python_code stringlengths 0 4.04M | repo_name stringlengths 7 58 | file_path stringlengths 5 147 |
|---|---|---|
from world import World, SimpleMob, make_mob_opts, Opt
from utils import Player, Pos, Look, Item
from fake_agent import FakeAgent
from world_visualizer import Window, setup
from recorder import Recorder
import pyglet
import logging
if __name__ == "__main__":
log_formatter = logging.Formatter(
"%(asctime)s ... | craftassist-master | python/craftassist/test/visualize_scenario.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import shapes
from base_craftassist_test_case import BaseCraftassistTestCase
from typing import List
from mc_util import Block
from all_test_commands import * # noqa
def add_two_cubes(test):
triples = {"has_name": "cube", "has_shape": "cube"}
test.cub... | craftassist-master | python/craftassist/test/interactive_memory_explorer.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import os
import unittest
import shapes
from mc_util import euclid_dist
from base_craftassist_test_case import BaseCraftassistTestCase
class Opt:
pass
TTAD_MODEL_DIR = os.path.join(
os.path.dirname(__file__), "../models/semantic_parser/ttad_bert_upd... | craftassist-master | python/craftassist/test/test_with_model.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
# import sys
# import os
# BASE_DIR = os.path.join(os.path.dirname(__file__), "../../")
# sys.path.append(BASE_DIR)
import unittest
from unittest.mock import Mock
from build_utils import to_relative_pos
from base_agent.dialogue_objects import AwaitResponse
from... | craftassist-master | python/craftassist/test/base_craftassist_test_case.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import fileinput
from ttad_annotate import MAX_WORDS
print("command", *["word{}".format(i) for i in range(MAX_WORDS)], sep=",")
for line in fileinput.input():
command = line.replace(",", "").strip()
words = command.split()
print(command, *words, *... | craftassist-master | python/craftassist/ttad-annotate/make_input_csv.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
MAX_WORDS = 30
CSS_SCRIPT = """
<script>
var node = document.createElement('style');
"""
for i in range(MAX_WORDS):
CSS_SCRIPT += """
if (! "${{word{i}}}") {{
node.innerHTML += '.word{i} {{ display: none }} '
}}
""".format(
... | craftassist-master | python/craftassist/ttad-annotate/ttad_annotate.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import csv
import argparse
import json
from collections import defaultdict, Counter
import re
from ttad_annotate import MAX_WORDS
def process_result(full_d):
worker_id = full_d["WorkerId"]
d = with_prefix(full_d, "Answer.root.")
try:
acti... | craftassist-master | python/craftassist/ttad-annotate/process_results.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
from collections import Counter, defaultdict
import fileinput
import json
import os
right_answer_count = Counter()
wrong_answer_count = Counter()
# compile sets of allowed answers
allowed_answers = defaultdict(set)
command = None
with open(os.path.join(os.path... | craftassist-master | python/craftassist/ttad-annotate/qualtest.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import re
def render_q(q, parent_id, show=True):
"""Return a fieldset for the given question"""
assert "key" in q, "Missing key for q: {}".format(q)
q_id = "{}.{}".format(parent_id, q["key"])
r = ""
r += '<fieldset id="{}" style="display:{}... | craftassist-master | python/craftassist/ttad-annotate/render_flows.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
LOCATION_RADIO = [
{"text": "Not specified", "key": None},
{
"text": "Where the speaker is looking (e.g. 'that thing', 'over there')",
"key": "SPEAKER_LOOK",
},
{"text": "Where the speaker is standing (e.g. 'here', 'by me')", "key... | craftassist-master | python/craftassist/ttad-annotate/flows.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import csv
def any_two(a, b, c):
return a == b or a == c or b == c
with open("Batch_3449808_batch_results.csv", "r") as f:
r = csv.DictReader(f)
r = [d for d in r]
whittled = [
{k: v for k, v in d.items() if (k.startswith("Answer.") or k == ... | craftassist-master | python/craftassist/ttad-annotate/analyze_outputs.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import logging
from typing import Dict, Tuple, Any, Optional
from base_agent.dialogue_objects import DialogueObject
from mc_memory_nodes import VoxelObjectNode, RewardNode
from .interpreter_helper import interpret_reference_object, ErrorWithResponse
######FIXM... | craftassist-master | python/craftassist/dialogue_objects/put_memory_handler.py |
