def ipm(imgFile, cfgFile):
image = cv2.cvtColor(cv2.imread(imgFile), cv2.COLOR_BGR2RGB)
TARGET_H, TARGET_W = 1024, 1024
# TARGET_H, TARGET_W = 800, 800
plane = Plane(20, -25, 0, 0, 0, 0, TARGET_H, TARGET_W, 0.035)
extrinsic, intrinsic = load_camera_params(cfgFile)
warped1 = ipm_from_parameters(image, plane.xyz, intrinsic, extrinsic,
TARGET_H, TARGET_W)
return warped1
def test_perspective():
extrinsic, intrinsic = load_camera_params('camera.json')
P = intrinsic @ extrinsic
plane = Plane(
0,
-1,
0, # x, y, z
0,
0,
0, # roll, pitch, yaw
3,
3,
2) # col, row, scale
print(perspective(plane.xyz, P, 3, 3))
def ipm_from_opencv(image, source_points, target_points):
# Compute projection matrix
M = cv2.getPerspectiveTransform(source_points, target_points)
# Warp the image
warped = cv2.warpPerspective(image, M, (TARGET_W, TARGET_H), flags=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT,
borderValue=0)
return warped
if __name__ == '__main__':
################
# Derived method
################
# Define the plane on the region of interest (road)
plane = Plane(0, -25, 0, 0, 0, 0, TARGET_H, TARGET_W, 0.1)
# Retrieve camera parameters
extrinsic, intrinsic = load_camera_params('camera.json')
# Apply perspective transformation
warped1 = ipm_from_parameters(image, plane.xyz, intrinsic, extrinsic)
################
# OpenCV
################
# Vertices coordinates in the source image
s = np.array([[830, 598],
[868, 568],
[1285, 598],
[1248, 567]], dtype=np.float32)
# Vertices coordinates in the destination image
t = np.array([[177, 231],
[213, 231],
return file_name
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Shadow detection')
parser.add_argument("--data_path", "-i", type=str)
parser.add_argument("--pin_num", type=int, default=5)
ARGS = parser.parse_args()
o_path = os.path.join(ARGS.data_path, "tmp")
if not os.path.exists(o_path):
os.makedirs(o_path)
camera_matrix, camera_dist = utils.load_camera_params(ARGS.data_path)
img_paths = glob.glob(os.path.join(ARGS.data_path, "*.png"))
img_paths = sorted(img_paths)
img_paths = np.array(img_paths, dtype=str)
imgs = [cv2.imread(path)[:, :, ::-1] for path in img_paths]
imgs = [cv2.undistort(i, camera_matrix, camera_dist) for i in imgs]
file_names = [__file_name(path) for path in img_paths]
marker_coordinates_paths = [
os.path.join(ARGS.data_path, "{}_marker_coordinates.npz".format(path))
for path in file_names
]
marker_coordinates = [
np.load(path)["marker_coordinates"]
for path in marker_coordinates_paths
def getImageFiles(rootDir):
imgFiles = os.listdir(rootDir)
imgFiles = [os.path.join(rootDir, img) for img in imgFiles]
return imgFiles
if __name__ == '__main__':
rootDir = argv[1]
cfgFile = argv[2]
imgFiles = getImageFiles(rootDir)
TARGET_H, TARGET_W = 1024, 1024
extrinsic, intrinsic = load_camera_params(cfgFile)
plane = Plane(20, -25, 0, 0, 0, 0, TARGET_H, TARGET_W, 0.035)
i = 1
for imgFile in tqdm(imgFiles, total=len(imgFiles)):
image = cv2.cvtColor(cv2.imread(imgFile), cv2.COLOR_BGR2RGB)
warped = ipm_from_parameters(image, plane.xyz, intrinsic, extrinsic)
cv2.imwrite(imgFile, cv2.cvtColor(warped, cv2.COLOR_BGR2RGB))
# outFile = os.path.join(rootDir, str(i) + ".png")
# cv2.imwrite(outFile, cv2.cvtColor(warped, cv2.COLOR_BGR2RGB))
# i += 1
# fig, ax = plt.subplots(1, 2)