一つのアプリにまとめる

.python-version

@@ -0,0 +1 @@
+3.11.5

.vscode/extensions.json

@@ -0,0 +1,6 @@
+{
+  "recommendations": [
+    "ms-python.vscode-pylance",
+    "ms-python.black-formatter"
+  ]
+}

.vscode/settings.json

@@ -1,3 +1,6 @@
 {
-    "editor.renderWhitespace": "boundary"
+    "editor.renderWhitespace": "boundary",
+    "[python]": {
+        "editor.defaultFormatter": "ms-python.black-formatter"
+    },
 }

CameraCalibration/cameraCalibration.py

@@ -6,30 +6,35 @@
 import glob
 
 # Defining the dimensions of checkerboard
-CHECKERBOARD = (6,9)
+CHECKERBOARD = (6, 9)
 criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
 
 # Creating vector to store vectors of 3D points for each checkerboard image
 objpoints = []
 # Creating vector to store vectors of 2D points for each checkerboard image
-imgpoints = [] 
+imgpoints = []
 
 
 # Defining the world coordinates for 3D points
-objp = np.zeros((1, CHECKERBOARD[0]*CHECKERBOARD[1], 3), np.float32)
-objp[0,:,:2] = np.mgrid[0:CHECKERBOARD[0], 0:CHECKERBOARD[1]].T.reshape(-1, 2)
+objp = np.zeros((1, CHECKERBOARD[0] * CHECKERBOARD[1], 3), np.float32)
+objp[0, :, :2] = np.mgrid[0 : CHECKERBOARD[0], 0 : CHECKERBOARD[1]].T.reshape(-1, 2)
 prev_img_shape = None
 
 # Extracting path of individual image stored in a given directory
-images = glob.glob('./images/*.jpg')
+images = glob.glob("./images/*.jpg")
 for fname in images:
     img = cv2.imread(fname)
-    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
     # Find the chess board corners
     # If desired number of corners are found in the image then ret = true
-    ret, corners = cv2.findChessboardCorners(gray, CHECKERBOARD, cv2.CALIB_CB_ADAPTIVE_THRESH+
-    	cv2.CALIB_CB_FAST_CHECK+cv2.CALIB_CB_NORMALIZE_IMAGE)
-
+    ret, corners = cv2.findChessboardCorners(
+        gray,
+        CHECKERBOARD,
+        cv2.CALIB_CB_ADAPTIVE_THRESH
+        + cv2.CALIB_CB_FAST_CHECK
+        + cv2.CALIB_CB_NORMALIZE_IMAGE,
+    )
+
     """
     If desired number of corner are detected,
     we refine the pixel coordinates and display 
@@ -38,27 +43,29 @@
     if ret == True:
         objpoints.append(objp)
         # refining pixel coordinates for given 2d points.
-        corners2 = cv2.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria)
-        
+        corners2 = cv2.cornerSubPix(gray, corners, (11, 11), (-1, -1), criteria)
+
         imgpoints.append(corners2)
 
         # Draw and display the corners
-        img = cv2.drawChessboardCorners(img, CHECKERBOARD, corners2,ret)
-    
-    cv2.imshow('img',img)
+        img = cv2.drawChessboardCorners(img, CHECKERBOARD, corners2, ret)
+
+    cv2.imshow("img", img)
     cv2.waitKey(0)
 
 cv2.destroyAllWindows()
 
-h,w = img.shape[:2]
+h, w = img.shape[:2]
 
 """
 Performing camera calibration by 
 passing the value of known 3D points (objpoints)
 and corresponding pixel coordinates of the 
 detected corners (imgpoints)
 """
-ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1],None,None)
+ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(
+    objpoints, imgpoints, gray.shape[::-1], None, None
+)
 
 print("Camera matrix : \n")
 print(mtx)

CameraCalibration/cameraCalibrationWithUndistortion.py

@@ -4,53 +4,58 @@
 import glob
 
 # Defining the dimensions of checkerboard
-CHECKERBOARD = (7,10)
+CHECKERBOARD = (7, 10)
 criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
 
 # Creating vector to store vectors of 3D points for each checkerboard image
 objpoints = []
 # Creating vector to store vectors of 2D points for each checkerboard image
-imgpoints = [] 
+imgpoints = []
 