import random
import Levenshtein
import block_data
import minecraft_specs
from mc_util import IDM
# TODO FILTERS!
def get_block_type(s) -> IDM:
"""string -> (id, meta)
or {"has_x": span} -> (id, meta) """
name_to_bid = minecraft_specs.get_block_data()["name_to_bid"]
if type(s) is str:
s_aug =... | craftassist-master | python/craftassist/dialogue_objects/block_helpers.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import numpy as np
import rotation
import shapes
import heuristic_perception
from mc_util import pos_to_np, to_block_center, to_block_pos, ErrorWithResponse
def post_process_loc(loc, interpreter):
return to_block_pos(loc)
def compute_locations(
inte... | craftassist-master | python/craftassist/dialogue_objects/reference_object_helpers.py |
from .interpreter import Interpreter
from .get_memory_handler import GetMemoryHandler
from .put_memory_handler import PutMemoryHandler
__all__ = [GetMemoryHandler, Interpreter, PutMemoryHandler]
| craftassist-master | python/craftassist/dialogue_objects/__init__.py |
from base_agent.dialogue_objects import ConditionInterpreter
from mc_stop_condition import AgentAdjacentStopCondition
from .block_helpers import get_block_type
# this will become unnecessary with distance between
class MCConditionInterpreter(ConditionInterpreter):
def __init__(self):
super().__init__()
... | craftassist-master | python/craftassist/dialogue_objects/condition_helper.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
from typing import Dict, Tuple, Any, Optional, Sequence
from base_agent.dialogue_objects import DialogueObject
from .interpreter_helper import interpret_reference_object, ErrorWithResponse
from base_agent.memory_nodes import MemoryNode, ReferenceObjectNode
from... | craftassist-master | python/craftassist/dialogue_objects/get_memory_handler.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import logging
import numpy as np
import random
import heuristic_perception
from typing import Tuple, Dict, Any, Optional, List
from word2number.w2n import word_to_num
import sys
import os
BASE_AGENT_ROOT = os.path.join(os.path.dirname(__file__), "../..")
sys.... | craftassist-master | python/craftassist/dialogue_objects/interpreter.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import logging
import numpy as np
import math
import random
import re
from typing import cast, List, Tuple, Union, Optional, Dict
from base_agent.dialogue_objects import ConfirmReferenceObject, SPEAKERLOOK, tags_from_dict
import block_data
import heuristic_perc... | craftassist-master | python/craftassist/dialogue_objects/interpreter_helper.py |
import numpy as np
import rotation
from shape_transforms import (
scale,
thicker,
shrink_sample,
replace_by_blocktype,
replace_by_halfspace,
fill_flat,
hollow,
rotate,
maybe_convert_to_list,
maybe_convert_to_npy,
)
from .interpreter_helper import (
ErrorWithResponse,
inte... | craftassist-master | python/craftassist/dialogue_objects/modify_helpers.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import logging
from multiprocessing import Queue, Process
import sys
import os
from mc_memory_nodes import InstSegNode
from heuristic_perception import all_nearby_objects
from shapes import get_bounds
VISION_DIR = os.path.dirname(os.path.realpath(__file__))
CRA... | craftassist-master | python/craftassist/voxel_models/subcomponent_classifier.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import logging
import sys
import os
import torch
GEOSCORER_DIR = os.path.join(os.path.dirname(os.path.realpath(__file__)), "geoscorer/")
sys.path.append(GEOSCORER_DIR)
from geoscorer_wrapper import ContextSegmentMergerWrapper
from spatial_utils import shift_sp... | craftassist-master | python/craftassist/voxel_models/geoscorer.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
import matplotlib
import plotly.graph_objs as go
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import visdom
import pickle
import os
import torch
GEOSCORER_DIR = os.path.dirname(os.path.realpat... | craftassist-master | python/craftassist/voxel_models/plot_voxels.py |
import pickle
import argparse
import glob
import os
import numpy as np
from typing import List, Dict, Set, Tuple
from pathlib import Path
from copy import deepcopy
from tqdm import tqdm
def open_house_schematic(house_directory: Path) -> np.ndarray:
with open(Path(house_directory) / "schematic.npy", "rb") as fil... | craftassist-master | python/craftassist/voxel_models/make_seg_ds.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import os
import argparse
import sys
