python3Packages.{bpycv,zcs,boxx,fn}: remove (#380443)

- The behavior of the `networking.nat.externalIP` and `networking.nat.externalIPv6` options has been changed. `networking.nat.forwardPorts` now only forwards packets destined for the specified IP addresses.

- `python3Packages.bpycv` has been removed due to being incompatible with Blender 4 and unmaintained.

- `python3Packages.jaeger-client` was removed because it was deprecated upstream. [OpenTelemetry](https://opentelemetry.io) is the recommended replacement.

- `nodePackages.meshcommander` has been removed, as the package was deprecated by Intel.

{

  lib,

  buildPythonPackage,

  fetchPypi,

  imageio,

  matplotlib,

  numpy,

  pandas,

  pyopengl,

  scikit-image,

  seaborn,

  snakeviz,

}:

buildPythonPackage rec {

  pname = "boxx";

  version = "0.10.14";

  format = "setuptools";

  src = fetchPypi {

    inherit pname version;

    hash = "sha256-unGnmPksEuqFXHTWJkj9Gv2G/qPDgT6AZXYiG2gtkEA=";

  };

  propagatedBuildInputs = [

    imageio

    matplotlib

    numpy

    pandas

    pyopengl

    scikit-image

    seaborn

    snakeviz

  ];

  pythonImportsCheck = [ "boxx" ];

  meta = with lib; {

    description = "Tool-box for efficient build and debug for Scientific Computing and Computer Vision";

    homepage = "https://github.com/DIYer22/boxx";

    license = licenses.mit;

    maintainers = with maintainers; [ lucasew ];

  };

}

# based on https://github.com/DIYer22/bpycv/blob/c576e01622d87eb3534f73bf1a5686bd2463de97/example/ycb_demo.py

import bpy

import bpycv

import os

import glob

import random

from pathlib import Path

example_data_dir = os.environ['BPY_EXAMPLE_DATA']

out_dir = Path(os.environ['out'])

out_dir.mkdir(parents=True, exist_ok=True)

models = sorted(glob.glob(os.path.join(example_data_dir, "model", "*", "*.obj")))

cat_id_to_model_path = dict(enumerate(sorted(models), 1))

distractors = sorted(glob.glob(os.path.join(example_data_dir, "distractor", "*.obj")))

bpycv.clear_all()

bpy.context.scene.frame_set(1)

bpy.context.scene.render.engine = "CYCLES"

bpy.context.scene.cycles.samples = 32

bpy.context.scene.render.resolution_y = 1024

bpy.context.scene.render.resolution_x = 1024

bpy.context.view_layer.cycles.denoising_store_passes = False

# A transparency stage for holding rigid body

stage = bpycv.add_stage(transparency=True)

bpycv.set_cam_pose(cam_radius=1, cam_deg=45)

hdri_dir = os.path.join(example_data_dir, "background_and_light")

hdri_manager = bpycv.HdriManager(

    hdri_dir=hdri_dir, download=False

)  # if download is True, will auto download .hdr file from HDRI Haven

hdri_path = hdri_manager.sample()

bpycv.load_hdri_world(hdri_path, random_rotate_z=True)

# load 5 objects

for index in range(5):

    cat_id = random.choice(list(cat_id_to_model_path))

    model_path = cat_id_to_model_path[cat_id]

    obj = bpycv.load_obj(model_path)

    obj.location = (

        random.uniform(-0.2, 0.2),

        random.uniform(-0.2, 0.2),

        random.uniform(0.1, 0.3),

    )

    obj.rotation_euler = [random.uniform(-3.1415, 3.1415) for _ in range(3)]

    # set each instance a unique inst_id, which is used to generate instance annotation.

    obj["inst_id"] = cat_id * 1000 + index

    with bpycv.activate_obj(obj):

        bpy.ops.rigidbody.object_add()

# load 6 distractors

for index in range(6):

    distractor_path = random.choice(distractors)

    target_size = random.uniform(0.1, 0.3)

    distractor = bpycv.load_distractor(distractor_path, target_size=target_size)

    distractor.location = (

        random.uniform(-0.2, 0.2),

        random.uniform(-0.2, 0.2),

        random.uniform(0.1, 0.3),

    )

    distractor.rotation_euler = [random.uniform(-3.1415, 3.1415) for _ in range(3)]

    with bpycv.activate_obj(distractor):

        bpy.ops.rigidbody.object_add()

# run pyhsic engine for 20 frames

for i in range(20):

    bpy.context.scene.frame_set(bpy.context.scene.frame_current + 1)

# render image, instance annoatation and depth in one line code

result = bpycv.render_data()

result.save(dataset_dir=str(out_dir.resolve()), fname="0", save_blend=True)

print(f'Save to "{out_dir}"')

print(f'Open "{out_dir}/vis/" to see visualize result.')

{

  stdenv,

  lib,

  beautifulsoup4,

  blender,

  boxx,

  buildPythonPackage,

  fetchFromGitHub,

  fetchPypi,

  minexr,

  opencv-python,

  requests,

  runCommand,

  zcs,

}:

buildPythonPackage rec {

  pname = "bpycv";

  version = "0.4.0";

  format = "setuptools";

  src = fetchPypi {

    inherit pname version;

    hash = "sha256-qqNGemDB0aagCXjrECuh6kLksf+KujPejpnXVqFG8GY=";

  };

  propagatedBuildInputs = [

    beautifulsoup4

    minexr

    zcs

    requests

    opencv-python

    boxx

  ];

  # pythonImportsCheck = [ "bpycv" ]; # this import depends on bpy that is only available inside blender

  doCheck = false;

  passthru.tests = {

    render =

      runCommand "bpycv-render-test"

        {

          BPY_EXAMPLE_DATA = fetchFromGitHub {

            owner = "DIYer22";

            repo = "bpycv_example_data";

            hash = "sha256-dGb6KvbXTGTu5f4AqhA+i4AwTqBoR5SdXk0vsMEcD3Q=";

            rev = "6ce0e65c107d572011394da16ffdf851e988dbb4";

          };

        }

        ''

          ${blender.withPackages (ps: [ ps.bpycv ])}/bin/blender-wrapped -b -P ${./bpycv-test.py}

        '';

  };

  meta = with lib; {

    description = "Computer vision utils for Blender";

    homepage = "https://github.com/DIYer22/bpycv";

    license = licenses.mit;

    maintainers = [ maintainers.lucasew ];

    inherit (blender.meta) platforms;

  };

}

{

  lib,

  buildPythonPackage,

  fetchpatch,

  fetchPypi,

  pythonAtLeast,

}:

buildPythonPackage rec {

  pname = "fn";

  version = "0.4.3";

  format = "setuptools";

  # Python 3.11 changed the API of the `inspect` module and fn was never

  # updated to adapt; last commit was in 2014.

  disabled = pythonAtLeast "3.11";

  src = fetchPypi {

    inherit pname version;

    sha256 = "1nmsjmn8jb4gp22ksx0j0hhdf4y0zm8rjykyy2i6flzimg6q1kgq";

  };

  patches = [

    (fetchpatch {

      url = "https://github.com/kachayev/fn.py/commit/a54fc0bd8aeae277de2db726131d249ce607c0c2.patch";

      hash = "sha256-I0ZISOgVibsc1k7gwSfeW6qV9PspQqdaHlRLr/IusQ8=";

      excludes = [ "fn/monad.py" ];

    })

  ];

  meta = with lib; {

    description = ''

      Functional programming in Python: implementation of missing

      features to enjoy FP

    '';

    homepage = "https://github.com/kachayev/fn.py";

    license = licenses.asl20;

  };

}