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import os
import os.path as osp
import glob
from pathlib import Path
import cv2
import numpy as np
import json
IMG_EXT = ['.bmp', '.jpg', '.png', '.jpeg']
NP_BOOL_TYPES = (np.bool_, np.bool8)
NP_FLOAT_TYPES = (np.float_, np.float16, np.float32, np.float64)
NP_INT_TYPES = (np.int_, np.int8, np.int16, np.int32, np.int64, np.uint, np.uint8, np.uint16, np.uint32, np.uint64)
# https://stackoverflow.com/questions/26646362/numpy-array-is-not-json-serializable
class NumpyEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj, np.ndarray):
return obj.tolist()
elif isinstance(obj, np.ScalarType):
if isinstance(obj, NP_BOOL_TYPES):
return bool(obj)
elif isinstance(obj, NP_FLOAT_TYPES):
return float(obj)
elif isinstance(obj, NP_INT_TYPES):
return int(obj)
return json.JSONEncoder.default(self, obj)
def find_all_imgs(img_dir, abs_path=False):
imglist = list()
for filep in glob.glob(osp.join(img_dir, "*")):
filename = osp.basename(filep)
file_suffix = Path(filename).suffix
if file_suffix.lower() not in IMG_EXT:
continue
if abs_path:
imglist.append(filep)
else:
imglist.append(filename)
return imglist
def imread(imgpath, read_type=cv2.IMREAD_COLOR):
# img = cv2.imread(imgpath, read_type)
# if img is None:
img = cv2.imdecode(np.fromfile(imgpath, dtype=np.uint8), read_type)
return img
def imwrite(img_path, img, ext='.png'):
suffix = Path(img_path).suffix
if suffix != '':
img_path = img_path.replace(suffix, ext)
else:
img_path += ext
cv2.imencode(ext, img)[1].tofile(img_path) |