from data_loaders import InstSegData
import torch
import torch.nn as nn
import torch.optim as optim
import instseg_models as models
##################################################
# for debugging
########################... | craftassist-master | python/craftassist/voxel_models/instance_segmentation/train_instance_segmentation.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import pickle
import numpy as np
import torch
from torch.utils import data as tds
import random
def get_rectanguloid_mask(y, fat=1):
M = y.nonzero().max(0)[0].tolist()
m = y.nonzero().min(0)[0].tolist()
M = [min(M[i] + fat, y.shape[i] - 1) for i in... | craftassist-master | python/craftassist/voxel_models/instance_segmentation/data_loaders.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import numpy as np
import torch
import torch.nn as nn
from data_loaders import make_example_from_raw
def conv3x3x3(in_planes, out_planes, stride=1, bias=True):
"""3x3x3 convolution with padding"""
return nn.Conv3d(in_planes, out_planes, kernel_size=3, ... | craftassist-master | python/craftassist/voxel_models/instance_segmentation/instseg_models.py |
import random
import sys
import argparse
sys.path.append("/private/home/rebeccaqian/minecraft/python/craftassist/")
import minecraft_specs
from shape_helpers import SHAPE_NAMES
ID_DELIM = "^"
BLOCK_NAMES = [v for k, v in minecraft_specs.get_block_data()["bid_to_name"].items() if k[0] < 256]
COLOR_NAMES = [
"aqua"... | craftassist-master | python/craftassist/voxel_models/modify/st_templates.py |
if __name__ == "__main__":
import os
import sys
import torch
import argparse
import conv_models as models
from shape_transform_dataloader import ModifyData
from voxel_models.plot_voxels import SchematicPlotter, draw_rgb # noqa
import visdom
from tqdm import tqdm
parser = argpar... | craftassist-master | python/craftassist/voxel_models/modify/encode_many.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import torch
import torch.nn as nn
import numpy as np
import os
import pickle
THIS_DIR = os.path.dirname(os.path.realpath(__file__))
MC_DIR = os.path.join(THIS_DIR, "../../../../")
def model_filename_from_opts(opts, savedir=None, uid=None):
filler = "]["
... | craftassist-master | python/craftassist/voxel_models/modify/conv_models.py |
if __name__ == "__main__":
import os
import sys
import torch
import argparse
from shape_transform_dataloader import ModifyData
from tqdm import tqdm
parser = argparse.ArgumentParser()
parser.add_argument("--num_examples", type=int, default=1000000, help="num examples to build")
pars... | craftassist-master | python/craftassist/voxel_models/modify/build_static_dataset.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import os
print(os.getcwd())
import sys
sys.path = [""] + sys.path
from shape_transform_dataloader import ModifyData
import torch
# import torch.nn as nn
import torch.optim as optim
import conv_models as models
# predict allowed blocks
# quantize to nearest ... | craftassist-master | python/craftassist/voxel_models/modify/train_conv_model.py |
#########################################################
# TAKEN FROM https://github.com/LMescheder/GAN_stability/
#########################################################
# coding: utf-8
import torch
from torch.nn import functional as F
import torch.utils.data
import torch.utils.data.distributed
from torch import ... | craftassist-master | python/craftassist/voxel_models/modify/gan_trainer.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import os
from shape_transform_dataloader import ModifyData
import torch
from torch import distributions
# import torch.nn as nn
import torch.optim as optim
import conv_models as models
from gan_trainer import Trainer
# predict allowed blocks
# quantize to ne... | craftassist-master | python/craftassist/voxel_models/modify/train_gan_model.py |
from datetime import datetime
import argparse
import os
import stat
parser = argparse.ArgumentParser()
parser.add_argument("--sweep_config_path", default="", help="path to sweep config")
parser.add_argument("--sweep_scripts_output_dir", default="", help="where to put script")
parser.add_argument("--sweep_name", defaul... | craftassist-master | python/craftassist/voxel_models/modify/build_sweep_scripts.py |
import numpy as np
import random
import torch
from torch.utils import data as tds
import pickle
import shape_transforms
import shape_helpers as sh
from build_utils import blocks_list_to_npy
import minecraft_specs
from block_data import COLOR_BID_MAP
BLOCK_DATA = minecraft_specs.get_block_data()
