How to load the Custom Trained Model for Inference on new Image set

[s91-maker]

Hi, I trained on model using custom Data, but now i am unable to load that custom model(.pth) for prediction.

Can you please provide a inference example, Basically the method to load the model back.

The get Model function was

def get_model(num_keypoints, weights_path=None):

anchor_generator = AnchorGenerator(sizes=(32, 64, 128, 256, 512), aspect_ratios=(0.25, 0.5, 0.75, 1.0, 2.0, 3.0, 4.0))
model = torchvision.models.detection.keypointrcnn_resnet50_fpn(pretrained=False,
                                                               pretrained_backbone=True,
                                                               num_keypoints=num_keypoints, # 4 in my case
                                                               num_classes = 3, # Background is the first class, object is the second class
                                                               rpn_anchor_generator=anchor_generator)

if weights_path:
    state_dict = torch.load(weights_path)
    model.load_state_dict(state_dict)        
    
return model 

Model Saving

torch.save(model.state_dict(), 'custom_keypointsrcnn_weights.pth')

Now the Inference Part

import torch
import torchvision
from torchvision.models.detection.rpn import AnchorGenerator
anchor_generator = AnchorGenerator(sizes=(32, 64, 128, 256, 512), aspect_ratios=(0.25, 0.5, 0.75, 1.0, 2.0, 3.0, 4.0))
m = torchvision.models.detection.keypointrcnn_resnet50_fpn(pretrained=False,pretrained_backbone=False,num_keypoints=4,num_classes = 3, rpn_anchor_generator=anchor_generator)

m.load_state_dict(torch.load("custom_keypointsrcnn_weights.pth"))
Traceback (most recent call last):
File "", line 1, in
File "C:\Python39\lib\site-packages\torch\nn\modules\module.py", line 1406, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for KeypointRCNN:
Missing key(s) in state_dict: "backbone.fpn.inner_blocks.0.weight", "backbone.fpn.inner_blocks.0.bias", "backbone.fpn.inner_blocks.1.weight", "backbone.fpn.inner_blocks.1.bias", "backbone.fpn.inner_blocks.2.weight", "backbone.fpn.inner_blocks.2.bias", "backbone.fpn.inner_blocks.3.weight", "backbone.fpn.inner_blocks.3.bias", "backbone.fpn.layer_blocks.0.weight", "backbone.fpn.layer_blocks.0.bias", "backbone.fpn.layer_blocks.1.weight", "backbone.fpn.layer_blocks.1.bias", "backbone.fpn.layer_blocks.2.weight", "backbone.fpn.layer_blocks.2.bias", "backbone.fpn.layer_blocks.3.weight", "backbone.fpn.layer_blocks.3.bias", "rpn.head.conv.weight", "rpn.head.conv.bias".
Unexpected key(s) in state_dict: "backbone.fpn.inner_blocks.0.0.weight", "backbone.fpn.inner_blocks.0.0.bias", "backbone.fpn.inner_blocks.1.0.weight", "backbone.fpn.inner_blocks.1.0.bias", "backbone.fpn.inner_blocks.2.0.weight", "backbone.fpn.inner_blocks.2.0.bias", "backbone.fpn.inner_blocks.3.0.weight", "backbone.fpn.inner_blocks.3.0.bias", "backbone.fpn.layer_blocks.0.0.weight", "backbone.fpn.layer_blocks.0.0.bias", "backbone.fpn.layer_blocks.1.0.weight", "backbone.fpn.layer_blocks.1.0.bias", "backbone.fpn.layer_blocks.2.0.weight", "backbone.fpn.layer_blocks.2.0.bias", "backbone.fpn.layer_blocks.3.0.weight", "backbone.fpn.layer_blocks.3.0.bias", "rpn.head.conv.0.0.weight", "rpn.head.conv.0.0.bias".

Even tried with get_model function getting the Same Error

Traceback (most recent call last):
File "D:\Projects\custom_KP\inference_kp.py", line 47, in
model = get_model(4,'custom_keypointsrcnn_weights.pth')
File "D:\Projects\custom_KP\inference_kp.py", line 35, in get_model
model.load_state_dict(state_dict)
File "C:\Python39\lib\site-packages\torch\nn\modules\module.py", line 1406, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for KeypointRCNN:
Missing key(s) in state_dict: "backbone.fpn.inner_blocks.0.weight", "backbone.fpn.inner_blocks.0.bias", "backbone.fpn.inner_blocks.1.weight", "backbone.fpn.inner_blocks.1.bias", "backbone.fpn.inner_blocks.2.weight", "backbone.fpn.inner_blocks.2.bias", "backbone.fpn.inner_blocks.3.weight", "backbone.fpn.inner_blocks.3.bias", "backbone.fpn.layer_blocks.0.weight", "backbone.fpn.layer_blocks.0.bias", "backbone.fpn.layer_blocks.1.weight", "backbone.fpn.layer_blocks.1.bias", "backbone.fpn.layer_blocks.2.weight", "backbone.fpn.layer_blocks.2.bias", "backbone.fpn.layer_blocks.3.weight", "backbone.fpn.layer_blocks.3.bias", "rpn.head.conv.weight", "rpn.head.conv.bias".
Unexpected key(s) in state_dict: "backbone.fpn.inner_blocks.0.0.weight", "backbone.fpn.inner_blocks.0.0.bias", "backbone.fpn.inner_blocks.1.0.weight", "backbone.fpn.inner_blocks.1.0.bias", "backbone.fpn.inner_blocks.2.0.weight", "backbone.fpn.inner_blocks.2.0.bias", "backbone.fpn.inner_blocks.3.0.weight", "backbone.fpn.inner_blocks.3.0.bias", "backbone.fpn.layer_blocks.0.0.weight", "backbone.fpn.layer_blocks.0.0.bias", "backbone.fpn.layer_blocks.1.0.weight", "backbone.fpn.layer_blocks.1.0.bias", "backbone.fpn.layer_blocks.2.0.weight", "backbone.fpn.layer_blocks.2.0.bias", "backbone.fpn.layer_blocks.3.0.weight", "backbone.fpn.layer_blocks.3.0.bias", "rpn.head.conv.0.0.weight", "rpn.head.conv.0.0.bias".

tried many option on pretrained=False/True, pretrained_backbone=False/True, but no use.