| | import numpy as np
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| | from PIL import Image
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| | from os.path import *
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| | import re
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| | import cv2
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| |
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| | TAG_CHAR = np.array([202021.25], np.float32)
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| |
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| |
|
| | def readFlow(fn):
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| | """ Read .flo file in Middlebury format"""
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| |
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| |
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| |
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| |
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| |
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| | with open(fn, 'rb') as f:
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| | magic = np.fromfile(f, np.float32, count=1)
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| | if 202021.25 != magic:
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| | print('Magic number incorrect. Invalid .flo file')
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| | return None
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| | else:
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| | w = np.fromfile(f, np.int32, count=1)
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| | h = np.fromfile(f, np.int32, count=1)
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| |
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| | data = np.fromfile(f, np.float32, count=2 * int(w) * int(h))
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| |
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| |
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| | return np.resize(data, (int(h), int(w), 2))
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| |
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| |
|
| | def readPFM(file):
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| | file = open(file, 'rb')
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| |
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| | color = None
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| | width = None
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| | height = None
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| | scale = None
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| | endian = None
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| |
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| | header = file.readline().rstrip()
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| | if header == b'PF':
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| | color = True
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| | elif header == b'Pf':
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| | color = False
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| | else:
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| | raise Exception('Not a PFM file.')
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| |
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| | dim_match = re.match(rb'^(\d+)\s(\d+)\s$', file.readline())
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| | if dim_match:
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| | width, height = map(int, dim_match.groups())
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| | else:
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| | raise Exception('Malformed PFM header.')
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| |
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| | scale = float(file.readline().rstrip())
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| | if scale < 0:
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| | endian = '<'
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| | scale = -scale
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| | else:
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| | endian = '>'
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| |
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| | data = np.fromfile(file, endian + 'f')
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| | shape = (height, width, 3) if color else (height, width)
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| |
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| | data = np.reshape(data, shape)
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| | data = np.flipud(data)
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| | return data
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| |
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| |
|
| | def writeFlow(filename, uv, v=None):
|
| | """ Write optical flow to file.
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| |
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| | If v is None, uv is assumed to contain both u and v channels,
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| | stacked in depth.
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| | Original code by Deqing Sun, adapted from Daniel Scharstein.
|
| | """
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| | nBands = 2
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| |
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| | if v is None:
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| | assert (uv.ndim == 3)
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| | assert (uv.shape[2] == 2)
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| | u = uv[:, :, 0]
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| | v = uv[:, :, 1]
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| | else:
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| | u = uv
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| |
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| | assert (u.shape == v.shape)
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| | height, width = u.shape
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| | f = open(filename, 'wb')
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| |
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| | f.write(TAG_CHAR)
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| | np.array(width).astype(np.int32).tofile(f)
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| | np.array(height).astype(np.int32).tofile(f)
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| |
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| | tmp = np.zeros((height, width * nBands))
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| | tmp[:, np.arange(width) * 2] = u
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| | tmp[:, np.arange(width) * 2 + 1] = v
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| | tmp.astype(np.float32).tofile(f)
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| | f.close()
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| |
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| |
|
| | def readFlowKITTI(filename):
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| | flow = cv2.imread(filename, cv2.IMREAD_ANYDEPTH | cv2.IMREAD_COLOR)
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| | flow = flow[:, :, ::-1].astype(np.float32)
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| | flow, valid = flow[:, :, :2], flow[:, :, 2]
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| | flow = (flow - 2 ** 15) / 64.0
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| | return flow, valid
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| |
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| |
|
| | def writeFlowKITTI(filename, uv):
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| | uv = 64.0 * uv + 2 ** 15
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| | valid = np.ones([uv.shape[0], uv.shape[1], 1])
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| | uv = np.concatenate([uv, valid], axis=-1).astype(np.uint16)
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| | cv2.imwrite(filename, uv[..., ::-1])
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| |
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| |
|
| | def read_gen(file_name, pil=False):
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| | ext = splitext(file_name)[-1]
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| | if ext == '.png' or ext == '.jpeg' or ext == '.ppm' or ext == '.jpg':
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| | return Image.open(file_name)
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| | elif ext == '.bin' or ext == '.raw':
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| | return np.load(file_name)
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| | elif ext == '.flo':
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| | return readFlow(file_name).astype(np.float32)
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| | elif ext == '.pfm':
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| | flow = readPFM(file_name).astype(np.float32)
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| | if len(flow.shape) == 2:
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| | return flow
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| | else:
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| | return flow[:, :, :-1]
|
| | return []
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| |
|