# FIXME....
NEW_BLOCK_C... | craftassist-master | python/craftassist/voxel_models/modify/shape_transform_dataloader.py |
import torch
import torch.utils.data
import torchvision
from box_ops import box_cxcywh_to_xyxy
from datasets.lvis import LvisDetectionBase
from pycocotools import mask as coco_mask
from pycocotools.coco import COCO
def convert_to_coco_api(ds):
coco_ds = COCO()
# annotation IDs need to start at 1, not 0, see ... | craftassist-master | python/craftassist/voxel_models/detection-transformer/to_coco_api.py |
import random
import torch
import torchvision.transforms.functional as F
import torchvision.transforms as T
from torchvision.ops.misc import interpolate
from box_ops import box_xyxy_to_cxcywh
import PIL
def crop(image, target, region):
cropped_image = F.crop(image, *region)
target = target.copy()
i, j, h... | craftassist-master | python/craftassist/voxel_models/detection-transformer/transforms.py |
import argparse
import builtins
import datetime
import json
import os
import random
import time
from pathlib import Path
import numpy as np
import torch
from torch.utils.data import DataLoader, DistributedSampler
from torch.optim.lr_scheduler import StepLR, MultiStepLR
import datasets
import to_coco_api
import utils
... | craftassist-master | python/craftassist/voxel_models/detection-transformer/detection.py |
import torch
def box_area(boxes):
"""
Computes the area of a set of bounding boxes, which are specified by its
(x1, y1, z1, x2, y2, z2) coordinates.
Arguments:
boxes (Tensor[N, 6]): boxes for which the area will be computed. They
are expected to be in (x1, y1, z1, x2, y2, z2) forma... | craftassist-master | python/craftassist/voxel_models/detection-transformer/box_ops.py |
import argparse
import os
import uuid
from pathlib import Path
import detection
import submitit
def parse_args():
detection_parser = detection.get_args_parser()
parser = argparse.ArgumentParser("Submitit for detection", parents=[detection_parser])
parser.add_argument(
"--partition", default="lea... | craftassist-master | python/craftassist/voxel_models/detection-transformer/run_with_submitit.py |
import unittest
import torch
import box_ops
class Tester(unittest.TestCase):
def test_box_cxcywh_to_xyxy(self):
t = torch.rand(10, 4)
r = box_ops.box_xyxy_to_cxcywh(box_ops.box_cxcywh_to_xyxy(t))
self.assertTrue((t - r).abs().max() < 1e-5)
if __name__ == "__main__":
unittest.main()
| craftassist-master | python/craftassist/voxel_models/detection-transformer/test_box_ops.py |
import copy
import datetime
from collections import OrderedDict, defaultdict
import numpy as np
import torch
import torch._six
import pycocotools.mask as mask_util
import utils
from datasets.lvis import LVIS
#################################################################
# From LVIS, with following changes:
# ... | craftassist-master | python/craftassist/voxel_models/detection-transformer/lvis_eval.py |
import json
import numpy as np
import copy
import torch
import torch._six
from pycocotools.cocoeval import COCOeval
from pycocotools.coco import COCO
import pycocotools.mask as mask_util
from collections import defaultdict
import utils
class CocoEvaluator(object):
def __init__(self, coco_gt, iou_types):
... | craftassist-master | python/craftassist/voxel_models/detection-transformer/coco_eval.py |
import math
import sys
from typing import Iterable
import torch
import utils
from coco_eval import CocoEvaluator
from datasets.lvis import LVIS
from lvis_eval import LvisEvaluator
def train_one_epoch(
model: torch.nn.Module,
criterion: torch.nn.Module,
data_loader: Iterable,
optimizer: torch.optim.O... | craftassist-master | python/craftassist/voxel_models/detection-transformer/engine.py |
from __future__ import print_function
from collections import defaultdict, deque
import datetime
import pickle
import subprocess
import time
import torch
import torch.distributed as dist
import os
class SmoothedValue(object):
"""Track a series of values and provide access to smoothed values over a
window o... | craftassist-master | python/craftassist/voxel_models/detection-transformer/utils.py |
import torch
import pandas as pd
from pathlib import Path
import seaborn as sns
import matplotlib.pyplot as plt
def plot_logs(logs, fields=("class_error", "loss_bbox_unscaled", "mAP"), ewm_col=0):
dfs = [pd.read_json(Path(p) / "log.txt", lines=True) for p in logs]
fig, axs = plt.subplots(ncols=len(fields), f... | craftassist-master | python/craftassist/voxel_models/detection-transformer/plot_utils.py |
import bisect
from torch.utils.data.dataset import ConcatDataset as _ConcatDataset
class ConcatDataset(_ConcatDataset):
"""
Same as torch.utils.data.dataset.ConcatDataset, but exposes an extra
method
"""
def get_idxs(self, idx):
dataset_idx = bisect.bisect_right(self.cumulative_sizes, id... | craftassist-master | python/craftassist/voxel_models/detection-transformer/datasets/voc2007_2012.py |
import copy
import os
import torch
import torch.utils.data
import torchvision
import transforms as T
from pycocotools import mask as coco_mask
class FilterAndRemapCocoCategories(object):
def __init__(self, categories, remap=True):
self.categories = categories
self.remap = remap
def __call__... | craftassist-master | python/craftassist/voxel_models/detection-transformer/datasets/coco.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import pickle
import numpy as np
import torch
from torch.utils import data as tds
from copy import deepcopy
def underdirt(schematic, labels=None, max_shift=0, nothing_id=0):
