml
+    ├── buildinfo.json
     └── intermediate_outputs/
         └── <intermediate files generated during the conversion>
 ```
@@ -357,7 +358,7 @@ The `output_dir` can be specified using the `--output-dir` CLI argument. An
 existing directory is replaced only when it is empty or holds the results of a
 previous conversion; a directory with any other content is refused rather than
 overwritten. If not specified, the name is autogenerated in the format
-`<model_name>_to_<target>_<date>_<time>`.
+`<model_name>_to_<platform>_<date>_<time>`.
 
 > [!NOTE]
 > The conversion runs inside the container, so the paths it logs are
@@ -373,7 +374,7 @@ with:
 ```bash
 modelconverter cache info    # show cache location and disk usage
 modelconverter cache clean       # remove cache contents after confirmation
-modelconverter cache clean --yes # remove it non-interactively
+modelconverter cache clean -y    # remove it non-interactively
 ```
 
 Inputs are cached in full — directories included — and ModelConverter warns
@@ -437,15 +438,15 @@ You can run the built image either manually using the `docker run` command or us
   fixing output ownership for you):
 
   ```bash
-  modelconverter convert <target> --path <s3_url_or_path> [ config overrides ]
+  modelconverter convert <platform> --path <s3_url_or_path> [ config overrides ]
   ```
 
 - If using Docker Compose:
 
   ```bash
   # Used by the entrypoint to preserve ownership with rootful Docker.
   export HOST_UID=$(id -u) HOST_GID=$(id -g)
-  docker compose run <target> convert <target> ...
+  docker compose run <platform> convert <platform> ...
   ```
 
 - If using the `docker run` command (mount the cache read-write and a local
@@ -459,8 +460,8 @@ You can run the built image either manually using the `docker run` command or us
     -e AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY \
     -e AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID \
     -e AWS_S3_ENDPOINT_URL=$AWS_S3_ENDPOINT_URL \
-    luxonis/modelconverter-<target>:<tool-version>-latest \
-    convert <target> \
+    luxonis/modelconverter-<platform>:<tool-version>-latest \
+    convert <platform> \
     --path <s3_url_or_path> [ config overrides ]
   ```
 
@@ -482,8 +483,8 @@ Below is a table of common command-line options available when using the `modelc
 | -------------------------------------------------- | ----- | ------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------- |
 | `--path`                                           |       | PATH   | Path to the configuration file or NN Archive                                                                                                               |
 | `--to`                                             |       | CHOICE | Output format: `native` or `nn_archive`                                                                                                                    |
-| `--main-stage`                                     | `-m`  | TEXT   | Name of the stage with the main model                                                                                                                      |
-| `--tool-version`                                   |       | TEXT   | Version of the underlying conversion tools to use. Available options differ based on the target platform (RVC2, RVC3, RVC4, HAILO)                         |
+| `--main-stage`                                     |       | TEXT   | Name of the stage with the main model                                                                                                                      |
+| `--tool-version`                                   |       | TEXT   | Version of the underlying conversion tools to use. Available options differ based on the platform (RVC2, RVC3, RVC4, HAILO)                                |
 | `--image/docker-image`                             |       | TEXT   | Full Docker image name to use. If a tag is included, it is used as-is and overrides `--tool-version`, otherwise, the tag is derived from `--tool-version`. |
 | `--archive-preprocess` / `--no-archive-preprocess` |       | FLAG   | Add pre-processing to the NN archive instead of the model                                                                                                  |
 
@@ -588,7 +589,7 @@ output_path/
 
 ## Interactive Mode
 
-Run the container interactively without any post-target arguments:
+Run the container interactively without any arguments after the platform name:
 
 ```bash
 modelconverter shell rvc4
@@ -610,7 +611,7 @@ Image files will be loaded and converted to the format specified in the config.
 
 ## Inference
 
-A basic support for inference. To run the inference, use `modelconverter infer <target> <args>`.
+A basic support for inference. To run the inference, use `modelconverter infer <platform> <args>`.
 For usage instructions, see `modelconverter infer --help`.
 
 The input files must be provided in a specific directory structure.
@@ -700,7 +701,7 @@ To install the package with the benchmarking dependencies, use:
 pip install modelconv[bench]
 ```
 
-To run the benchmark, use `modelconverter benchmark <target> <args>`.
+To run the benchmark, use `modelconverter benchmark <platform> <args>`.
 
 For usage instructions, see `modelconverter benchmark --help`.
 
