lol

calib (copy).py

@@ -0,0 +1,48 @@
+#retval, corners = cv2.findChessboardCorners(image,patternSize, flags)
+
+import cv2
+import numpy as np
+
+# Define the size of the chessboard
+chessboard_size = (22, 16)
+
+# Define the object points of the chessboard
+object_points = np.zeros((np.prod(chessboard_size), 3), dtype=np.float32)
+object_points[:, :2] = np.mgrid[0:chessboard_size[0], 0:chessboard_size[1]].T.reshape(-1, 2)
+
+# Create arrays to store the object points and image points from all the images
+object_points_array = []
+image_points_array = []
+
+# Load the images
+images = []
+images.append(cv2.imread("/home/ros/Bureau/ca_ur5/left.jpg"))
+images.append(cv2.imread("/home/ros/Bureau/ca_ur5/left2.jpg"))
+# Add more images as needed
+
+# Loop through each image and find the chessboard corners
+for image in images:
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+    # Find the chessboard corners
+    found, corners = cv2.findChessboardCorners(gray, chessboard_size, None)
+
+    # If the corners are found, add the object points and image points to the arrays
+    if found:
+    	print("yes it is found")
+        object_points_array.append(object_points)
+        image_points_array.append(corners)
+    else 
+    	print("not found")
+"""
+# Calibrate the camera using the object points and image points
+ret, camera_matrix, distortion_coefficients, rotation_vectors, translation_vectors = cv2.calibrateCamera(
+    object_points_array, image_points_array, gray.shape[::-1], None, None)
+
+# Print the camera matrix and distortion coefficients
+print("Camera matrix:")
+print(camera_matrix)
+print("Distortion coefficients:")
+print(distortion_coefficients)
+
+""

calib.py

@@ -4,7 +4,7 @@ import cv2
 import numpy as np
 
 # Define the size of the chessboard
-chessboard_size = (22, 16)
+chessboard_size = (21, 15)
 
 # Define the object points of the chessboard
 object_points = np.zeros((np.prod(chessboard_size), 3), dtype=np.float32)

calib2.py

@@ -0,0 +1,48 @@
+#retval, corners = cv2.findChessboardCorners(image,patternSize, flags)
+
+import cv2
+import numpy as np
+
+# Define the size of the chessboard
+chessboard_size = (22, 16)
+
+# Define the object points of the chessboard
+object_points = np.zeros((np.prod(chessboard_size), 3), dtype=np.float32)
+object_points[:, :2] = np.mgrid[0:chessboard_size[0], 0:chessboard_size[1]].T.reshape(-1, 2)
+
+# Create arrays to store the object points and image points from all the images
+object_points_array = []
+image_points_array = []
+
+# Load the images
+images = []
+images.append(cv2.imread("/home/ros/Bureau/ca_ur5/left.jpg"))
+images.append(cv2.imread("/home/ros/Bureau/ca_ur5/left2.jpg"))
+# Add more images as needed
+
+# Loop through each image and find the chessboard corners
+for image in images:
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+    # Find the chessboard corners
+    found, corners = cv2.findChessboardCorners(gray, chessboard_size, None)
+
+    # If the corners are found, add the object points and image points to the arrays
+    if found:
+    	print("yes it is found")
+        "object_points_array.append(object_points)
+        "image_points_array.append(corners)
+    else 
+    	print("not found")
+"""
+# Calibrate the camera using the object points and image points
+ret, camera_matrix, distortion_coefficients, rotation_vectors, translation_vectors = cv2.calibrateCamera(
+    object_points_array, image_points_array, gray.shape[::-1], None, None)
+
+# Print the camera matrix and distortion coefficients
+print("Camera matrix:")
+print(camera_matrix)
+print("Distortion coefficients:")
+print(distortion_coefficients)
+
+""

findcorners.py

@@ -0,0 +1,42 @@
+import cv2
+
+cam = cv2.VideoCapture(0)
+
+CHECKERBOARD = (5,8)
+criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
+
+img_counter = 0
+
+while True:
+	ret, frame = cam.read()
+	if not ret:
+		print("failed to grab frame")
+		break
+		
+	frame = cv2.resize(frame, (640,480))
+
+	gray = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
+	ret, corners = cv2.findChessboardCorners(frame, CHECKERBOARD)
+
+	cv2.imshow("test", frame)
+
+	if ret == True:
+		print(corners)
+		fnn = cv2.drawChessboardCorners(frame, CHECKERBOARD, corners, ret)
+		cv2.imshow("result", fnn)
+
+	k = cv2.waitKey(1)
+	if k%256 == 27:
+		# ESC pressed
+		print("Escape hit, closing...")
+		break
+	elif k%256 == 32:
+		# SPACE pressed
+		img_name = "opencv_frame_{}.png".format(img_counter)
+		cv2.imwrite(img_name, frame)
+		print("{} written!".format(img_name))
+		img_counter += 1
+
+cam.release()
+
+cv2.destroyAllWindows()

test2.py

@@ -19,19 +19,23 @@ objp[0,:,:2] = np.mgrid[0:CHECKERBOARD[0], 0:CHECKERBOARD[1]].T.reshape(-1, 2)
 prev_img_shape = None
 
 
-h = 480
-w = 640
+h = 544
+w = 960
 
+#print(CHECKERBOARD)
 # Extracting path of individual image stored in a given directory
 images = glob.glob('/home/ros/Bureau/ca_ur5/*.jpg')
 for fname in images:
 	img = cv2.imread(fname)
 	h,w = img.shape[:2]
 	gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
-	print(gray)
+	cv2.imshow('gray',gray)
 	# 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)
+	#print(cv2.CALIB_CB_ADAPTIVE_THRESH)
+	print(ret)
+	print(corners)
 	"""
 	If desired number of corner are detected,
 	we refine the pixel coordinates and display 
@@ -39,6 +43,8 @@ for fname in images:
 	"""
 	if ret == True:
 		objpoints.append(objp)
+		print("objpoints is : \n")
+		print(objpoints)
 		# refining pixel coordinates for given 2d points.
 		corners2 = cv2.cornerSubPix(gray, corners, (11,11),(-1,-1), criteria)
 		imgpoints.append(corners2)
@@ -46,7 +52,7 @@ for fname in images:
 		# Draw and display the corners
 		img = cv2.drawChessboardCorners(img,CHECKERBOARD,corners2,ret)
 
-	cv2.imshow('img',img)
+	#cv2.imshow('img',img)
 	cv2.waitKey(0)
 
 cv2.destroyAllWindows()