Install AnyGrasp

You can follow this blog post for detailed instructions on installing AnyGrasp.

Below is an example script used to deploy AnyGrasp as a server:

anygrasp_sdk/grasp_detection/server.py

import argparse
import os

parser = argparse.ArgumentParser()
parser.add_argument("-p", "--port", type=str)
parser.add_argument("-d", "--device", type=str)
args = parser.parse_args()

os.environ["CUDA_VISIBLE_DEVICES"] = args.device

import numpy as np
import open3d as o3d
from flask import Flask, request, jsonify
import torch
import gc

from gsnet import AnyGrasp
from graspnetAPI import GraspGroup

VISUALIZED = False
app = Flask(__name__)

class Configs:
    checkpoint_path = "log/checkpoint_detection.tar"
    max_gripper_width = 0.1
    gripper_height = 0.03
    top_down_grasp = True
    debug = True

cfgs = Configs()

print("Loading AnyGrasp model into memory...")
anygrasp = AnyGrasp(cfgs)
anygrasp.load_net()
print("Model loaded successfully.")

def handle_grasp(data):
    try:
        dense_mode = data.get("dense_mode", False)
        print(dense_mode)
        colors = np.array(data["colors"])
        depths = np.array(data["depths"])
        fx, fy = float(data["fx"]), float(data["fy"])
        cx, cy = float(data["cx"]), float(data["cy"])
        scale = float(data["scale"])

        intrinsic = o3d.camera.PinholeCameraIntrinsic()
        intrinsic.set_intrinsics(
            width=colors.shape[1], height=colors.shape[0], fx=fx, fy=fy, cx=cx, cy=cy
        )
        colors = colors.astype(np.float32) / 255.0
        xmap, ymap = np.arange(depths.shape[1]), np.arange(depths.shape[0])
        xmap, ymap = np.meshgrid(xmap, ymap)
        points_z = depths / scale
        points_x = (xmap - cx) / fx * points_z
        points_y = (ymap - cy) / fy * points_z

        mask = (points_z > -2.0) & (points_z <= 2.0)
        points = np.stack([points_x, points_y, points_z], axis=-1)
        points = points[mask].astype(np.float32)
        colors = colors[mask].astype(np.float32)

        lims = [-20.0, 20.0, -20.0, 20.0, -2.0, 2.0]

        with torch.no_grad():
            gg, cloud = anygrasp.get_grasp(
                points,
                colors,
                lims=lims,
                apply_object_mask=True,
                dense_grasp=dense_mode,
                collision_detection=True,
            )

        if gg is None or len(gg) == 0:
            return None

        gg = gg.nms().sort_by_score()
        gg_pick = gg[:]  # top-K or all

        if VISUALIZED:
            trans_mat = np.array([[1, 0, 0, 0],
                                  [0, 1, 0, 0],
                                  [0, 0, -1, 0],
                                  [0, 0, 0, 1]])
            cloud.transform(trans_mat)
            grippers = gg_pick.to_open3d_geometry_list()
            for gripper in grippers:
                gripper.transform(trans_mat)
            o3d.visualization.draw_geometries([*grippers, cloud])

        return gg_pick
    finally:
        gc.collect()
        torch.cuda.empty_cache()


@app.route("/process", methods=["POST"])
def process_data():
    try:
        data = request.get_json()
        data["colors"] = np.array(data["colors"], dtype=np.uint8)
        data["depths"] = np.array(data["depths"], dtype=np.uint16)
        result = handle_grasp(data)

        if result is None:
            return jsonify({"message": "No Grasp detected!"}), 400

        grasp_list = []
        for grasp in result:
            grasp_list.append({
                "translation": grasp.translation.tolist(),
                "rotation_matrix": grasp.rotation_matrix.tolist(),
                "depth": grasp.depth,
                "score": grasp.score,
            })

        return jsonify({"grasp_groups": grasp_list}), 200

    except Exception as e:
        print("Error:", e)
        return jsonify({"error": str(e)}), 500


if __name__ == "__main__":
    app.run(host="0.0.0.0", port=int(args.port), threaded=False)

You can launch the AnyGrasp server with the following command:

python anygrasp_sdk/grasp_detection/server.py -p 5000 -d 0

• -p specifies the port that the server will listen on.
• -d specifies which GPU to use.

You can also expose this port within your local network, allowing multiple servers to access the same AnyGrasp server instance simultaneously.

You can edit default section in configs/miscs/anygrasp.yml to change the server configuration to your server address and port.