# todo fancier dirt!
# FIXME!!!! label as ground where appropriate
shift =... | craftassist-master | python/craftassist/voxel_models/detection-transformer/datasets/house.py |
import importlib
def build_dataset(image_set, args):
# what a hack
mod = importlib.import_module("datasets." + args.dataset_file)
return mod.build(image_set, args)
| craftassist-master | python/craftassist/voxel_models/detection-transformer/datasets/__init__.py |
import json
import os
import time
from collections import defaultdict
import torchvision
from PIL import Image
import pycocotools.mask as mask_utils
import transforms as T
from .coco import ConvertCocoPolysToMask
def _isArrayLike(obj):
return hasattr(obj, "__iter__") and hasattr(obj, "__len__")
class LVIS:
... | craftassist-master | python/craftassist/voxel_models/detection-transformer/datasets/lvis.py |
from .voc import VOCDetection
from typing import Iterable
import to_coco_api
VOC_PATH = "/datasets01/VOC/060817/"
class VOCDetection2012(VOCDetection):
def __init__(self, image_set: str = "train", transforms: Iterable = None):
super(VOCDetection, self).__init__(
VOC_PATH, image_set=image_set... | craftassist-master | python/craftassist/voxel_models/detection-transformer/datasets/voc2012.py |
import json
import os
import numpy as np
import torch
from PIL import Image
import transforms as T
from box_ops import masks_to_boxes
from panopticapi.utils import rgb2id
class CocoPanoptic:
def __init__(self, img_folder, ann_folder, ann_file, transforms=None):
with open(ann_file, "r") as f:
... | craftassist-master | python/craftassist/voxel_models/detection-transformer/datasets/coco_panoptic.py |
import torchvision
from typing import Iterable
import to_coco_api
import transforms as T
VOC_PATH = "/checkpoint/szagoruyko/detection_transformer_shared/datasets01"
class VOCDetection(torchvision.datasets.VOCDetection):
def __init__(self, image_set: str = "train", transforms: Iterable = None):
super()._... | craftassist-master | python/craftassist/voxel_models/detection-transformer/datasets/voc.py |
import copy
import torch
import torch.nn.functional as F
from torch import nn
class Transformer(nn.Module):
def __init__(
self,
d_model=512,
nhead=8,
num_encoder_layers=6,
num_decoder_layers=6,
dim_feedforward=2048,
dropout=0.1,
activation="relu",
... | craftassist-master | python/craftassist/voxel_models/detection-transformer/models/detr.py |
from itertools import zip_longest
import torch
from scipy.optimize import linear_sum_assignment
from torch import nn
from box_ops import generalized_box_iou, box_cxcyczwhd_to_xyzxyz
def prepare_outputs(outputs):
"""
Change convention from outputs = {scores[N], boxes[N]}
into a [{scores[0], boxes[0]}, ..... | craftassist-master | python/craftassist/voxel_models/detection-transformer/models/matcher.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import numpy as np
import torch
import torch.nn as nn
def underdirt(schematic, labels=None, max_shift=0, nothing_id=0):
# todo fancier dirt!
# FIXME!!!! label as ground where appropriate
shift = torch.randint(max_shift + 1, (1,)).item()
if shif... | craftassist-master | python/craftassist/voxel_models/detection-transformer/models/semseg.py |
from collections import OrderedDict
import torch
import torch.nn.functional as F
import torchvision
from torch import nn
from torchvision.models._utils import IntermediateLayerGetter
from utils import NestedTensor
from .position_encoding import build_position_encoding
from .semseg import SemSegNet
class FrozenBatc... | craftassist-master | python/craftassist/voxel_models/detection-transformer/models/backbone.py |
import math
import torch
from torch import nn
class PositionEmbedding(nn.Module):
"""
This is a more standard version of the position embedding, very similar to the one
used by the Attention is all you need paper, generalized to work on images.
