> ## Documentation Index
> Fetch the complete documentation index at: https://docs.generalrobotics.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# GraspGen

> 6-DoF grasp generation from depth and segmentation

Generate 6-DoF grasp poses from depth images and segmentation masks (or directly from a point cloud).

## Parameters

<ParamField body="depth_image" type="str | PIL.Image | np.ndarray">
  Depth image. Required if `point_cloud` is not provided.
</ParamField>

<ParamField body="seg_image" type="str | PIL.Image | np.ndarray">
  Segmentation mask. Required if `point_cloud` is not provided.
</ParamField>

<ParamField body="camera_intrinsics" type="str | np.ndarray">
  3x3 camera intrinsics matrix. Required if `point_cloud` is not provided.
</ParamField>

<ParamField body="point_cloud" type="str | np.ndarray | List">
  Optional `(N, 3)` point cloud. When provided, `depth_image`/`seg_image`/`camera_intrinsics` are ignored.
</ParamField>

<ParamField body="aux_args" type="Dict[str, Any]">
  Auxiliary parameters:

  * `num_grasps` — Number of grasps to generate
  * `gripper_config` — Gripper type. Supported values: `"robotiq_2f_140"` (default), `"single_suction_cup_30mm"`, `"franka_panda"`
  * `camera_extrinsics` — 4x4 camera extrinsics matrix
</ParamField>

<ParamField body="timeout" type="float | None">
  Optional HTTP timeout.
</ParamField>

## Returns

`dict` with keys:

* `grasps` — Array of 4x4 grasp poses `(N, 4, 4)`
* `confidence` — Array of confidence scores `(N,)`
* `latency_ms` — Optional server-reported latency

## Example

```python theme={null}
from grid_cortex_client import CortexClient
import numpy as np
from PIL import Image

client = CortexClient()
K = np.eye(3)
aux = {"num_grasps": 128, "gripper_config": "single_suction_cup_30mm", "camera_extrinsics": np.eye(4)}
depth_image = np.load("depth.npy")
seg_image = np.array(Image.open("seg.png"))

res = client.run(
    model_id="graspgen",
    depth_image=depth_image,
    seg_image=seg_image,
    camera_intrinsics=K,
    aux_args=aux,
)
print(res["grasps"].shape)  # (N, 4, 4)
```