@@ -711,7 +712,7 @@ modelconverter benchmark rvc4 --model-path <path_to_model.tar.xz>
 ```
 
 The command prints a table with the benchmark results to the console and
-kptionally saves the results to a `.csv` file.
+optionally saves the results to a `.csv` file.
 
 > [!IMPORTANT]
 > **Device Connection Requirements for RVC4**: The device must be connected and accessible either using the [Android Debug Bridge (ADB)](https://developer.android.com/tools/adb) or via SSH for the benchmarking to work in the following cases:
@@ -734,7 +735,7 @@ kptionally saves the results to a `.csv` file.
 > - `--num-images`: The number of images to run through the model (default is 500). The total benchmark time will depend on the model size and complexity, as well as the device performance. Too many images may lead to an out-of-memory error, while too few images may lead to less accurate results. Adjust this parameter based on your specific situation and requirements.
 
 > [!NOTE]
-> Benchmark input support depends on the target and backend:
+> Benchmark input support depends on the platform and backend:
 >
 > - **RVC2**: `--model-path` can be a local `.blob`, an NN Archive (`.tar.xz`), or a model slug from [Luxonis HubAI](https://hub.luxonis.com/ai).
 > - **RVC4** with `--dai-benchmark` (default): `--model-path` can be an NN Archive (`.tar.xz`) or a model slug from [Luxonis HubAI](https://hub.luxonis.com/ai).
@@ -789,7 +790,7 @@ For other usage instructions run `modelconverter analyze --help`
 > [!NOTE]
 > It is important to ensure that you are using the correct ONNX model for comparison. Before converting to DLC, ModelConverter can modify the ONNX files by adding normalization layers or simplifying the graph. The ONNX model that is actually converted to DLC is typically located at `output/<output_dir>/intermediate_outputs/model_name-modified.onnx`
 >
-> For the DLC argument, you should use the final top-level DLC from the conversion output directory (for example `shared_with_container/outputs/model_name/model_name.dlc`), not the intermediate DLCs in `intermediate_outputs/`. This is because `modelconverter analyze` compares the ONNX reference model against the DLC that will actually run on the device, so the final deployable DLC is the correct default target. If you need to debug where differences are introduced during conversion, you can also analyze the intermediate `*-modified.dlc` or `*-modified-quantized.dlc` artifacts, but they represent earlier conversion stages rather than the final device-ready model.
+> For the DLC argument, you should use the final top-level DLC from the conversion output directory (for example `output/<output_dir>/model_name.dlc`), not the intermediate DLCs in `intermediate_outputs/`. This is because `modelconverter analyze` compares the ONNX reference model against the DLC that will actually run on the device, so the final deployable DLC is the correct default target. If you need to debug where differences are introduced during conversion, you can also analyze the intermediate `*-modified.dlc` or `*-modified-quantized.dlc` artifacts, but they represent earlier conversion stages rather than the final device-ready model.
 >
 > If the model has multiple inputs, make sure that each input directory has the same number of images. The tool alphabetically sorts images in each directory and assumes that images with the same index are used as one input.
 >
@@ -803,7 +804,7 @@ The tool creates two CSV files located in `output/analysis/model_name/`. One fil
 There is also a visualization option that displays all CSV files in `output/analysis/`. This offers a fast and easy way to inspect different model conversion parameters. For more usage instructions, run `modelconverter visualize --help`. To create the visualizations, simply run:
 