"""
def __init__(self, num_pos_feats=16, temperature... | craftassist-master | python/craftassist/voxel_models/detection-transformer/models/position_encoding.py |
import importlib
def build_model(args):
# what a hack
mod = importlib.import_module("models." + args.model_file)
return mod.build(args)
| craftassist-master | python/craftassist/voxel_models/detection-transformer/models/__init__.py |
import torch
import torch.nn.functional as F
from torch import nn
from torchvision.ops import misc as misc_ops
import box_ops
# TODO need to do proper packaging as this is getting confusing
from utils import NestedTensor, accuracy, get_world_size, is_dist_avail_and_initialized
from .backbone import build_backbone
fr... | craftassist-master | python/craftassist/voxel_models/detection-transformer/models/model_parallel.py |
from torch import nn
import torch.nn.functional as F
class MLP(nn.Module):
"""Simple feed forward fully connected, with some options
Parameters
----------
input_dim : int
Number of input channels
hidden_dim : int
Number of channels in the hidden layers
output_dim : int
... | craftassist-master | python/craftassist/voxel_models/detection-transformer/models/common.py |
"""
This file provides the definition of the convolutional heads used to predict masks
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from utils import NestedTensor
class DETRmask(nn.Module):
def __init__(self, detr, mask_head="v2"):
super().__init__()
self.detr = detr
... | craftassist-master | python/craftassist/voxel_models/detection-transformer/models/mask_heads.py |
"""
This file defines the basic loss functions that are used in the project
"""
import torch.nn.functional as F
def dice_loss(inputs, targets, num_boxes):
"""
Compute the DICE loss, similar to generalized IOU for masks
Args:
inputs: A float tensor of arbitrary shape.
The prediction... | craftassist-master | python/craftassist/voxel_models/detection-transformer/models/loss_utils.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import os
import sys
import visdom
import torch
VOXEL_MODELS_DIR = os.path.join(os.path.dirname(os.path.realpath(__file__)), "../")
sys.path.append(VOXEL_MODELS_DIR)
import plot_voxels as pv
import spatial_utils as su
import training_utils as tu
class Geoscore... | craftassist-master | python/craftassist/voxel_models/geoscorer/visualization_utils.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import torch
import torch.optim as optim
import torch.nn as nn
import directional_utils as du
def conv3x3x3(in_planes, out_planes, stride=1, bias=True):
"""3x3x3 convolution with padding"""
return nn.Conv3d(in_planes, out_planes, kernel_size=3, stride=... | craftassist-master | python/craftassist/voxel_models/geoscorer/models.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import torch
import time
import training_utils as tu
def train_epoch(tms, DL, opts):
l = 0
error = 0
count = 0
dlit = iter(DL)
tu.set_modules(tms, train=True)
for i in range(len(DL)):
b = dlit.next()
targets, scores = tu... | craftassist-master | python/craftassist/voxel_models/geoscorer/train_spatial_emb.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import json
dataset_config = {
"inst_dir": [
{"drop_perc": -1.0, "ground_type": None},
{"drop_perc": -1.0, "ground_type": "flat"},
],
"shape_dir": [
{"ground_type": "flat", "max_shift": None},
{"ground_type": "flat", ... | craftassist-master | python/craftassist/voxel_models/geoscorer/config_maker.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import argparse
from training_utils import get_context_segment_trainer_modules
from spatial_utils import index_to_coord
class ContextSegmentMergerWrapper(object):
"""
Wrapper for the geoscorer
"""
def __init__(self, models_path):
if mo... | craftassist-master | python/craftassist/voxel_models/geoscorer/geoscorer_wrapper.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import math
import os
import random
import pickle
import torch
import torch.utils.data
from collections import defaultdict
import spatial_utils as su
import directional_utils as du
def parse_instance_data(inst_data):
parsed_instance_data = []
for h in ... | craftassist-master | python/craftassist/voxel_models/geoscorer/inst_seg_dataset.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import numpy as np
import random
import torch
import torch.utils.data
from shape_dataset import SegmentContextShapeData, SegmentContextShapeDirData
from inst_seg_dataset import SegmentContextInstanceData
from autogen_dataset import SegmentContextGlueCubesData
... | craftassist-master | python/craftassist/voxel_models/geoscorer/combined_dataset.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import numpy as np
import random
import os
import sys
import argparse
import torch
import string
import json
from shutil import copyfile
from inspect import currentframe, getframeinfo
from datetime import datetime
import models
import combined_dataset as cd
