Hi, I am working on a project using the OAK-D camera and facing an issue with linking nodes in the pipeline. My goal is to classify the key points detected by the camera for different yoga poses using a custom neural network. Specifically, I'm trying to pass the output of a landmark detection neural network to my pose classification neural network as input. The issue is that when I use **_pc_nn.out.link(manager_script.inputs['from_pc_nn'])_** to link the pose classification output to the manager_script input, the pipeline starts running and a new window opens showing the key points being detected. However, a few seconds later the program stops working and I'm not able to classify the key points. If I don't use this link **pc_nn.out.link(manager_script.inputs['from_pc_nn'])**, the pipeline works fine _**(detecting and marking landmarks)**_. ``` Here is the code of the pipeline: ` def create_pipeline(self): print("Creating pipeline...") # Start defining a pipeline pipeline = dai.Pipeline() pipeline.setOpenVINOVersion(dai.OpenVINO.Version.VERSION_2021_4) self.pd_input_length = 224 self.lm_input_length = 256 self.pc_input_length = 66 # ColorCamera print("Creating Color Camera...") cam = pipeline.create(dai.node.ColorCamera) cam.setResolution(dai.ColorCameraProperties.SensorResolution.THE_1080_P) cam.setInterleaved(False) cam.setIspScale(self.scale_nd[0], self.scale_nd[1]) cam.setFps(self.internal_fps) cam.setBoardSocket(dai.CameraBoardSocket.RGB) if self.crop: cam.setVideoSize(self.frame_size, self.frame_size) cam.setPreviewSize(self.frame_size, self.frame_size) else: cam.setVideoSize(self.img_w, self.img_h) cam.setPreviewSize(self.img_w, self.img_h) if not self.laconic: cam_out = pipeline.create(dai.node.XLinkOut) cam_out.setStreamName("cam_out") cam_out.input.setQueueSize(1) cam_out.input.setBlocking(False) cam.video.link(cam_out.input) #Define manager script node manager_script = pipeline.create(dai.node.Script) manager_script.setScript(self.build_manager_script()) #Define pose classification pre processing print("Creating Pose Classification pre processing image manip...") pre_pc_manip = pipeline.create(dai.node.ImageManip) pre_pc_manip.setMaxOutputFrameSize(self.pc_input_length*self.pc_input_length*3) pre_pc_manip.setWaitForConfigInput(True) pre_pc_manip.inputImage.setQueueSize(1) pre_pc_manip.inputImage.setBlocking(False) cam.preview.link(pre_pc_manip.inputImage) manager_script.outputs['pre_pd_manip_cfg'].link(pre_pd_manip.inputConfig) #Define link to send result to host manager_out = pipeline.create(dai.node.XLinkOut) manager_out.setStreamName("manager_out") manager_script.outputs['host'].link(manager_out.input) #Define landmark pre processing image manip print("Creating Landmark pre processing image manip...") pre_lm_manip = pipeline.create(dai.node.ImageManip) pre_lm_manip.setMaxOutputFrameSize(self.lm_input_length*self.lm_input_length*3) pre_lm_manip.setWaitForConfigInput(True) pre_lm_manip.inputImage.setQueueSize(1) pre_lm_manip.inputImage.setBlocking(False) cam.preview.link(pre_lm_manip.inputImage) manager_script.outputs['pre_lm_manip_cfg'].link(pre_lm_manip.inputConfig) print("Creating DiveideBy255 Neural Network...") divide_nn = pipeline.create(dai.node.NeuralNetwork) divide_nn.setBlobPath(self.divide_by_255_model) pre_lm_manip.out.link(divide_nn.input) #Define landmark model print("Creating Landmark Neural Network...") lm_nn = pipeline.create(dai.node.NeuralNetwork) lm_nn.setBlobPath(self.lm_model) # lm_nn.setNumInferenceThreads(1) divide_nn.out.link(lm_nn.input) lm_nn.out.link(manager_script.inputs['from_lm_nn']) #Define Pose Classify model print("Creating Pose Classify Neural Network...") pc_nn = pipeline.create(dai.node.NeuralNetwork) pc_nn.setBlobPath(self.pc_model) pre_pc_manip.out.link(pc_nn.input) lm_nn.out.link(pc_nn.input) pc_nn.out.link(manager_script.inputs['from_pc_nn']) print("Pipeline created.") return pipeline ` ``` If I don't link this, the pipeline works fine and just detects and landmarks key points. However, I want to classify these key points to identify the yoga poses. Could someone please help me understand what might be causing this issue and how I can modify my code to link the output of my custom node to the input of the manager script? This is basically capturing the information from the manager_script node _I need to classify the detected landmarks/key points into specific yoga poses. To do this, I'm trying to pass the landmark output to feed it into the pose classify neural network. However, I'm having trouble making this work. I'm not sure what changes I need to make to my node to enable it to send data to the manager-script node, which in turn would feed the data to the pose classify network._ ``` ` def next_frame(self): self.fps.update() if self.laconic: video_frame = np.zeros((self.frame_size, self.frame_size, 3), dtype=np.uint8) else: in_video = self.q_video.get() video_frame = in_video.getCvFrame() #Get result from device res = marshal.loads(self.q_manager_out.get().getData()) # self.lm_score_thresh: body = mpu.Body() body.rect_x_center_a = res["rect_center_x"] * self.frame_size body.rect_y_center_a = res["rect_center_y"] * self.frame_size body.rect_w_a = body.rect_h_a = res["rect_size"] * self.frame_size body.rotation = res["rotation"] body.rect_points = mpu.rotated_rect_to_points(body.rect_x_center_a, body.rect_y_center_a, body.rect_w_a, body.rect_h_a, body.rotation) body.lm_score = res["lm_score"] self.lm_postprocess(body, res['lms'], res['lms_world']) if self.xyz: if res['xyz_ref'] == 0: body.xyz_ref = None else: if res['xyz_ref'] == 1: body.xyz_ref = "mid_hips" else: # res['xyz_ref'] == 2: body.xyz_ref = "mid_shoulders" body.xyz = np.array(res["xyz"]) if self.smoothing: body.xyz = self.filter_xyz.apply(body.xyz) body.xyz_zone = np.array(res["xyz_zone"]) body.xyz_ref_coords_pixel = np.mean(body.xyz_zone.reshape((2,2)), axis=0) ` ``` Thanks for your help in advance!

