Failed to initialize GLEW

[stevenwudi]

Hi, after running install.sh (beforehand I need to run sudo apt install libeigen3-dev, sudo apt-get install libglfw3-dev libgles2-mesa-dev, sudo apt-get install libglew-dev to install all the required libraries)

I have the render_egl.pyx file.

However, by executing demo.py, I have the error "Failed to initialize GLEW".

Any clue to overcome it? Many thanks!

[pengwangucla]

It seems init GLEW is not necessary for successfully render a depth map. I have already update to rm the line of ERROR message. You may check it out again.

[stevenwudi]

Hey, after fetch the update, I recompile the .so file. (I have Ubuntu 16.04 with Python 3.6)
However, exit code 139 (interrupted by signal 11: SIGSEGV) appears when executing render.renderMesh_py

[ApolloScapeAuto]

Never met that problem. We worked with Ubuntu14.04 and python 2.7. So you mean excuting render.render_test.py ?

[pengwangucla]

Is it possible due to some driver conflict ? Try to reinstall nvidia driver (I met segment fault when having matlab or nouveau driver)

[ApolloScapeAuto]

@stevenwudi Did you solve the problem ?

[stevenwudi]

No, unfortunately, by using Ubuntu 14.04, Python2.7 still generate (interrupted by signal 11: SIGSEGV) error. (Although we have NVIDIA-SMI 384.69 )

Could it be the Failed to initialize GLEW reason (uncommenting this line /* fprintf(stderr, "Failed to initialize GLEW\n"); */ out will print the original error message .

[skylian]

Could you check the error message returned by glewInit()? For example, you can do something like this:

GLenum ret = glewInit();
if (ret != GLEW_OK) {
    fprintf(stderr, "Error: %s\n", glewGetErrorString(ret));
}

[ApolloScapeAuto]

@stevenwudi If you can't fix it. May be you can use other renderer like open3d etc for rendering operation given the mesh model, camera intrinsic and pose.

[stevenwudi]

Hey, I couldn't render the image with (interrupted by signal 11: SIGSEGV) error. ( open3d works by installing from pip, and I would say it is a nice rendering software).

However, I created the following script replacing the showAnn and render_car: Gist: I have accumulated the mask for individual cars, the masks are required by firstly projecting the vertices to 2d using imgpts, jac = cv2.projectPoints(np.float32(car['vertices']), pose[:3], pose[3:], self.intrinsic, distCoeffs=np.asarray([])) and then drawing the edges by cv2.polylines(mask, [pts], True, (0, 255, 0))

It almost makes sense to me (apart from some weird rotation and transnational misalignment. Could you help me to check what's wrong? Many thanks!

    def showAnn(self, image_name, settings):
        """Show the annotation of a pose file in an image
        Input:
            image_name: the name of image
        Output:
            depth: a rendered depth map of each car
            masks: an instance mask of the label
            image_vis: an image show the overlap of car model and image
        """

        car_pose_file = '%s/%s.json' % (self._data_config['pose_dir'], image_name)
        with open(car_pose_file) as f:
            car_poses = json.load(f)
        image_file = '%s/%s.jpg' % (self._data_config['image_dir'], image_name)
        image = cv2.imread(image_file, cv2.IMREAD_UNCHANGED)[:, :, ::-1]

        intrinsic = self.dataset.get_intrinsic(image_name)
        image, self.intrinsic = self.rescale(image, intrinsic)

        merged_image = image.copy()
        mask_all = np.zeros(image.shape)
        for i, car_pose in enumerate(car_poses):
            car_name = car_models.car_id2name[car_pose['car_id']].name
            mask = self.render_car_cv2(car_pose['pose'], car_name, image)
            mask_all += mask

        mask_all = mask_all * 255 / mask_all.max()

        alpha = 0.5
        cv2.addWeighted(image.astype(np.uint8), 1.0, mask_all.astype(np.uint8), 1 - alpha, 0, merged_image)

def render_car(self,  pose, car_name, image):
        car = self.car_models[car_name]
        pose = np.array(pose)
        # project 3D points to 2d image plane
        imgpts, jac = cv2.projectPoints(np.float32(car['vertices']), pose[:3], pose[3:], self.intrinsic, distCoeffs=np.asarray([]))

        mask = np.zeros(image.shape)
        for face in car['faces'] - 1:
            pts = np.array([[imgpts[idx, 0, 0], imgpts[idx, 0, 1]] for idx in face], np.int32)
            pts = pts.reshape((-1, 1, 2))
            cv2.polylines(mask, [pts], True, (0, 255, 0))

        return mask

[stevenwudi]

Here is one of the example images from training sequences:

[stevenwudi]

It would be really great if we don't need 3rd-party rendering software (as I have done). But the not strictly alignment of the mesh using my code above would make our algorithm not working properly. Hence, it will be greatly appreciated if someone can investigate the misalignment issue. Many thanks!

