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Diffstat (limited to 'r_basicsr/utils/lmdb_util.py')
| -rw-r--r-- | r_basicsr/utils/lmdb_util.py | 196 |
1 files changed, 196 insertions, 0 deletions
diff --git a/r_basicsr/utils/lmdb_util.py b/r_basicsr/utils/lmdb_util.py new file mode 100644 index 0000000..97774ca --- /dev/null +++ b/r_basicsr/utils/lmdb_util.py @@ -0,0 +1,196 @@ +import cv2
+import lmdb
+import sys
+from multiprocessing import Pool
+from os import path as osp
+from tqdm import tqdm
+
+
+def make_lmdb_from_imgs(data_path,
+ lmdb_path,
+ img_path_list,
+ keys,
+ batch=5000,
+ compress_level=1,
+ multiprocessing_read=False,
+ n_thread=40,
+ map_size=None):
+ """Make lmdb from images.
+
+ Contents of lmdb. The file structure is:
+ example.lmdb
+ ├── data.mdb
+ ├── lock.mdb
+ ├── meta_info.txt
+
+ The data.mdb and lock.mdb are standard lmdb files and you can refer to
+ https://lmdb.readthedocs.io/en/release/ for more details.
+
+ The meta_info.txt is a specified txt file to record the meta information
+ of our datasets. It will be automatically created when preparing
+ datasets by our provided dataset tools.
+ Each line in the txt file records 1)image name (with extension),
+ 2)image shape, and 3)compression level, separated by a white space.
+
+ For example, the meta information could be:
+ `000_00000000.png (720,1280,3) 1`, which means:
+ 1) image name (with extension): 000_00000000.png;
+ 2) image shape: (720,1280,3);
+ 3) compression level: 1
+
+ We use the image name without extension as the lmdb key.
+
+ If `multiprocessing_read` is True, it will read all the images to memory
+ using multiprocessing. Thus, your server needs to have enough memory.
+
+ Args:
+ data_path (str): Data path for reading images.
+ lmdb_path (str): Lmdb save path.
+ img_path_list (str): Image path list.
+ keys (str): Used for lmdb keys.
+ batch (int): After processing batch images, lmdb commits.
+ Default: 5000.
+ compress_level (int): Compress level when encoding images. Default: 1.
+ multiprocessing_read (bool): Whether use multiprocessing to read all
+ the images to memory. Default: False.
+ n_thread (int): For multiprocessing.
+ map_size (int | None): Map size for lmdb env. If None, use the
+ estimated size from images. Default: None
+ """
+
+ assert len(img_path_list) == len(keys), ('img_path_list and keys should have the same length, '
+ f'but got {len(img_path_list)} and {len(keys)}')
+ print(f'Create lmdb for {data_path}, save to {lmdb_path}...')
+ print(f'Totoal images: {len(img_path_list)}')
+ if not lmdb_path.endswith('.lmdb'):
+ raise ValueError("lmdb_path must end with '.lmdb'.")
+ if osp.exists(lmdb_path):
+ print(f'Folder {lmdb_path} already exists. Exit.')
+ sys.exit(1)
+
+ if multiprocessing_read:
+ # read all the images to memory (multiprocessing)
+ dataset = {} # use dict to keep the order for multiprocessing
+ shapes = {}
+ print(f'Read images with multiprocessing, #thread: {n_thread} ...')
+ pbar = tqdm(total=len(img_path_list), unit='image')
+
+ def callback(arg):
+ """get the image data and update pbar."""
+ key, dataset[key], shapes[key] = arg
+ pbar.update(1)
+ pbar.set_description(f'Read {key}')
+
+ pool = Pool(n_thread)
+ for path, key in zip(img_path_list, keys):
+ pool.apply_async(read_img_worker, args=(osp.join(data_path, path), key, compress_level), callback=callback)
+ pool.close()
+ pool.join()
+ pbar.close()
+ print(f'Finish reading {len(img_path_list)} images.')
