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Configuration error
Configuration error
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d01f62c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 | import os
from os import path
import shutil
import collections
import cv2
from PIL import Image
if not hasattr(Image, 'Resampling'): # Pillow<9.0
Image.Resampling = Image
import numpy as np
from util.palette import davis_palette
import progressbar
# https://bugs.python.org/issue28178
# ah python ah why
class LRU:
def __init__(self, func, maxsize=128):
self.cache = collections.OrderedDict()
self.func = func
self.maxsize = maxsize
def __call__(self, *args):
cache = self.cache
if args in cache:
cache.move_to_end(args)
return cache[args]
result = self.func(*args)
cache[args] = result
if len(cache) > self.maxsize:
cache.popitem(last=False)
return result
def invalidate(self, key):
self.cache.pop(key, None)
class ResourceManager:
def __init__(self, config):
# determine inputs
images = config['images']
video = config['video']
self.workspace = config['workspace']
self.size = config['size']
self.palette = davis_palette
# create temporary workspace if not specified
if self.workspace is None:
if images is not None:
basename = path.basename(images)
elif video is not None:
basename = path.basename(video)[:-4]
else:
raise NotImplementedError(
'Either images, video, or workspace has to be specified')
self.workspace = path.join('./workspace', basename)
print(f'Workspace is in: {self.workspace}')
# determine the location of input images
need_decoding = False
need_resizing = False
if path.exists(path.join(self.workspace, 'images')):
pass
elif images is not None:
need_resizing = True
elif video is not None:
# will decode video into frames later
need_decoding = True
# create workspace subdirectories
self.image_dir = path.join(self.workspace, 'images')
self.mask_dir = path.join(self.workspace, 'masks')
os.makedirs(self.image_dir, exist_ok=True)
os.makedirs(self.mask_dir, exist_ok=True)
# convert read functions to be buffered
self.get_image = LRU(self._get_image_unbuffered, maxsize=config['buffer_size'])
self.get_mask = LRU(self._get_mask_unbuffered, maxsize=config['buffer_size'])
# extract frames from video
if need_decoding:
self._extract_frames(video)
# copy/resize existing images to the workspace
if need_resizing:
self._copy_resize_frames(images)
# read all frame names
self.names = sorted(os.listdir(self.image_dir))
self.names = [f[:-4] for f in self.names] # remove extensions
self.length = len(self.names)
assert self.length > 0, f'No images found! Check {self.workspace}/images. Remove folder if necessary.'
print(f'{self.length} images found.')
self.height, self.width = self.get_image(0).shape[:2]
self.visualization_init = False
def _extract_frames(self, video):
cap = cv2.VideoCapture(video)
frame_index = 0
print(f'Extracting frames from {video} into {self.image_dir}...')
bar = progressbar.ProgressBar(max_value=progressbar.UnknownLength)
while(cap.isOpened()):
_, frame = cap.read()
if frame is None:
break
if self.size > 0:
h, w = frame.shape[:2]
new_w = (w*self.size//min(w, h))
new_h = (h*self.size//min(w, h))
if new_w != w or new_h != h:
frame = cv2.resize(frame,dsize=(new_w,new_h),interpolation=cv2.INTER_AREA)
cv2.imwrite(path.join(self.image_dir, f'{frame_index:07d}.jpg'), frame)
frame_index += 1
bar.update(frame_index)
bar.finish()
print('Done!')
def _copy_resize_frames(self, images):
image_list = os.listdir(images)
print(f'Copying/resizing frames into {self.image_dir}...')
for image_name in progressbar.progressbar(image_list):
if self.size < 0:
# just copy
shutil.copy2(path.join(images, image_name), self.image_dir)
else:
frame = cv2.imread(path.join(images, image_name))
h, w = frame.shape[:2]
new_w = (w*self.size//min(w, h))
new_h = (h*self.size//min(w, h))
if new_w != w or new_h != h:
frame = cv2.resize(frame,dsize=(new_w,new_h),interpolation=cv2.INTER_AREA)
cv2.imwrite(path.join(self.image_dir, image_name), frame)
print('Done!')
def save_mask(self, ti, mask):
# mask should be uint8 H*W without channels
assert 0 <= ti < self.length
assert isinstance(mask, np.ndarray)
mask = Image.fromarray(mask)
mask.putpalette(self.palette)
mask.save(path.join(self.mask_dir, self.names[ti]+'.png'))
self.invalidate(ti)
def save_visualization(self, ti, image):
# image should be uint8 3*H*W
assert 0 <= ti < self.length
assert isinstance(image, np.ndarray)
if not self.visualization_init:
self.visualization_dir = path.join(self.workspace, 'visualization')
os.makedirs(self.visualization_dir, exist_ok=True)
self.visualization_init = True
image = Image.fromarray(image)
image.save(path.join(self.visualization_dir, self.names[ti]+'.jpg'))
def _get_image_unbuffered(self, ti):
# returns H*W*3 uint8 array
assert 0 <= ti < self.length
image = Image.open(path.join(self.image_dir, self.names[ti]+'.jpg'))
image = np.array(image)
return image
def _get_mask_unbuffered(self, ti):
# returns H*W uint8 array
assert 0 <= ti < self.length
mask_path = path.join(self.mask_dir, self.names[ti]+'.png')
if path.exists(mask_path):
mask = Image.open(mask_path)
mask = np.array(mask)
return mask
else:
return None
def read_external_image(self, file_name, size=None):
image = Image.open(file_name)
is_mask = image.mode in ['L', 'P']
if size is not None:
# PIL uses (width, height)
image = image.resize((size[1], size[0]),
resample=Image.Resampling.NEAREST if is_mask else Image.Resampling.BICUBIC)
image = np.array(image)
return image
def invalidate(self, ti):
# the image buffer is never invalidated
self.get_mask.invalidate((ti,))
def __len__(self):
return self.length
@property
def h(self):
return self.height
@property
def w(self):
return self.width
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