integrate yolo as ML backend into my label tasks

[JasonSloan]

Hi, i tried to integrate the ML models into my label tasks, everything seemd to work fine but no predictions showed though.

Env: label-studio was running in a docker container while the ML-backend was running in the container of the container, but i checked the ENV variable as well as the mapping directory inside the ML-backend container and they were all correctly set.

Tests: I tested in my web browser of the connection between label-studio and ML-backend and it worked fine.

Model weight: I put an official yolov8m.pt file downloaded from github into the models folder and i checked inside the ML-backend container that it was really being there.

Settings: I set the label template to yolo and wrote the configurations code below:
<View> <Image name="image" value="$image"/> <RectangleLabels name="label" toName="image" model_score_threshold="0.25" model_path="[yolov8n.pt](http://yolov8n.pt/)" opacity="0.1"> <Label value="Person" background="red"/> <Label value="person" background="red"/> <Label value="Car" background="blue"/> </RectangleLabels> </View>

Finally, i checked the images inside the project but no person bounding boxes were shown. Besides, I was pretty sure that the yolov8m.pt can successfully detected them.

So would you please tell me that where i was doing wrong?

[makseq]

Hi,

1. This line looks wrong in your labeling config

 model_path="[yolov8n.pt](http://yolov8n.pt/)"

it should be

model_path="yolov8n.pt"

2. You don't need to download official models manually, they will be downloaded automatically.
3. Most likely, you didn't specify LABEL_STUDIO_URL and LABEL_STUDIO_API_KEY in the docker-compose.yml file.
4. Check ML backend logs, the problem should be mentioned there.