Dear OAK-D support team,
I recently started to train a model with the intent of using it on OAK-D camera.
For this, I referred to https://colab.research.google.com/github/luxonis/depthai-ml-training/blob/master/colab-notebooks/Easy_TinyYOLOv4_Object_Detector_Training_on_Custom_Data.ipynb#scrollTo=FcGqlLT3un1O
I successfully trained the custom model and was able to make prediction using it on an Image.
However, I continued with the steps for convert model so it can be used on DepthAI as in the article
This requires three steps: 1. Convert model to Tensorflow frozen model. 2. Convert Tf model to OpenVINO IR files .xml and .bin. 3. Compile a blob from the IR files. The blob can be used for inference on DepthAI modules.
I converted my model best weight to Tensorflow frozen and have the .pb file.
I also carried the 2 and 3 step and have the blob file.
However, when i tried to use my model in the camera, I get thes error messages
Input tensor 'input_1' (0) exceeds available data range. Data size (519168B), tensor offset (0), size (1108992B) - skipping inference
Mask is not defined for output layer with width '1000'. Define at pipeline build time using: 'setAnchorMasks' for 'side1000'.
Input image (608x608) does not match NN (3x608)
Kindly assist me in resolving this challenge.
Thanks