75 lines
2.5 KiB
Python
75 lines
2.5 KiB
Python
'''
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@ Date: 2021-04-13 16:14:36
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@ Author: Qing Shuai
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@ LastEditors: Qing Shuai
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@ LastEditTime: 2021-07-17 16:00:17
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@ FilePath: /EasyMocap/easymocap/annotator/chessboard.py
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'''
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import numpy as np
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import cv2
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def getChessboard3d(pattern, gridSize):
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object_points = np.zeros((pattern[1]*pattern[0], 3), np.float32)
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# 注意：这里为了让标定板z轴朝上，设定了短边是x，长边是y
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object_points[:,:2] = np.mgrid[0:pattern[0], 0:pattern[1]].T.reshape(-1,2)
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object_points[:, [0, 1]] = object_points[:, [1, 0]]
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object_points = object_points * gridSize
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return object_points
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colors_chessboard_bar = [
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[0, 0, 255],
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[0, 128, 255],
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[0, 200, 200],
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[0, 255, 0],
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[200, 200, 0],
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[255, 0, 0],
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[255, 0, 250]
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]
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def get_lines_chessboard(pattern=(9, 6)):
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w, h = pattern[0], pattern[1]
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lines = []
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lines_cols = []
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for i in range(w*h-1):
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lines.append([i, i+1])
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lines_cols.append(colors_chessboard_bar[i//w])
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return lines, lines_cols
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def _findChessboardCorners(img, pattern):
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"basic function"
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criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
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retval, corners = cv2.findChessboardCorners(img, pattern,
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flags=cv2.CALIB_CB_ADAPTIVE_THRESH + cv2.CALIB_CB_FAST_CHECK + cv2.CALIB_CB_FILTER_QUADS)
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if not retval:
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return False, None
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corners = cv2.cornerSubPix(img, corners, (11, 11), (-1, -1), criteria)
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corners = corners.squeeze()
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return True, corners
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def _findChessboardCornersAdapt(img, pattern):
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"Adapt mode"
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img = cv2.adaptiveThreshold(img, 255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,\
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cv2.THRESH_BINARY,21, 2)
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return _findChessboardCorners(img, pattern)
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def findChessboardCorners(img, annots, pattern):
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conf = sum([v[2] for v in annots['keypoints2d']])
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if annots['visited'] and conf > 0:
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return True
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elif annots['visited']:
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return None
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annots['visited'] = True
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gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
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# Find the chess board corners
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for func in [_findChessboardCornersAdapt, _findChessboardCorners]:
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ret, corners = func(gray, pattern)
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if ret:break
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else:
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return None
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# found the corners
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show = img.copy()
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show = cv2.drawChessboardCorners(show, pattern, corners, ret)
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assert corners.shape[0] == len(annots['keypoints2d'])
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corners = np.hstack((corners, np.ones((corners.shape[0], 1))))
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annots['keypoints2d'] = corners.tolist()
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return show |