 
 # Defining the world coordinates for 3D points
-objp = np.zeros((1, CHECKERBOARD[0]*CHECKERBOARD[1], 3), np.float32)
-objp[0,:,:2] = np.mgrid[0:CHECKERBOARD[0], 0:CHECKERBOARD[1]].T.reshape(-1, 2)
+objp = np.zeros((1, CHECKERBOARD[0] * CHECKERBOARD[1], 3), np.float32)
+objp[0, :, :2] = np.mgrid[0 : CHECKERBOARD[0], 0 : CHECKERBOARD[1]].T.reshape(-1, 2)
 prev_img_shape = None
 
 # Extracting path of individual image stored in a given directory
-images = glob.glob('./CameraCalibration/img_camera/*.jpg')
+images = glob.glob("./CameraCalibration/img_camera/*.jpg")
 for fname in images:
     img = cv2.imread(fname)
     print(fname)
-    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
     # Find the chess board corners
     # If desired number of corners are found in the image then ret = true
-    ret, corners = cv2.findChessboardCorners(gray, CHECKERBOARD, cv2.CALIB_CB_ADAPTIVE_THRESH+
-    	cv2.CALIB_CB_FAST_CHECK+cv2.CALIB_CB_NORMALIZE_IMAGE)
-
+    ret, corners = cv2.findChessboardCorners(
+        gray,
+        CHECKERBOARD,
+        cv2.CALIB_CB_ADAPTIVE_THRESH
+        + cv2.CALIB_CB_FAST_CHECK
+        + cv2.CALIB_CB_NORMALIZE_IMAGE,
+    )
+
     """
     If desired number of corner are detected,
     we refine the pixel coordinates and display 
     them on the images of checker board
     """
     if ret == True:
-        print('here')
+        print("here")
         objpoints.append(objp)
         # refining pixel coordinates for given 2d points.
-        corners2 = cv2.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria)
-        
+        corners2 = cv2.cornerSubPix(gray, corners, (11, 11), (-1, -1), criteria)
+
         imgpoints.append(corners2)
 
         # Draw and display the corners
-        img = cv2.drawChessboardCorners(img, CHECKERBOARD, corners2,ret)
-    
-    cv2.imshow('./CameraCalibration/img_corner/',img)
+        img = cv2.drawChessboardCorners(img, CHECKERBOARD, corners2, ret)
+
+    cv2.imshow("./CameraCalibration/img_corner/", img)
     cv2.waitKey(0)
 
 cv2.destroyAllWindows()
 
-h,w = img.shape[:2]
+h, w = img.shape[:2]
 print(h, w)
 
 """
@@ -59,7 +64,9 @@
 and corresponding pixel coordinates of the 
 detected corners (imgpoints)
 """
-ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1],None,None)
+ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(
+    objpoints, imgpoints, gray.shape[::-1], None, None
+)
 
 print("Camera matrix : \n")
 print(mtx)
@@ -74,16 +81,16 @@
 
 img = cv2.imread(images[0])
 # Refining the camera matrix using parameters obtained by calibration
-newcameramtx, roi = cv2.getOptimalNewCameraMatrix(mtx, dist, (w,h), 1, (w,h))
+newcameramtx, roi = cv2.getOptimalNewCameraMatrix(mtx, dist, (w, h), 1, (w, h))
 
 # Method 1 to undistort the image
 dst = cv2.undistort(img, mtx, dist, None, newcameramtx)
 
 # Method 2 to undistort the image
-mapx,mapy=cv2.initUndistortRectifyMap(mtx,dist,None,newcameramtx,(w,h),5)
+mapx, mapy = cv2.initUndistortRectifyMap(mtx, dist, None, newcameramtx, (w, h), 5)
 
-dst = cv2.remap(img,mapx,mapy,cv2.INTER_LINEAR)
+dst = cv2.remap(img, mapx, mapy, cv2.INTER_LINEAR)
 
 # Displaying the undistorted image
-cv2.imshow("./CameraCalibration/img_undistort/",dst)
+cv2.imshow("./CameraCalibration/img_undistort/", dst)
 cv2.waitKey(0)