reordered imports

This commit is contained in:
Flippchen 2023-04-20 11:41:07 +02:00
parent ff38b9a377
commit 72d1c6c64c
2 changed files with 4 additions and 6 deletions

View File

@ -11,8 +11,8 @@ import pooch
from .session_base import BaseSession from .session_base import BaseSession
from .session_cloth import ClothSession from .session_cloth import ClothSession
from .session_dis import DisSession from .session_dis import DisSession
from .session_simple import SimpleSession
from .session_sam import SamSession from .session_sam import SamSession
from .session_simple import SimpleSession
def download_model(url: str, md5: str, fname: str, path: Path): def download_model(url: str, md5: str, fname: str, path: Path):

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@ -1,11 +1,9 @@
from typing import List from typing import List
import numpy
import numpy as np import numpy as np
from PIL import Image from PIL import Image
from PIL.Image import Image as PILImage from PIL.Image import Image as PILImage
import onnxruntime as ort import onnxruntime as ort
from matplotlib import pyplot as plt
from .session_base import BaseSession from .session_base import BaseSession
@ -39,7 +37,7 @@ def resize_longes_side(img: PILImage, size=1024):
return img.resize((new_w, new_h)) return img.resize((new_w, new_h))
def pad_to_square(img: numpy.ndarray, size=1024): def pad_to_square(img: np.ndarray, size=1024):
h, w = img.shape[:2] h, w = img.shape[:2]
padh = size - h padh = size - h
padw = size - w padw = size - w
@ -60,7 +58,7 @@ class SamSession(BaseSession):
def normalize( def normalize(
self, self,
img: numpy.ndarray, img: np.ndarray,
mean=(123.675, 116.28, 103.53), mean=(123.675, 116.28, 103.53),
std=(58.395, 57.12, 57.375), std=(58.395, 57.12, 57.375),
size=(1024, 1024), size=(1024, 1024),
@ -78,7 +76,7 @@ class SamSession(BaseSession):
) -> List[PILImage]: ) -> List[PILImage]:
# Preprocess image # Preprocess image
image = resize_longes_side(img) image = resize_longes_side(img)
image = numpy.array(image) image = np.array(image)
image = self.normalize(image) image = self.normalize(image)
image = pad_to_square(image) image = pad_to_square(image)