""... | craftassist-master | python/craftassist/voxel_models/geoscorer/training_utils.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import numpy as np
import torch
import os
import sys
import random
CRAFTASSIST_DIR = os.path.join(os.path.dirname(os.path.realpath(__file__)), "../../")
TEST_DIR = os.path.join(CRAFTASSIST_DIR, "test/")
sys.path.append(CRAFTASSIST_DIR)
sys.path.append(TEST_DIR)
... | craftassist-master | python/craftassist/voxel_models/geoscorer/spatial_utils.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import numpy as np
import os
import sys
import random
import torch
import torch.utils.data
CRAFTASSIST_DIR = os.path.join(os.path.dirname(os.path.realpath(__file__)), "../../")
sys.path.append(CRAFTASSIST_DIR)
import shapes
import shape_helpers as sh
import sp... | craftassist-master | python/craftassist/voxel_models/geoscorer/shape_dataset.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import numpy as np
import torch
import random
def get_viewer_look(c_sl):
return torch.tensor([c_sl // 2 for _ in range(3)])
def get_random_viewer_info(sl):
viewer_pos = torch.tensor(np.random.randint(0, sl, 3))
viewer_look = get_viewer_look(sl)
... | craftassist-master | python/craftassist/voxel_models/geoscorer/directional_utils.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import numpy as np
import random
import torch
import torch.utils.data
import spatial_utils as su
import directional_utils as du
def get_glue_cubes_direction_target_coord(viewer_pos, dir_vec, cube_size, origin_cont, c_sl):
# Note: c_sizes and s_sizes are th... | craftassist-master | python/craftassist/voxel_models/geoscorer/autogen_dataset.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import numpy as np
import torch
import pickle
import torch.nn as nn
from data_loaders import make_example_from_raw
class SemSegNet(nn.Module):
def __init__(self, opts, classes=None):
super(SemSegNet, self).__init__()
if opts.load:
... | craftassist-master | python/craftassist/voxel_models/semantic_segmentation/semseg_models.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import pickle
import numpy as np
import torch
from torch.utils import data as tds
from copy import deepcopy
def underdirt(schematic, labels=None, max_shift=0, nothing_id=0):
# todo fancier dirt!
# FIXME!!!! label as ground where appropriate
shift =... | craftassist-master | python/craftassist/voxel_models/semantic_segmentation/data_loaders.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import os
import argparse
import sys
from tqdm import tqdm
from data_loaders import SemSegData
import torch
import torch.nn as nn
from torch.utils.data import DataLoader
import torch.optim as optim
import semseg_models as models
from pathlib import Path
#####... | craftassist-master | python/craftassist/voxel_models/semantic_segmentation/train_semantic_segmentation.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import struct
class Decoder:
def __init__(self, fp):
self.fp = fp
self.count = 0
def readByte(self):
return self.readStructFmt(">b")
def readUByte(self):
return self.readStructFmt(">B")
def readShort(self):
... | craftassist-master | python/logging_plugin/decoder.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
BLOCK_SPREAD = 1
# BLOCK_TO_PICKUPS = 2
# BREWING_COMPLETED = 3
# BREWING_COMPLETING = 4
CHAT = 5
CHUNK_AVAILABLE = 6
# CHUNK_GENERATED = 7
# CHUNK_GENERATING = 8
# CHUNK_UNLOADED = 9
# CHUNK_UNLOADING = 10
COLLECTING_PICKUP = 11
# CRAFTING_NO_RECIPE = 12
# DISC... | craftassist-master | python/logging_plugin/hooks.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import numpy as np
from scipy.misc import imread
INF_DEPTH = 100
def plot(blockpath, plt, imgpath=None, depthpath=None, vis=None, out_path=None, size=None):
block = np.fromfile(blockpath, np.uint8)
if size is None:
width = height = int((len(b... | craftassist-master | python/logging_plugin/plot_vision.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import binascii
from decoder import Decoder
import hooks
import util
# https://api.cuberite.org/Globals.html
dtAttack = 0
etMob = 4
class BaseLogReader:
def __init__(self, logdir):
self.logdir = logdir
fp = open(logdir + "/logging.bin", ... | craftassist-master | python/logging_plugin/base_log_reader.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import hashlib
import hooks
HOOK_MAP = {getattr(hooks, h): h for h in dir(hooks) if not h.startswith("__")}
def get_hook_name(hook_id):
return HOOK_MAP[hook_id]
def get_hashes(path):
with open(path, "rb") as f:
contents = f.read()
raw_h... | craftassist-master | python/logging_plugin/util.py |
import os.path
import sys
sys.path.insert(0, os.path.dirname(__file__))
| craftassist-master | python/logging_plugin/__init__.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
from base_log_reader import BaseLogReader
import hooks
import util
class PrintLogReader(BaseLogReader):
def __init__(self, *args, ignore_hooks=[], only_hooks=[], **kwargs):