Hi @"rb210002"#p7474 It is incredibly difficult to debug this code since i'm not getting the full picture of what might be going on. Few questions: - "However, a few seconds later the program stops working and I'm not able to classify the key points." So the program exits or just freezes. In case it freezes, I would check the resources (shaves, cmx) you are using for the pipeline, since it might be that you are pushing it too hard. You can do that by running `DEPTHAI_LEVEL DEBUG python3 ` - Is the script correctly forwarding data from pc_nn? It looks like the script queue could be congested which would prevent anything from going out. Perhaps try checking if pose classification works on the host (the rest of the pipeline should remain on the device). Thoughts? Jaka

Hi @"jakaskerl"#1112, I apologize for my delayed response. I am experiencing an issue with the program where it freezes after a few seconds. Upon further investigation, I noticed that the program is utilizing 2.49 Mb out of 2.50 CMX. I have enabled DEBUG mode and here is the output that I am receiving: [URL=https://i.imgur.com/EBi6qo3.png][IMG]https://i.imgur.com/EBi6qo3h.png[/IMG][/URL] Could you please help me verify if the script is correctly forwarding data from pc_nn? Also, I would appreciate it if you could clarify your previous suggestion - "Perhaps try checking if pose classification works on the host (the rest of the pipeline should remain on the device)." Do you mean that I should run the pipeline on the host instead of the OAK-D? I would appreciate any further guidance on this. Thank you for your assistance.

Hi @"rb210002"#p7534 , You can use pipeline graph which also shows FPS of all links: https://github.com/luxonis/depthai_pipeline_graph Thanks, Erik

Hello @"erik"#p7538 , I'm not sure how the pipeline graph will be beneficial in this specific situation. While I understand that pipeline graphs are used to visualize pipelines, I'm uncertain how it can help us in this particular scenario. Could you please clarify this for me?

@"rb210002"#p7540 you mentioned > Could you please help me verify if the script is correctly forwarding data from pc_nn? With pipeline graph you can see FPS of each link, so you can check whether script node is forwarding data to pc_nn output. Or is this inside Script node? If so, you can use [script node logging](https://docs.luxonis.com/projects/api/en/latest/tutorials/debugging/#script-node-logging).

Hi @"erik"#175 , thank you for your previous help. I'm new to this and I'm having trouble finding a way to view the FPS of each link. I tried using script node logging, but it's not very clear to me. I also looked at the pipeline graph to see if the script is forwarding data from pc_nn correctly, but I'm still struggling. Could you please provide some guidance or resources on how to accomplish this? Thank you for your assistance.

Hi @"rb210002"#p7543 Perhaps you are using the wrong (or outdated) version of pipeline graph. Try and install latest from: https://github.com/luxonis/depthai_pipeline_graph Hope this helps with the FPS, Jaka

Hi @"jakaskerl"#p7546 , I am using the latest version of pipeline graph.

Maybe share a screenshot @"rb210002"#p7551 ?

Hi @"erik"#p7555 , I wanted to give you an update regarding the version of the software I've been using. I recently discovered that I had been using version 0.0.3, but I've now updated it to version 0.0.5. I actually tried to install the update a few days ago, but it seems that I inadvertently installed an old version. Apologies for any confusion this may have caused.

OAK-D pipeline stops responding when linking nodes

rb210002

Hi team,

Looking for a resolution Kindly Help

Regards

jakaskerl

Hey rb210002
sorry for the late reply,
the scripts on the drive look empty.

Thanks,
Jaka

rb210002

Hi jakaskerl , can you confirm are you able to see the content in the script? If not please let me known

Regards

rb210002

Certainly, here's a possible message:

Hi @jakaskerl , I wanted to let you know that I checked the script and it's not empty. However, I'm wondering if you might be checking it through Google Drive on your phone? If that's the case, it might be helpful to check it on your desktop instead. Would you mind giving that a try and letting me know if you find anything? Thank you.

jakaskerl

Hi rb210002
I can now.
Will reply when I find something.

Regards,
Jaka

rb210002

Hey jakaskerl , do you find what causing this issue?

jakaskerl

Hi rb210002
Sorry, I've been running on a very busy schedule.

Thanks,
Jaka

AdamPolak

jakaskerl

Is it possible to run this on a C++ program? I set depthai to debug but do not get any logging as is explaiend in the github. Does this print in another console or does it only print in python?

erik

@AdamPolak I believe you can also enable it via depthai, in python the API is like this:

# Connect to device and start pipeline
with dai.Device(pipeline) as device:
    def logging(msg):
        print(msg)

    device.setLogLevel(dai.LogLevel.TRACE) # Or eg. DEBUG
    device.addLogCallback(logging)

AdamPolak

erik

this is perfect thank you.

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