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debug: reset to develop 

fix the commit 72da54f that overwrite the file from release/2.4
pull/2215/head
root 2022-08-17 03:43:01 +00:00 committed by Tingquan Gao
parent af16e0cd47
commit 2d10f8e16c
1 changed files with 39 additions and 12 deletions
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51
deploy/python/preprocess.py
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@ -27,8 +27,9 @@ import cv2
import numpy as np import numpy as np
import importlib import importlib
from PIL import Image from PIL import Image
from paddle.vision.transforms import ToTensor, Normalize
from .det_preprocess import DetNormalizeImage, DetPadStride, DetPermute, DetResize from python.det_preprocess import DetNormalizeImage, DetPadStride, DetPermute, DetResize
def create_operators(params): def create_operators(params):
@ -53,13 +54,14 @@ def create_operators(params):
class UnifiedResize(object): class UnifiedResize(object):
def __init__(self, interpolation=None, backend="cv2"): def __init__(self, interpolation=None, backend="cv2", return_numpy=True):
_cv2_interp_from_str = { _cv2_interp_from_str = {
'nearest': cv2.INTER_NEAREST, 'nearest': cv2.INTER_NEAREST,
'bilinear': cv2.INTER_LINEAR, 'bilinear': cv2.INTER_LINEAR,
'area': cv2.INTER_AREA, 'area': cv2.INTER_AREA,
'bicubic': cv2.INTER_CUBIC, 'bicubic': cv2.INTER_CUBIC,
'lanczos': cv2.INTER_LANCZOS4 'lanczos': cv2.INTER_LANCZOS4,
'random': (cv2.INTER_LINEAR, cv2.INTER_CUBIC)
} }
_pil_interp_from_str = { _pil_interp_from_str = {
'nearest': Image.NEAREST, 'nearest': Image.NEAREST,
@ -67,13 +69,26 @@ class UnifiedResize(object):
'bicubic': Image.BICUBIC, 'bicubic': Image.BICUBIC,
'box': Image.BOX, 'box': Image.BOX,
'lanczos': Image.LANCZOS, 'lanczos': Image.LANCZOS,
'hamming': Image.HAMMING 'hamming': Image.HAMMING,
'random': (Image.BILINEAR, Image.BICUBIC)
} }
def _pil_resize(src, size, resample): def _cv2_resize(src, size, resample):
pil_img = Image.fromarray(src) if isinstance(resample, tuple):
resample = random.choice(resample)
return cv2.resize(src, size, interpolation=resample)
def _pil_resize(src, size, resample, return_numpy=True):
if isinstance(resample, tuple):
resample = random.choice(resample)
if isinstance(src, np.ndarray):
pil_img = Image.fromarray(src)
else:
pil_img = src
pil_img = pil_img.resize(size, resample) pil_img = pil_img.resize(size, resample)
return np.asarray(pil_img) if return_numpy:
return np.asarray(pil_img)
return pil_img
if backend.lower() == "cv2": if backend.lower() == "cv2":
if isinstance(interpolation, str): if isinstance(interpolation, str):
@ -81,11 +96,12 @@ class UnifiedResize(object):
# compatible with opencv < version 4.4.0 # compatible with opencv < version 4.4.0
elif interpolation is None: elif interpolation is None:
interpolation = cv2.INTER_LINEAR interpolation = cv2.INTER_LINEAR
self.resize_func = partial(cv2.resize, interpolation=interpolation) self.resize_func = partial(_cv2_resize, resample=interpolation)
elif backend.lower() == "pil": elif backend.lower() == "pil":
if isinstance(interpolation, str): if isinstance(interpolation, str):
interpolation = _pil_interp_from_str[interpolation.lower()] interpolation = _pil_interp_from_str[interpolation.lower()]
self.resize_func = partial(_pil_resize, resample=interpolation) self.resize_func = partial(
_pil_resize, resample=interpolation, return_numpy=return_numpy)
else: else:
logger.warning( logger.warning(
f"The backend of Resize only support \"cv2\" or \"PIL\". \"f{backend}\" is unavailable. Use \"cv2\" instead." f"The backend of Resize only support \"cv2\" or \"PIL\". \"f{backend}\" is unavailable. Use \"cv2\" instead."
@ -93,6 +109,8 @@ class UnifiedResize(object):
self.resize_func = cv2.resize self.resize_func = cv2.resize
def __call__(self, src, size): def __call__(self, src, size):
if isinstance(size, list):
size = tuple(size)
return self.resize_func(src, size) return self.resize_func(src, size)
@ -137,7 +155,8 @@ class ResizeImage(object):
size=None, size=None,
resize_short=None, resize_short=None,
interpolation=None, interpolation=None,
backend="cv2"): backend="cv2",
return_numpy=True):
if resize_short is not None and resize_short > 0: if resize_short is not None and resize_short > 0:
self.resize_short = resize_short self.resize_short = resize_short
self.w = None self.w = None
@ -151,10 +170,18 @@ class ResizeImage(object):
'both 'size' and 'resize_short' are None") 'both 'size' and 'resize_short' are None")
self._resize_func = UnifiedResize( self._resize_func = UnifiedResize(
interpolation=interpolation, backend=backend) interpolation=interpolation,
backend=backend,
return_numpy=return_numpy)
def __call__(self, img): def __call__(self, img):
img_h, img_w = img.shape[:2] if isinstance(img, np.ndarray):
# numpy input
img_h, img_w = img.shape[:2]
else:
# PIL image input
img_w, img_h = img.size
if self.resize_short is not None: if self.resize_short is not None:
percent = float(self.resize_short) / min(img_w, img_h) percent = float(self.resize_short) / min(img_w, img_h)
w = int(round(img_w * percent)) w = int(round(img_w * percent))