- Edited
Hi DarshitDesai
Perhaps the SD capacity is too low?
Hi DarshitDesai
Perhaps the SD capacity is too low?
jakaskerl So the memory card is 32 gbs
Hi DarshitDesai
I see, could you try:
Let me know if it works.
Thanks,
Jaka
jakaskerl I'll check the debugger. Does it come with premium version or free version?
Etcher runs only with admin approval
Redownload didn't work with v9 and v8
Hi DarshitDesai
ctrl+shift+i to open the logs.
Thanks,
Jaka
jakaskerl It says that the unmount sd card failed in the console after etching the OS?
jakaskerl Hi I was somehow able to make it work with one of the linux pcs I had. But now when I try to run a code which worked on the Desktop PC it gives me the following error
Traceback (most recent call list):
File "/home/pi/Desktop/testrun.py", line 2, in <module>
from depthai_sdk import OakCamera
ImportError: cannot import name 'OakCamera' from 'depthaisdk' (/home/pi/depthai/depthaisdk/src/depthai_sdk/init.py)
I modified the dependencies myself since the linux image which was there didn't have any of the latest components of the Oakcamera SDK. How do I fetch the tracker (X,Y,Z) values from the spatial tracker?
Hi DarshitDesai
Great that you got it working, strange though.
What versions are you now using? Since you said you modified the dependencies I would assume you have the latest.
You can fetch the trackers inside the callback function. https://docs.luxonis.com/projects/sdk/en/latest/fundamentals/packets/#api-usage
You would need to send a trackerpacket to the callback, and print it there.
Thanks,
Jaka
jakaskerl I don't think it was a version issue, When I opened the image, there were some files like the Oakcamera.py and other dependencies which should have been there not present in the depthai/depthai_sdk folder, I just pip installed those and cloned those from github.
About the question, I am combining tracker with spatial calculation of the tracked object, both of them combined give me a x,y,z position for a class of detected object in the visualizer, now I want it raw in the form of a list or maybe a ros topic which I can publish and later subscribe to it so that my robot can act according to it, what are some ways to do that? Note ros is only a middleware example I could think of, I would prefer if something in the sdk itself helped me do it
Hi DarshitDesai
As I have mentioned above, instead of stock visualizer, make your own callback function that will run each time there is a frame ready. Tracker and spatials are both available outputs of the NN component https://docs.luxonis.com/projects/sdk/en/latest/components/nn_component/#nncomponent).
Inside that same callback you can either print a list of all xyz values, or maybe make a publish to a ros topic. This is up to you since ROS is not integrated into SDK as of now.
Thanks,
Jaka
jakaskerl I am still not able to figure out those values, can you tell me the exact api call in the python sdk that I need to type up for getting the x,y,z values?
Here's my code for your reference
from depthai_sdk import OakCamera
import depthai as dai
from depthai_sdk.classes import DetectionPacket
def cb(packet: DetectionPacket):
print(packet.img_detections)
with OakCamera() as oak:
color = oak.create_camera('color')
# List of models that are supported out-of-the-box by the SDK:
# https://docs.luxonis.com/projects/sdk/en/latest/features/ai_models/#sdk-supported-models
nn = oak.create_nn('yolov8n_coco_640x352', color, tracker=True, spatial=True)
nn.config_nn(resize_mode='stretch')
nn.config_tracker(
tracker_type=dai.TrackerType.ZERO_TERM_COLOR_HISTOGRAM,
track_labels=[0], # Track only 1st object from the object map. If unspecified, track all object types
# track_labels=['person'] # Track only people (for coco datasets, person is 1st object in the map)
assignment_policy=dai.TrackerIdAssignmentPolicy.SMALLEST_ID,
max_obj=1, # Max objects to track, which can improve performance
threshold=0.1 # Tracker threshold
)
nn.config_spatial(
bb_scale_factor=0.3, # Scaling bounding box before averaging the depth in that ROI
lower_threshold=500, # Discard depth points below 30cm
upper_threshold=8000, # Discard depth pints above 10m
# Average depth points before calculating X and Y spatial coordinates:
calc_algo=dai.SpatialLocationCalculatorAlgorithm.AVERAGE
)
oak.visualize([nn.out.tracker], fps=True)
# oak.callback(nn.out.tracker, callback=cb)
oak.visualize([nn.out.image_manip], fps=True)
oak.visualize([nn.out.spatials], fps=True)
oak.visualize(nn.out.passthrough)
# oak.start(blocking=True)
oak.start(blocking=True)
Hi DarshitDesai
I think you should be using trackerpacket if you are sending trackers as your callback arguments.
Tracklets should give you a list of all tracked objects and their positions.
Thanks,
Jaka
jakaskerl there are two detection api packets, SpatialMappingBbpacket and TrackerPacket, which of the x,y,z are more accurate or have optimal estimates from the kalman filter?
Hi DarshitDesai
Tracker packet is the SDK equivalent for the the tracker message in API, so you should use that. Filter can be applied with tracker_config when tracker is enabled.
Thanks,
Jaka
jakaskerl In my code I did use Spatial tracking feature, Wouldn't the spatialmapping packet have good results?
Hi DarshitDesai
Should work as well yes, since it includes the info for spatials. However there is no tracking here to my knowledge. It's basically just a depth frame with bb mappings.
Thanks,
Jaka
The depth sdk everytime tries to connect to the internet and download the yolov8n blob model, Is there a way to store it on device and use that? I am using a raspberry pi and it is tedious to connect it to the internet again and again
Hi DarshitDesai
I think the downloaded models should be stored in cache and run locally once downloaded. Alternatively you can download the json, bin and xml file you get when converting a model and specify it when creating a new camera.
with OakCamera(args="model.json") as oak: #ignore this
Thanks,
Jaka