> This is the documentation for LibreYOLO 1.5.0. Current version: https://www.libreyolo.com/docs/cli/utilities # libreyolo utilities Nine commands that report or inspect rather than compute. They print environment facts, the model and format inventory, resolved defaults, checkpoint details, and they build and query a face gallery. Verified against LibreYOLO v1.5.0. ## Synopsis ```bash libreyolo [key=value ...] ``` Arguments are `key=value` pairs, and POSIX form works too, so `model=x` and `--model x` are the same argument. Every command here writes results to stdout and accepts `json=true` and `quiet=true`. The root command carries one flag of its own, `libreyolo --version`, which prints the version string and exits. That is a smaller output than the `version` command below. ## version Prints the LibreYOLO version plus the Python, torch and CUDA versions it is running against. ```bash libreyolo version ``` | Argument | Default | Meaning | |---|---|---| | `json` | `false` | JSON output to stdout | | `quiet` | `false` | Suppress stderr | ## checks Prints the environment in more detail: Python, torch, CUDA, cuDNN, every detected GPU with its name and memory, and the installed version of each optional package the export paths use. ```bash libreyolo checks ``` | Argument | Default | Meaning | |---|---|---| | `json` | `false` | JSON output to stdout | | `quiet` | `false` | Suppress stderr | The package list covers `onnx`, `onnxruntime`, `tensorrt`, `openvino`, `paddlepaddle`, `x2paddle`, `mnn`, `ncnn`, `onnx2tf`, `ai-edge-litert`, `transformers` and `scipy`. A package that is not installed reports as such rather than being omitted, so a failed export can be traced to a missing dependency from this one command. ## models Lists every model family with its tasks, sizes, the CLI names that resolve to its checkpoints, and each size's input resolution. ```bash libreyolo models ``` | Argument | Default | Meaning | |---|---|---| | `json` | `false` | JSON output to stdout | | `quiet` | `false` | Suppress stderr | A family whose optional dependency is not installed is listed as unavailable together with the `pip install` line that would make it available. The CLI names are what `model=` accepts as a shorthand: `yolox-s` resolves to `LibreYOLOXs.pt`, and non-detection tasks carry their task suffix. ## formats Lists the export formats the installed environment can produce, with each format's file extension and whether it supports FP16 and INT8. ```bash libreyolo formats [family=] [task=] ``` | Argument | Default | Meaning | |---|---|---| | `family` | | Show tiers for one model family. `model=` is accepted as the same option | | `task` | | Canonical model task. The family's default task when unset | | `json` | `false` | JSON output to stdout | | `quiet` | `false` | Suppress stderr | Without `family`, the output is the format inventory alone. With it, each format gains the support tier for that family and task, the reason behind the tier, and any constraint attached to it. An unknown family, or a task the family does not support, is a usage error. Format aliases appear next to their canonical name: `engine` for `tensorrt`, `litert` for `tflite`. ## cfg Prints the resolved default configuration: the train defaults, the validation defaults, the prediction defaults, and the per-family overrides. ```bash libreyolo cfg ``` | Argument | Default | Meaning | |---|---|---| | `json` | `false` | JSON output to stdout | | `quiet` | `false` | Suppress stderr | The values are read from the configuration dataclasses, not from a copy, so this is the authority on what a training run will use when you do not pass an argument. `family_overrides` is the section that answers why a family trained at settings you did not ask for. See [`libreyolo train`](/docs/v1.5.0/cli/train) for how those overrides are applied. ## info Loads a model on the CPU and reports its family, size, parameter count, classes, and the export tier for each format. ```bash libreyolo info model= ``` | Argument | Default | Meaning | |---|---|---| | `model` | | Model name or path to weights. Required | | `detailed` | `false` | Include per-parameter details | | `json` | `false` | JSON output to stdout | | `quiet` | `false` | Suppress stderr | ## metadata Reads a checkpoint's metadata without constructing a model, and validates it against the LibreYOLO checkpoint schema. ```bash libreyolo metadata path= ``` | Argument | Default | Meaning | |---|---|---| | `path` | | Path to a `.pt` checkpoint. Required | | `json` | `false` | JSON output to stdout | | `quiet` | `false` | Suppress stderr | Large tensor-bearing entries are summarized rather than printed, so the output stays readable on a full training checkpoint. A checkpoint that does not exist exits with `checkpoint_not_found`, and one whose metadata fails validation prints the errors and exits `1`. ## enroll Builds a face gallery from a folder-per-person tree, so later predictions can name the faces they find. ```bash libreyolo enroll model= source= gallery= ``` | Argument | Default | Meaning | |---|---|---| | `model` | | Face-embedding model, path or name. Required | | `source` | | Folder-per-person tree, `source//*.jpg`. Required | | `gallery` | | Output gallery file `.npz`. Extended in place if it exists. Required | | `face_detector` | | Face detector: a YuNet `.onnx` or a LibreYOLO detector. The family's default detector when unset | | `device` | `auto` | Device: `0`, `cpu`, `mps`, `auto` | | `json` | `false` | JSON output to stdout | | `quiet` | `false` | Suppress stderr | ```bash # people/ holds one folder per identity; the folder name becomes the identity. libreyolo enroll model=librefacerec-l.onnx source=people/ gallery=people.npz ``` The subfolder name is the identity. A reference image with no detectable face is skipped with a line on stderr and the rest continue; a source with no identity subfolders, or one where no face was found at all, is an error. Pass the resulting file to [`libreyolo predict`](/docs/v1.5.0/cli/predict) as `gallery=people.npz` to have detections carry an identity and a match score. ## compare Reports the cosine similarity between two face images and whether it clears the same-identity threshold. ```bash libreyolo compare model= source= source2= ``` | Argument | Default | Meaning | |---|---|---| | `model` | | Face-embedding model, path or name. Required | | `source` | | First image. Required | | `source2` | | Second image to compare against. Required | | `face_detector` | | Face detector: a YuNet `.onnx` or a LibreYOLO detector | | `threshold` | `0.4` | Cosine-similarity threshold for the same-identity decision | | `device` | `auto` | Device: `0`, `cpu`, `mps`, `auto` | | `json` | `false` | JSON output to stdout | | `quiet` | `false` | Suppress stderr | ```bash libreyolo compare model=librefacerec-l.onnx source=a.jpg source2=b.jpg ``` `libreyolo verify` is registered as a second name for this command and takes the same arguments. Both `compare` and `enroll` need a model whose task is face embedding. Anything else exits with `config_unsupported`. Local image paths and `http` or `https` URLs are both accepted as sources. ## Examples **Environment** ```bash libreyolo version libreyolo checks ``` **What is available** ```bash libreyolo models libreyolo formats family=yolo9 task=detect ``` **Inspect a checkpoint** ```bash libreyolo info model=LibreYOLO9s.pt libreyolo metadata path=weights/LibreYOLO9s.pt ``` ## Notes stdout carries the result; progress and warnings go to stderr. `json=true` prints one object with `schema_version`, which is the form to read from a script. Text output is the default and is meant to be read by a person. Exit codes follow the same map as the rest of the CLI: `0` on success, `2` for a usage or configuration error, `3` when a source cannot be found, `4` when a model or checkpoint cannot be loaded, and `1` for other runtime failures. Related: [`libreyolo doctor`](/docs/v1.5.0/cli/doctor), which is the dataset-side inspection command, and [`libreyolo profile`](/docs/v1.5.0/cli/profile), the performance-side one.