+
+ # create lmdb environment
+ if map_size is None:
+ # obtain data size for one image
+ img = cv2.imread(osp.join(data_path, img_path_list[0]), cv2.IMREAD_UNCHANGED)
+ _, img_byte = cv2.imencode('.png', img, [cv2.IMWRITE_PNG_COMPRESSION, compress_level])
+ data_size_per_img = img_byte.nbytes
+ print('Data size per image is: ', data_size_per_img)
+ data_size = data_size_per_img * len(img_path_list)
+ map_size = data_size * 10
+
+ env = lmdb.open(lmdb_path, map_size=map_size)
+
+ # write data to lmdb
+ pbar = tqdm(total=len(img_path_list), unit='chunk')
+ txn = env.begin(write=True)
+ txt_file = open(osp.join(lmdb_path, 'meta_info.txt'), 'w')
+ for idx, (path, key) in enumerate(zip(img_path_list, keys)):
+ pbar.update(1)
+ pbar.set_description(f'Write {key}')
+ key_byte = key.encode('ascii')
+ if multiprocessing_read:
+ img_byte = dataset[key]
+ h, w, c = shapes[key]
+ else:
+ _, img_byte, img_shape = read_img_worker(osp.join(data_path, path), key, compress_level)
+ h, w, c = img_shape
+
+ txn.put(key_byte, img_byte)
+ # write meta information
+ txt_file.write(f'{key}.png ({h},{w},{c}) {compress_level}\n')
+ if idx % batch == 0:
+ txn.commit()
+ txn = env.begin(write=True)
+ pbar.close()
+ txn.commit()
+ env.close()
+ txt_file.close()
+ print('\nFinish writing lmdb.')
+
+
+def read_img_worker(path, key, compress_level):
+ """Read image worker.
+
+ Args:
+ path (str): Image path.
+ key (str): Image key.
+ compress_level (int): Compress level when encoding images.
+
+ Returns:
+ str: Image key.
+ byte: Image byte.
+ tuple[int]: Image shape.
+ """
+
+ img = cv2.imread(path, cv2.IMREAD_UNCHANGED)
+ if img.ndim == 2:
+ h, w = img.shape
+ c = 1
+ else:
+ h, w, c = img.shape
+ _, img_byte = cv2.imencode('.png', img, [cv2.IMWRITE_PNG_COMPRESSION, compress_level])
+ return (key, img_byte, (h, w, c))
+
+
+class LmdbMaker():
+ """LMDB Maker.
+
+ Args:
+ lmdb_path (str): Lmdb save path.
+ map_size (int): Map size for lmdb env. Default: 1024 ** 4, 1TB.
+ batch (int): After processing batch images, lmdb commits.
+ Default: 5000.
+ compress_level (int): Compress level when encoding images. Default: 1.
+ """
+
+ def __init__(self, lmdb_path, map_size=1024**4, batch=5000, compress_level=1):
+ if not lmdb_path.endswith('.lmdb'):
+ raise ValueError("lmdb_path must end with '.lmdb'.")
+ if osp.exists(lmdb_path):
+ print(f'Folder {lmdb_path} already exists. Exit.')
+ sys.exit(1)
+
+ self.lmdb_path = lmdb_path
+ self.batch = batch
+ self.compress_level = compress_level
+ self.env = lmdb.open(lmdb_path, map_size=map_size)
+ self.txn = self.env.begin(write=True)
+ self.txt_file = open(osp.join(lmdb_path, 'meta_info.txt'), 'w')
+ self.counter = 0
+
+ def put(self, img_byte, key, img_shape):
+ self.counter += 1
+ key_byte = key.encode('ascii')
+ self.txn.put(key_byte, img_byte)
+ # write meta information
+ h, w, c = img_shape
+ self.txt_file.write(f'{key}.png ({h},{w},{c}) {self.compress_level}\n')
+ if self.counter % self.batch == 0:
+ self.txn.commit()
+ self.txn = self.env.begin(write=True)
+
+ def close(self):
+ self.txn.commit()
+ self.env.close()
+ self.txt_file.close()
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