super().__init__(*args, **kwargs)
assert (
len(only_h... | craftassist-master | python/logging_plugin/print_log_reader.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
from matplotlib import pyplot as plt
import glob
import matplotlib.animation as animation
import numpy as np
import os.path
import time
FFMpegWriter = animation.writers["ffmpeg"]
def render_video(ob_dir, outfile, dpi=100, max_depth=48):
writer = FFMpegWri... | craftassist-master | python/logging_plugin/video.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import math
from base_log_reader import BaseLogReader
def to_discrete(pos):
return tuple(math.floor(p) for p in pos)
class PrintLogReader(BaseLogReader):
def on_player_spawned(self, tick, buf_start, eid, name, pos, look):
print("[{}] Player ... | craftassist-master | python/logging_plugin/discrete_move_log_reader.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import os
import shutil
import subprocess
import tempfile
import sys
python_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.insert(0, python_dir)
import edit_cuberite_config
from repo import repo_home
from base_log_reader import Ba... | craftassist-master | python/logging_plugin/recover_initial_blockmap.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import argparse
import logging
import os
import subprocess
import numpy as np
import sys
python_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.insert(0, python_dir)
from cuberite_process import CuberiteProcess
from repo import re... | craftassist-master | python/render_vision_dataset/render_3x.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import argparse
import glob
import logging
import os
import subprocess
import random
import numpy as np
import sys
python_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.insert(0, python_dir)
from cuberite_process import CuberiteP... | craftassist-master | python/render_vision_dataset/render_one_block_change.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import argparse
import logging
import os
import subprocess
import random
import cv2
import numpy as np
import sys
python_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.insert(0, python_dir)
from cuberite_process import CuberitePr... | craftassist-master | python/render_vision_dataset/render_verify_pixel2block.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import argparse
import logging
import os
import subprocess
import random
from sklearn.neighbors import KDTree
import cv2
import pickle
import numpy as np
import sys
python_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.insert(0, py... | craftassist-master | python/render_vision_dataset/render_schematic_with_pixel2block-color.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import argparse
import glob
import logging
import os
import subprocess
import random
import struct
import numpy as np
import sys
python_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.insert(0, python_dir)
from cuberite_process impo... | craftassist-master | python/render_vision_dataset/render_schematic_with_pixel2block.py |
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
#!/usr/bin/python
import os
import sys
if __name__ == "__main__":
npy_files = sys.argv[1]
port = int(sys.argv[2])
home = os.path.expanduser("~")
## for each house, we render four different angles
with open(npy_files, "r") as f:
lin... | craftassist-master | python/render_vision_dataset/render_script.py |
import os
import threading
from flask import Flask
import socketio
from flask_cors import cross_origin, CORS
import mcevent
app = None
def _dashboard_thread(web_root, ip, port):
global app
root_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../"))
static_folder = os.path.join(root_dir,... | craftassist-master | python/dashboard/__init__.py |
import threading
import weakref
def _make_id(target):
if hasattr(target, "__func__"):
return (id(target.__self__), id(target.__func__))
return id(target)
NONE_ID = _make_id(None)
# A marker for caching
NO_RECEIVERS = object()
class Signal:
"""
Base class for all signals
Internal attr... | craftassist-master | python/mcevent/dispatcher.py |
"""Multi-consumer multi-producer dispatching mechanism
Originally based on pydispatch (BSD) https://pypi.org/project/PyDispatcher/2.0.1/
See license.txt for original license.
Heavily modified for Django's purposes.
"""
from .dispatcher import Signal, receiver # NOQA
dispatch = Signal() # NOQA
class SocketIOMock... | craftassist-master | python/mcevent/__init__.py |
import argparse
import glob
import json
import os
import shutil
import subprocess
import uuid
# LOOK ANGLES
# -----------------
# - chunky definitions of yaw/pitch differ from minecraft's:
# -> chunky_pitch = minecraft_pitch - 90
# -> chunk_yaw = 90 - minecraft_yaw
# - chunky uses radians, minecraft uses degrees
... | craftassist-master | python/minecraft_render/render.py |
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