anodev/carvekit repository overview

import torch
from carvekit.api.high import HiInterface

# Check doc strings for more information
interface = HiInterface(object_type="hairs-like",  # Can be "object" or "hairs-like".
                        batch_size_seg=5,
                        batch_size_matting=1,
                        device='cuda' if torch.cuda.is_available() else 'cpu',
                        seg_mask_size=640,  # Use 640 for Tracer B7 and 320 for U2Net
                        matting_mask_size=2048,
                        trimap_prob_threshold=231,
                        trimap_dilation=30,
                        trimap_erosion_iters=5,
                        fp16=False)
images_without_background = interface(['./tests/data/cat.jpg'])
cat_wo_bg = images_without_background[0]
cat_wo_bg.save('2.png')

                   

import PIL.Image

from carvekit.api.interface import Interface
from carvekit.ml.wrap.fba_matting import FBAMatting
from carvekit.ml.wrap.tracer_b7 import TracerUniversalB7
from carvekit.pipelines.postprocessing import MattingMethod
from carvekit.pipelines.preprocessing import PreprocessingStub
from carvekit.trimap.generator import TrimapGenerator

# Check doc strings for more information
seg_net = TracerUniversalB7(device='cpu',
              batch_size=1)

fba = FBAMatting(device='cpu',
                 input_tensor_size=2048,
                 batch_size=1)

trimap = TrimapGenerator()

preprocessing = PreprocessingStub()

postprocessing = MattingMethod(matting_module=fba,
                               trimap_generator=trimap,
                               device='cpu')

interface = Interface(pre_pipe=preprocessing,
                      post_pipe=postprocessing,
                      seg_pipe=seg_net)

image = PIL.Image.open('tests/data/cat.jpg')
cat_wo_bg = interface([image])[0]
cat_wo_bg.save('2.png')
                   

Usage: carvekit [OPTIONS]

  Performs background removal on specified photos using console interface.

Options:
  -i ./2.jpg                   Path to input file or dir  [required]
  -o ./2.png                   Path to output file or dir
  --pre none                   Preprocessing method
  --post fba                   Postprocessing method.
  --net tracer_b7              Segmentation Network. Check README for more info.
  --recursive                  Enables recursive search for images in a folder
  --batch_size 10              Batch Size for list of images to be loaded to
                               RAM

  --batch_size_seg 5           Batch size for list of images to be processed
                               by segmentation network

  --batch_size_mat 1           Batch size for list of images to be processed
                               by matting network

  --seg_mask_size 640          The size of the input image for the
                               segmentation neural network. Use 640 for Tracer B7 and 320 for U2Net

  --matting_mask_size 2048     The size of the input image for the matting
                               neural network.
  --trimap_dilation 30       The size of the offset radius from the
                                  object mask in pixels when forming an
                                  unknown area
  --trimap_erosion 5        The number of iterations of erosion that the
                                  object's mask will be subjected to before
                                  forming an unknown area
  --trimap_prob_threshold 231
                                  Probability threshold at which the
                                  prob_filter and prob_as_unknown_area
                                  operations will be applied

  --device cpu                 Processing Device.
  --fp16                       Enables mixed precision processing. Use only with CUDA. CPU support is experimental!
  --help                       Show this message and exit.