[stevenwudi]

Hey, I am wondering whether the misalignment could be caused by distorted image lens. Hence, we need the distortion coefficients for the correction?

[jianghe01]

Hi steven, i ve seen your example image, than i guess u maybe use the car fitting result rotation pose as quaternion. i think u can try to use it as Eularian angle. hope can help u.

[stevenwudi]

Hi @jianghe01 , thanks for the heads up. After close examination, when I project the 3D vertices to 2D image plane, I should use rotation vector instead of the euler angles (yaw, pitch, roll).

Hence, using the following should correct the misalignment.

rmat = uts.euler_angles_to_rotation_matrix(pose[:3])
rvect, _ = cv2.Rodrigues(rmat)
imgpts, jac = cv2.projectPoints(np.float32(car['vertices']), rvect, pose[3:], self.intrinsic, distCoeffs=None)

If the mask of the mesh is required, we can draw the triangle lines as:

mask = np.zeros(image.shape)
for face in car['faces'] - 1:
    pts = np.array([[imgpts[idx, 0, 0], imgpts[idx, 0, 1]] for idx in face], np.int32)
    pts = pts.reshape((-1, 1, 2))
    cv2.polylines(mask, [pts], True, (0, 255, 0))

[stevenwudi]

Here is the produced mesh overlay image, it's generally satisfactory enough (171206_034808931_Camera_5):

Nevertheless, after some examination, we found out that some car_id are rather different than the real car models, for example the closest car and the car under 40km/h sign (orientation issue) in (171206_034636094_Camera_5), is it normal?

[pengwangucla]

@stevenwudi From those examples I think you got every thing right. How about the first image you showed with misalignment, is it the same with the example in the demo ? If it is, this might due to some error labelling.

[XBSong]

@stevenwudi , Thanks for the feedback, we generate the types of some cars automatically and check the results to guarantee the accuracy, but it may exist some mistakes, we believe most of the types of cars is right. We will update the results of 171206_034636094_Camera_5 soon.

[XBSong]

@stevenwudi , Hi, we have updated the result of 171206_034636094_Camera_5, you can re-download the dataset if it is needed. Thanks.

[stevenwudi]

@pengwangucla @XibinSong Hi, Yes. I think the mesh problem is solved. However, there is a new issue in term of using camera intrinsic in the code. I have made an issue in #3

[Jerrypiglet]

@pengwangucla @XibinSong Hi, Yes. I think the mesh problem is solved. However, there is a new issue in term of using camera intrinsic in the code. I have made an issue in #3

Hey Di, did you get a chance to fix the GLEW issue of the renderer? @stevenwudi

[stevenwudi]

@Jerrypiglet Hi Jerry. No, unfortunately I didn't manage to fix the GLEW issue. So in the end, I didn't use the provided render at all. Cheers

[ShreyasSkandan]

It seems init GLEW is not necessary for successfully render a depth map. I have already update to rm the line of ERROR message. You may check it out again.

I'm trying to use proj_point_cloud.py in self_localization but I'm getting the same "Failed to initialize GLEW" problem. You mention that I should be able to generate a depth image without the renderer, could you provide more details regarding this? Thanks.

[pengwangucla]

I'm trying to use proj_point_cloud.py in self_localization but I'm getting the same "Failed to initialize GLEW" problem. You mention that I should be able to generate a depth image without the renderer, could you provide more details regarding this? Thanks.

I was using ubuntu 14.04, haven't test with other platform. Maybe need deeper debug : P

[ShreyasSkandan]

I'm trying to use proj_point_cloud.py in self_localization but I'm getting the same "Failed to initialize GLEW" problem. You mention that I should be able to generate a depth image without the renderer, could you provide more details regarding this? Thanks.

