I work with multi-channel images (5 channels). I'm trying to train an object detection model with this images but I haven't found any good support to do it.
I attempt to train a faster RCNN inception resnet v2 network.
3. Additional context
To be more specific, I'm able to modify the input layer ([3, 3, 3, 32] to [3, 3, 5, 32]) in order to adapt one pre-trained model and I'm able to export this model and perform inference with it.
For this, I made modifications based on this: https://github.com/minhnhat93/tf_object_detection_multi_channels
The problem comes when I want to train a model using multiple-channel images.
I've tried using the --num_additional_channels option in model_main.py, but I couldn't make it work.
Prerequisites
Please answer the following question for yourself before submitting an issue.
1. The entire URL of the file you are using
https://github.com/tensorflow/models/tree/r1.13.0/research/object_detection
2. Describe the feature you request
I work with multi-channel images (5 channels). I'm trying to train an object detection model with this images but I haven't found any good support to do it.
I attempt to train a faster RCNN inception resnet v2 network.
3. Additional context
To be more specific, I'm able to modify the input layer ([3, 3, 3, 32] to [3, 3, 5, 32]) in order to adapt one pre-trained model and I'm able to export this model and perform inference with it. For this, I made modifications based on this: https://github.com/minhnhat93/tf_object_detection_multi_channels
The problem comes when I want to train a model using multiple-channel images.
I've tried using the
--num_additional_channels
option in model_main.py, but I couldn't make it work.4. Are you willing to contribute it? (Yes or No)
Yes