 ```bash
-modelconverter visualize <optional_path_to_dir>
+modelconverter visualize <path_to_dir>
 ```
 
 This command will create interactive pyplot scatter plots and cycle usage bar plots in a local web browser, as well as save both HTML files for easier access in the future.

configs/defaults.yaml

@@ -23,7 +23,7 @@ stages:
     # If specified, then the `calibration.path` must be provided.
     calibration:
       # Path to the calibration dataset. It can be either a local directory,
-      # an S3 url, or an LDF identificator in a form <dataset_name>:<split>.
+      # an S3 url, or an LDF identifier in a form <dataset_name>:<split>.
       # Example:
       # path: models/coco128
       # path: test_name:val

docker/entrypoint_common.sh

@@ -1,8 +1,8 @@
-# Shared part of every target entrypoint: run the requested command as a
+# Shared part of every platform entrypoint: run the requested command as a
 # signal-forwarding child, then hand the mounts back to the invoking host user.
 #
-# Sourced -- not executed -- by docker/<target>/entrypoint.sh after that
-# target's own environment setup, with the container's arguments intact. The
+# Sourced -- not executed -- by docker/<platform>/entrypoint.sh after that
+# platform's own environment setup, with the container's arguments intact. The
 # Dockerfiles copy it next to the entrypoint, at /app/entrypoint_common.sh.
 
 # Where the image puts the mounts. Only ever overridden by the tests, which

docker/hailo/Dockerfile

@@ -14,7 +14,7 @@ ENV IN_DOCKER=
 WORKDIR /app
 
 COPY --link requirements.txt requirements.txt
-COPY --link modelconverter/packages/hailo/requirements.txt requirements-hailo.txt
+COPY --link modelconverter/platforms/hailo/requirements.txt requirements-hailo.txt
 
 RUN <<EOF
 

docker/rvc2/Dockerfile

@@ -9,8 +9,8 @@ RUN <<EOF
 
     set -e
 
-    apt-get update
-    apt-get install -y  \
+    apt-get update -qq
+    apt-get install -y -qq \
         cmake           \
         unzip           \
         perl            \
@@ -136,7 +136,7 @@ COPY --link --from=base /opt/intel /opt/intel
 COPY --link --from=base /usr/local/lib /usr/local/lib
 
 COPY --link requirements.txt /app/requirements.txt
-COPY --link modelconverter/packages/rvc2/requirements.txt requirements-rvc2.txt
+COPY --link modelconverter/platforms/rvc2/requirements.txt requirements-rvc2.txt
 
 RUN <<EOF
 
@@ -159,8 +159,8 @@ ARG DEV=false
 COPY --link requirements-dev.txt /app/requirements-dev.txt
 COPY --link requirements-eval.txt /app/requirements-eval.txt
 RUN if [ "$DEV" = "true" ]; then \
-        apt-get update && \
-        apt-get install -y --no-install-recommends git && \
+        apt-get update -qq && \
+        apt-get install -y -qq --no-install-recommends git && \
         rm -rf /var/lib/apt/lists/* && \
         pip install --no-cache-dir -r /app/requirements-dev.txt codecov-cli && \
         pip install --no-cache-dir --no-deps -r /app/requirements-eval.txt; \

docker/rvc3/Dockerfile

@@ -6,8 +6,8 @@ RUN <<EOF
 
     set -e
 
-    apt-get update
-    apt-get install -y  \
+    apt-get update -qq
+    apt-get install -y -qq \
         cmake           \
         unzip           \
         perl            \
@@ -67,8 +67,8 @@ RUN <<EOF
 
     set -e
 
-    apt-get update
-    apt-get install -y --no-install-recommends git
+    apt-get update -qq
+    apt-get install -y -qq --no-install-recommends git
     rm -rf /var/lib/apt/lists/*
 
 EOF
@@ -104,7 +104,7 @@ COPY --link --from=base /usr/local/lib /usr/local/lib
 
 
 COPY --link requirements.txt requirements.txt
-COPY --link modelconverter/packages/rvc3/requirements.txt requirements-rvc3.txt
+COPY --link modelconverter/platforms/rvc3/requirements.txt requirements-rvc3.txt
 
 RUN <<EOF
 

docker/rvc4/Dockerfile

@@ -9,8 +9,8 @@ RUN <<EOF
 
     echo 'deb http://deb.debian.org/debian oldstable main' >> /etc/apt/sources.list
 
-    apt-get update
-    apt-get install -y --fix-missing \
+    apt-get update -qq
+    apt-get install -y -qq --fix-missing \
         cmake           \
         unzip           \
         perl            \
@@ -30,7 +30,7 @@ RUN <<EOF
 
     set -e
 
-    unzip snpe.zip -d /opt
+    unzip -q snpe.zip -d /opt
 
     # The SNPE archive from README.md contains an extra directory
     if [ -d /opt/qairt ]; then
@@ -56,7 +56,7 @@ RUN <<EOF
 EOF
 
 COPY --link requirements.txt requirements.txt
-COPY --link modelconverter/packages/rvc4/requirements.txt requirements-rvc4.txt
+COPY --link modelconverter/platforms/rvc4/requirements.txt requirements-rvc4.txt
 
 RUN pip install --upgrade pip setuptools wheel
 RUN pip install -r requirements.txt
@@ -112,8 +112,8 @@ ARG DEV=false
 COPY --link requirements-dev.txt /app/requirements-dev.txt
 COPY --link requirements-eval.txt /app/requirements-eval.txt
 RUN if [ "$DEV" = "true" ]; then \
-        apt-get update && \
-        apt-get install -y --no-install-recommends git && \
+        apt-get update -qq && \
+        apt-get install -y -qq --no-install-recommends git && \
         rm -rf /var/lib/apt/lists/* && \
         pip install --no-cache-dir -r /app/requirements-dev.txt codecov-cli && \
         pip install --no-cache-dir --no-deps -r /app/requirements-eval.txt; \