refactored
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+20
-16
@@ -2,6 +2,9 @@ import numpy as np
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import cv2 as cv
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import glob
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PAT_NX = 7
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PAT_NY = 6
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def draw_gizmo(img, corners, imgpts):
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corner = tuple(corners[0].ravel().astype("int32"))
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imgpts = imgpts.astype("int32")
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@@ -26,6 +29,14 @@ def draw_cube(img, corners, imgpts):
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return img
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def init_data():
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criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001)
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objp = np.zeros((PAT_NX * PAT_NY, 3), np.float32)
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objp[:, :2] = np.mgrid[0:PAT_NX, 0:PAT_NY].T.reshape(-1, 2)
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axis = np.float32([[3, 0, 0], [0, 3, 0], [0, 0, -3]]).reshape(-1, 3)
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return criteria, objp, axis
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def main():
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process_video()
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@@ -34,11 +45,8 @@ def process_video():
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with np.load('results/cam.npz') as X:
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mtx, dist, _, _ = [X[i] for i in ('mtx', 'dist', 'rvecs', 'tvecs')]
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criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001)
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objp = np.zeros((6 * 7, 3), np.float32)
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objp[:, :2] = np.mgrid[0:7, 0:6].T.reshape(-1, 2)
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axis = np.float32([[3, 0, 0], [0, 3, 0], [0, 0, -3]]).reshape(-1, 3)
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# Init
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criteria, objp, axis = init_data()
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# Open camera
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video = cv.VideoCapture(0)
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@@ -51,7 +59,7 @@ def process_video():
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ok, img = video.read()
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if not ok:
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return
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process_img(img, criteria, objp, axis, mtx, dist)
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process(img, mtx, dist, criteria, objp, axis)
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k = cv.waitKey(1) & 0xFF
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if k == ord('q'):
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break
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@@ -60,25 +68,21 @@ def process_still():
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with np.load('results/cam.npz') as X:
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mtx, dist, _, _ = [X[i] for i in ('mtx', 'dist', 'rvecs', 'tvecs')]
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criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001)
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objp = np.zeros((6 * 7, 3), np.float32)
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objp[:, :2] = np.mgrid[0:7, 0:6].T.reshape(-1, 2)
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axis = np.float32([[3, 0, 0], [0, 3, 0], [0, 0, -3]]).reshape(-1, 3)
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# Init
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criteria, objp, axis = init_data()
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for fname in glob.glob('check*.jpg'):
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img = cv.imread(fname)
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process_img(img, criteria, objp, axis, mtx, dist)
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process(img, mtx, dist, criteria, objp, axis)
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k = cv.waitKey(1) & 0xFF
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if k == ord('q'):
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break
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def process_img(img, criteria, objp, axis, mtx, dist): # Load previously saved data
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pattern_size = (7, 6)
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def process(img, mtx, dist, criteria, objp, axis): # Load previously saved data
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gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
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ret, corners = cv.findChessboardCorners(gray, pattern_size, corners=None, flags=cv.CALIB_CB_ADAPTIVE_THRESH+cv.CALIB_CB_NORMALIZE_IMAGE+cv.CALIB_CB_FAST_CHECK)
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cv.drawChessboardCorners(img, corners=corners, patternSize=pattern_size, patternWasFound=ret)
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ret, corners = cv.findChessboardCorners(gray, (PAT_NX, PAT_NY), corners=None, flags=cv.CALIB_CB_ADAPTIVE_THRESH+cv.CALIB_CB_NORMALIZE_IMAGE+cv.CALIB_CB_FAST_CHECK)
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cv.drawChessboardCorners(img, corners=corners, patternSize=(PAT_NX, PAT_NY), patternWasFound=ret)
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if ret:
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corners2 = cv.cornerSubPix(gray, corners, (11, 11), (-1, -1), criteria)
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