I am using detectron2 model for instant segmentation & object detection .My goal is to deploy this model onto a robot using Viam robotics and they(Viam) only accept a .tflite model when uploading.
I need a script (written in Python) that would take a trained PyTorch model file (.pth extension) and export it to TensorFlow format (.pb). [frozen graph] or .onnx so that I can be able to upload it into the robot
The model was trained using the Facebook’s DETECTRON2 (the pre-trained model was “COCO-InstanceSegmentation/mask_rcnn_X_101_32x8d_FPN_3x.yaml”)
I already have the output “pth” file. The script should take this file as a parameter and return single ‘.pb’ file.
I checked this doc doing tensorflow conversions and it uses the below code for conversion;
# 1. Download the corresponding model from detectron2 model zoo
# 2. Convert:
$ python convert_d2.py --d2-config detectron2/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml --d2-pkl model_final_f10217.pkl --output R50FPN-d2-converted.npz
# the script will print tensorpack configs
'MODE_MASK=True' 'MODE_FPN=True' 'BACKBONE.STRIDE_1X1=True' 'PREPROC.PIXEL_MEAN=[123.675,116.28,103.53]' 'PREPROC.PIXEL_STD=[1.0,1.0,1.0]'
# 3. Use the above configs to verify the conversion is correct:
$ ./predict.py --evaluate out.json --load R50FPN-d2-converted.npz --config DATA.BASEDIR=~/data/coco 'MODE_MASK=True' 'MODE_FPN=True' 'BACKBONE.STRIDE_1X1=True' 'PREPROC.PIXEL_MEAN=[123.675,116.28,103.53]' 'PREPROC.PIXEL_STD=[1.0,1.0,1.0]'
# 4. Naively convert the model to a frozen pb file:
$ ./predict.py --output-pb out.pb --load R50FPN-d2-converted.npz --config DATA.BASEDIR=~/data/coco 'MODE_MASK=True' 'MODE_FPN=True' 'BACKBONE.STRIDE_1X1=True' 'PREPROC.PIXEL_MEAN=[123.675,116.28,103.53]' 'PREPROC.PIXEL_STD=[1.0,1.0,1.0]'
But I would like to know what --d2-pkl stands for and how can I use my custom trained model(‘.pth’) for this conversion. I would like to get your help on this, please.