216 lines
8.8 KiB
Python
216 lines
8.8 KiB
Python
'''
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@ Date: 2021-07-16 20:13:57
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@ Author: Qing Shuai
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@ LastEditors: Qing Shuai
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@ LastEditTime: 2022-05-11 20:41:10
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@ FilePath: /EasyMocapPublic/apps/calibration/detect_chessboard.py
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'''
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# detect the corner of chessboard
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from easymocap.annotator.file_utils import getFileList, read_json, save_json
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from easymocap.mytools.debug_utils import mywarn
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from tqdm import tqdm
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from easymocap.annotator import ImageFolder
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from easymocap.annotator.chessboard import findChessboardCorners
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import numpy as np
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from os.path import join
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import cv2
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import os
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import func_timeout
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import threading
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from easymocap.mytools.debug_utils import log
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def getChessboard3d(pattern, gridSize, axis='yx'):
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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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template = np.mgrid[0:pattern[0], 0:pattern[1]].T.reshape(-1,2)
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object_points = np.zeros((pattern[1]*pattern[0], 3), np.float32)
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# 长边是x,短边是z
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if axis == 'xz':
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object_points[:, 0] = template[:, 0]
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object_points[:, 2] = template[:, 1]
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elif axis == 'yx':
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object_points[:, 0] = template[:, 1]
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object_points[:, 1] = template[:, 0]
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else:
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raise NotImplementedError
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object_points = object_points * gridSize
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return object_points
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def create_chessboard(path, image, pattern, gridSize, ext, overwrite=True):
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print('Create chessboard {}'.format(pattern))
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keypoints3d = getChessboard3d(pattern, gridSize=gridSize, axis=args.axis)
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keypoints2d = np.zeros((keypoints3d.shape[0], 3))
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imgnames = getFileList(join(path, image), ext=ext)
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template = {
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'keypoints3d': keypoints3d.tolist(),
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'keypoints2d': keypoints2d.tolist(),
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'pattern': pattern,
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'grid_size': gridSize,
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'visited': False
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}
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for imgname in tqdm(imgnames, desc='create template chessboard'):
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annname = imgname.replace(ext, '.json')
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annname = join(path, 'chessboard', annname)
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if os.path.exists(annname) and overwrite:
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# 覆盖keypoints3d
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data = read_json(annname)
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data['keypoints3d'] = template['keypoints3d']
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save_json(annname, data)
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elif os.path.exists(annname) and not overwrite:
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continue
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else:
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save_json(annname, template)
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def _detect_chessboard(datas, path, image, out, pattern):
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for imgname, annotname in datas:
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# imgname, annotname = dataset[i]
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# detect the 2d chessboard
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img = cv2.imread(imgname)
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annots = read_json(annotname)
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try:
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show = findChessboardCorners(img, annots, pattern)
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except func_timeout.exceptions.FunctionTimedOut:
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show = None
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save_json(annotname, annots)
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if show is None:
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mywarn('[Info] Cannot find chessboard in {}'.format(imgname))
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continue
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outname = join(out, imgname.replace(path + '/{}/'.format(image), ''))
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os.makedirs(os.path.dirname(outname), exist_ok=True)
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if isinstance(show, np.ndarray):
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cv2.imwrite(outname, show)
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def detect_chessboard(path, image, out, pattern, gridSize, args):
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create_chessboard(path, image, pattern, gridSize, ext=args.ext, overwrite=args.overwrite3d)
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dataset = ImageFolder(path, image=image, annot='chessboard', ext=args.ext)
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dataset.isTmp = False
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trange = list(range(len(dataset)))
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threads = []
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for i in range(args.mp):
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ranges = trange[i::args.mp]
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datas = [dataset[t] for t in ranges]
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thread = threading.Thread(target=_detect_chessboard, args=(datas, path, image, out, pattern)) # 应该不存在任何数据竞争
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thread.start()
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threads.append(thread)
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for thread in threads:
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thread.join()
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def _detect_by_search(path, image, out, pattern, sub):
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dataset = ImageFolder(path, sub=sub, annot='chessboard', ext=args.ext)
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dataset.isTmp = False
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nFrames = len(dataset)
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found = np.zeros(nFrames, dtype=bool)
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visited = np.zeros(nFrames, dtype=bool)
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proposals = []
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init_step = args.max_step
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min_step = args.min_step
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for nf in range(0, nFrames, init_step):
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if nf + init_step < len(dataset):
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proposals.append([nf, nf+init_step])
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while len(proposals) > 0:
