YodaEmbedding

import numpy as np
import numba


@numba.jit(nopython=True)
def estimate_flow_blockmatching(prev_img, next_img, block_size, search_window):
    """Estimate motion vectors using block matching.

    Args:
        prev_img: previous frame

YodaEmbedding

# example.py

from common import setup
import torch.nn.functional as F

args, model, data_module = setup()
test_data_loader = data_module.test_dataloader()

for batch in iter(test_data_loader):
    inputs, targets = batch

YodaEmbedding

CompressAI Pytorch Lightning example

YodaEmbedding

"""
Repair ModelNet40.

Some of the files in ModelNet40 are broken, e.g.,

.. code-block:: bash

    $ head -n 1 ModelNet40/chair/train/chair_0856.off
    OFF6586 5534 0

YodaEmbedding

{
  "0": "0",
  "1": "1",
  "2": "2",
  "3": "3",
  "4": "4",
  "5": "5",
  "6": "6",
  "7": "7",
  "8": "8",

YodaEmbedding

import argparse
from pathlib import Path

import numpy as np
import torch
from compressai.datasets import Vimeo90kDataset
from torch.utils.data import DataLoader
from torchvision import transforms

MESSAGE = """

YodaEmbedding

AccessModifierOffset: -2
AlignAfterOpenBracket: BlockIndent    # New in v14. For earlier clang-format versions, use AlwaysBreak instead.
AlignConsecutiveMacros: false
AlignConsecutiveAssignments: false
AlignConsecutiveDeclarations: false
AlignEscapedNewlines: DontAlign
AlignOperands: false
AlignTrailingComments: false
AllowAllArgumentsOnNextLine: false
AllowAllConstructorInitializersOnNextLine: false