I was using ubuntu 14.04, haven't test with other platform. Maybe need deeper debug : P

Oh, alright. Thanks anyway!

[ThoBaro]

I solved the GLEW error on Ubuntu 16.04 / python 2 using a specific nvidia driver version. GLEW throws an error since the context is not properly initialized, which is caused by a bug/missing piece in the newer nvidia drivers. Solution from this post:

from console mode (ctrl + alt + F1) with stopped lightdm (sudo service lightdm stop)
$ sudo apt purge *nvidia*
$ # WARNING: The following driver version is a potential risk to your system since it's deprecated
$ wget https://launchpad.net/ubuntu/+archive/primary/+files/nvidia-graphics-drivers-384_384.90.orig.tar.gz # 
$ tar xzf nvidia-graphics-drivers-384_384.90.orig.tar.gz
$ cd nvidia-graphics-drivers-384_384.90
$ chmod u+x NVIDIA-Linux-x86_64-384.90-no-compat32.run
$ sudo ./NVIDIA-Linux-x86_64-384.90-no-compat32.run

After that i was able to run the example script.

[ThoBaro]

Nevertheless, after some examination, we found out that some car_id are rather different than the real car models, for example the closest car and the car under 40km/h sign (orientation issue) in (171206_034636094_Camera_5), is it normal?

@stevenwudi: Was this pose problem fixed for you? I downloaded the recent version and still have this issue. Also the car left to the problematic car is turned upside down:

I'm glad for any help!

[stevenwudi]

Nevertheless, after some examination, we found out that some car_id are rather different than the real car models, for example the closest car and the car under 40km/h sign (orientation issue) in (171206_034636094_Camera_5), is it normal?

@stevenwudi: Was this pose problem fixed for you? I downloaded the recent version and still have this issue. Also the car left to the problematic car is turned upside down:

I'm glad for any help!

Well, I didn't use the provided rendering tool but using the script that I have provided above. I believe the mistakes in the car rotations are only few so it does not matter much. But from you low resolution image, it seems that one car (deep blue) is upside down, that does not seem correct.

[ThoBaro]

Well, I didn't use the provided rendering tool but using the script that I have provided above. I believe the mistakes in the car rotations are only few so it does not matter much. But from you low resolution image, it seems that one car (deep blue) is upside down, that does not seem correct.

@stevenwudi: Okay, thanks for the feedback! I'm very confused about the flipped car. I'm also using my own code with a render engine that uses a rotation matrix as an input. I build it from the euler angles and the math seems correct. I even redownloaded the labels. But since the dataset was updated after your rendering can you do me the favor and compare the labels files? Here's the current one.

171206_034636094_Camera_5.json.txt

[stevenwudi]

@Tbarowski , Here is favor: Using your provided json file, we rendered the mesh as below which is different from what you get. I have cleaned up a script as: https://github.com/stevenwudi/6DVNET/blob/master/tools/ApolloScape_car_instance/demo_mesh.py You probably only need the files from: https://github.com/stevenwudi/6DVNET/tree/master/tools/ApolloScape_car_instance

Moreover, our team has visually screened all the training and validation images and manually circle the corrupted images out. Here is the list: https://github.com/stevenwudi/6DVNET/tree/master/tools/ApolloScape_car_instance/split_delete

Best Di Wu

[ThoBaro]

@Tbarowski , Here is favor: Using your provided json file, we rendered the mesh as below which is different from what you get. I have cleaned up a script as: https://github.com/stevenwudi/6DVNET/blob/master/tools/ApolloScape_car_instance/demo_mesh.py You probably only need the files from: https://github.com/stevenwudi/6DVNET/tree/master/tools/ApolloScape_car_instance

Moreover, our team has visually screened all the training and validation images and manually circle the corrupted images out. Here is the list: https://github.com/stevenwudi/6DVNET/tree/master/tools/ApolloScape_car_instance/split_delete

Best Di Wu

Thanks for all your efforts!

Unfortunately I'm getting a different result with your code:

Also, i am not able to run your code directly since I'm missing models as reported in https://github.com/ApolloScapeAuto/dataset-api/issues/13. I'm using the models from 3d_car_instance_sample.tar.gz.

Is there any other source for the models? I'm quite sure that the error lies in the models. How many models do you have / do you have files for the models that I miss (see other ticket).