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left, right = proposals.pop(0)
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print('[detect] {} {:4.1f}% Check [{:5d}, {:5d}]'.format(
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sub, visited.sum()/visited.shape[0]*100, left, right), end=' ')
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for nf in [left, right]:
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if not visited[nf]:
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visited[nf] = True
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imgname, annotname = dataset[nf]
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# detect the 2d chessboard
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img = cv2.imread(imgname)
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annots = read_json(annotname)
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try:
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show = findChessboardCorners(img, annots, pattern)
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except func_timeout.exceptions.FunctionTimedOut:
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show = None
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save_json(annotname, annots)
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if show is None:
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if args.debug:
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print('[Info] Cannot find chessboard in {}'.format(imgname))
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found[nf] = False
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continue
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found[nf] = True
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outname = join(out, imgname.replace(path + '{}{}{}'.format(os.sep, image, os.sep), ''))
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os.makedirs(os.path.dirname(outname), exist_ok=True)
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if isinstance(show, np.ndarray):
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cv2.imwrite(outname, show)
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print('{}-{}'.format('o' if found[left] else 'x', 'o' if found[right] else 'x'))
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if not found[left] and not found[right]:
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visited[left:right] = True
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continue
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mid = (left+right)//2
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if mid == left or mid == right:
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continue
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if mid - left > min_step:
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proposals.append((left, mid))
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if right - mid > min_step:
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proposals.append((mid, right))
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def detect_chessboard_sequence(path, image, out, pattern, gridSize, args):
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create_chessboard(path, image, pattern, gridSize, ext=args.ext, overwrite=args.overwrite3d)
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subs = sorted(os.listdir(join(path, image)))
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subs = [s for s in subs if os.path.isdir(join(path, image, s))]
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if len(subs) == 0:
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subs = [None]
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from multiprocessing import Process
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tasks = []
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for sub in subs:
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task = Process(target=_detect_by_search, args=(path, image, out, pattern, sub))
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task.start()
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tasks.append(task)
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for task in tasks:
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task.join()
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for sub in subs:
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dataset = ImageFolder(path, sub=sub, annot='chessboard', ext=args.ext)
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dataset.isTmp = False
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count, visited = 0, 0
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for nf in range(len(dataset)):
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imgname, annotname = dataset[nf]
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# detect the 2d chessboard
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annots = read_json(annotname)
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if annots['visited']:
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visited += 1
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if annots['keypoints2d'][0][-1] > 0.01:
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count += 1
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log('{}: found {:4d}/{:4d} frames'.format(sub, count, visited))
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def check_chessboard(path, out):
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subs_notvalid = []
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for sub in sorted(os.listdir(join(path, 'images'))):
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if os.path.exists(join(out, sub)):
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continue
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subs_notvalid.append(sub)
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print(subs_notvalid)
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mywarn('Cannot find chessboard in view {}'.format(subs_notvalid))
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mywarn('Please annot them manually:')
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mywarn(f'python3 apps/annotation/annot_calib.py {path} --mode chessboard --annot chessboard --sub {" ".join(subs_notvalid)}')
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if __name__ == "__main__":
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import argparse
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parser = argparse.ArgumentParser()
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parser.add_argument('path', type=str)
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parser.add_argument('--image', type=str, default='images')
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parser.add_argument('--out', type=str, required=True)
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parser.add_argument('--ext', type=str, default='.jpg', choices=['.jpg', '.png'])
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parser.add_argument('--pattern', type=lambda x: (int(x.split(',')[0]), int(x.split(',')[1])),
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help='The pattern of the chessboard', default=(9, 6))
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parser.add_argument('--grid', type=float, default=0.1,
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help='The length of the grid size (unit: meter)')
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parser.add_argument('--max_step', type=int, default=50)
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parser.add_argument('--min_step', type=int, default=0)
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parser.add_argument('--mp', type=int, default=4)
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parser.add_argument('--axis', type=str, default='yx')
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parser.add_argument('--silent', action='store_true')
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parser.add_argument('--debug', action='store_true')
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parser.add_argument('--overwrite3d', action='store_true')
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parser.add_argument('--seq', action='store_true')
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parser.add_argument('--check', action='store_true')
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args = parser.parse_args()
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if args.seq:
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detect_chessboard_sequence(args.path, args.image, args.out, pattern=args.pattern, gridSize=args.grid, args=args)
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else:
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detect_chessboard(args.path, args.image, args.out, pattern=args.pattern, gridSize=args.grid, args=args)
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if args.check:
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check_chessboard(args.path, args.out) |