restructure

Author: ddelago

ChAruco_Circles.webm

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+# System information:
+# - Linux Mint 18.1 Cinnamon 64-bit
+# - Python 2.7 with OpenCV 3.2.0
+
+import numpy
+import cv2
+from cv2 import aruco
+import pickle
+import glob
+
+
+# ChAruco board variables
+CHARUCOBOARD_ROWCOUNT = 7
+CHARUCOBOARD_COLCOUNT = 5 
+ARUCO_DICT = aruco.Dictionary_get(aruco.DICT_5X5_1000)
+
+# Create constants to be passed into OpenCV and Aruco methods
+CHARUCO_BOARD = aruco.CharucoBoard_create(
+        squaresX=CHARUCOBOARD_COLCOUNT,
+        squaresY=CHARUCOBOARD_ROWCOUNT,
+        squareLength=0.04,
+        markerLength=0.02,
+        dictionary=ARUCO_DICT)
+
+# Create the arrays and variables we'll use to store info like corners and IDs from images processed
+corners_all = [] # Corners discovered in all images processed
+ids_all = [] # Aruco ids corresponding to corners discovered
+image_size = None # Determined at runtime
+
+
+# This requires a set of images or a video taken with the camera you want to calibrate
+# I'm using a set of images taken with the camera with the naming convention:
+# 'camera-pic-of-charucoboard-<NUMBER>.jpg'
+# All images used should be the same size, which if taken with the same camera shouldn't be a problem
+images = glob.glob('./pictures/*.jpg')
+
+
+# Loop through images glob'ed
+for iname in images:
+    # Open the image
+    # ret, img = cap.read()
+
+    img = cv2.imread(iname)
+
+    # img = cv2.imread(iname)
+    cv2.imshow('Charuco board', img)
+
+    # Grayscale the image
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+
+    # Find aruco markers in the query image
+    corners, ids, _ = aruco.detectMarkers(
+            image=gray,
+            dictionary=ARUCO_DICT)
+
+    # Outline the aruco markers found in our query image
+    img = aruco.drawDetectedMarkers(
+            image=img, 
+            corners=corners)
+
+    # Get charuco corners and ids from detected aruco markers
+    response, charuco_corners, charuco_ids = aruco.interpolateCornersCharuco(
+            markerCorners=corners,
+            markerIds=ids,
+            image=gray,
+            board=CHARUCO_BOARD)
+
+    # If a Charuco board was found, let's collect image/corner points
+    # Requiring at least 20 squares
+    if response > 20:
+        # Add these corners and ids to our calibration arrays
+        corners_all.append(charuco_corners)
+        ids_all.append(charuco_ids)
+        
+        # Draw the Charuco board we've detected to show our calibrator the board was properly detected
+        img = aruco.drawDetectedCornersCharuco(
+                image=img,
+                charucoCorners=charuco_corners,
+                charucoIds=charuco_ids)
+       
+        # If our image size is unknown, set it now
+        if not image_size:
+            image_size = gray.shape[::-1]
+    
+        # Reproportion the image, maxing width or height at 1000
+        proportion = max(img.shape) / 1000.0
+        img = cv2.resize(img, (int(img.shape[1]/proportion), int(img.shape[0]/proportion)))
+        # Pause to display each image, waiting for key press
+        cv2.imshow('Charuco board', img)
+        if cv2.waitKey(0) == ord('q'):
+            break
+    else:
+        print("Not able to detect a charuco board in image: {}".format(iname))
+
+# Destroy any open CV windows
+cv2.destroyAllWindows()
+
+# Make sure at least one image was found
+if len(images) < 1:
+    # Calibration failed because there were no images, warn the user
+    print("Calibration was unsuccessful. No images of charucoboards were found. Add images of charucoboards and use or alter the naming conventions used in this file.")
+    # Exit for failure
+    exit()
+
+# Make sure we were able to calibrate on at least one charucoboard by checking
+# if we ever determined the image size
+if not image_size:
+    # Calibration failed because we didn't see any charucoboards of the PatternSize used
+    print("Calibration was unsuccessful. We couldn't detect charucoboards in any of the images supplied. Try changing the patternSize passed into Charucoboard_create(), or try different pictures of charucoboards.")
+    # Exit for failure
+    exit()
+
+# Now that we've seen all of our images, perform the camera calibration
+# based on the set of points we've discovered
+calibration, cameraMatrix, distCoeffs, rvecs, tvecs = aruco.calibrateCameraCharuco(
+        charucoCorners=corners_all,
+        charucoIds=ids_all,
+        board=CHARUCO_BOARD,
+        imageSize=image_size,
+        cameraMatrix=None,
+        distCoeffs=None)
+    
+# Print matrix and distortion coefficient to the console
+print(cameraMatrix)
+print(distCoeffs)
+    
+# Save values to be used where matrix+dist is required, for instance for posture estimation
+# I save files in a pickle file, but you can use yaml or whatever works for you
+f = open('calibration.pckl', 'wb')
+pickle.dump((cameraMatrix, distCoeffs, rvecs, tvecs), f)
+f.close()
+    
+# Print to console our success
+print('Calibration successful. Calibration file used: {}'.format('calibration.pckl'))